Procurement orchestration is a game-changing strategy.

Powered by cutting-edge orchestration platforms, it harmonises automated business processes across teams and seamlessly integrates with existing systems. It’s the secret sauce for streamlining all procurement-related activities, wrapping around an organisation’s current infrastructure while catering to the diverse working styles and preferences of employees.

Unlike traditional tech solutions that simply pile onto an organisation’s existing stack, orchestration transforms how companies leverage their unique blend of people, data, and technology. Its true promise? Empowering internal shared service teams to take full control of the tools they use, breaking free from outdated, restrictive tech models. Legacy systems often isolate procurement functions, creating operational silos that slow down response times and hinder alignment with stakeholders.

Orchestration not only modernises procurement processes but also simplifies user experience. Gone are the days of drowning in unnecessary technology or forcing employees to adapt to clunky systems. Orchestration flips the script, making technology work for teams—not the other way around. It dissolves the silos that typically isolate working environments, creating a fluid ecosystem where stakeholders no longer need to log into ERP or P2P platforms just to submit or approve requests. 

One of the most compelling aspects of orchestration is its adaptability. Orchestration layers can be implemented over existing infrastructure, enabling organisations to leverage their current investments while enhancing overall capabilities. Procurement orchestration doesn’t just connect systems; it connects people, innovation, and efficiency—unlocking a smarter, more collaborative way to work.

The journey to ORO Labs

ORO Labs is the procurement orchestration platform for modern companies. It is on a mission to make processes better, faster and more agile in procurement and supply chain. ORO offers self-driving workflows which enable more efficient, collaborative, compliant purchasing with a personalised user experience and smarter decision-making. 

Dharani Jeyaprakasam is a Solution Design Architect at ORO Labs. Having previously served 17 years at IBM in a variety of roles, Jeyaprakasam joined ORO Labs after feeling dejected about whether orchestration mattered to the world. After speaking with CEO and founder Sudhir Bhojwani, she realised she wanted to join the journey. “I was just blown away by the passion that Sudhir showed. This is especially when it comes to the problems we were trying to solve,” explains Jeyaprakasam. “There was this honest person trying to give me the same information that I felt myself. He was honest and accepting that there is a flaw in the product and that is what we’re trying to fix. And that honesty was the real attracting factor for me.”

Shared Vision

Sabih Rozales is also a Solution Design Architect at ORO Labs. He explains that what brings employees within ORO together is having a shared vision to a common goal. For Rozales, he served 14 years at Vodafone prior to ORO Labs and it was the idea of discovering a simplified way of orchestration that convinced him about the career switch.

“I was really enjoying the orchestration journey because it was allowing us to build what we want rather than be framed from the solutions that we get from the market,” he discusses. “I questioned whether there was a better way of doing it and how we brought AI and intelligence into it too. After meeting with the founders of ORO and I was really impressed with what they have already built and their passion for the future and the roadmap ahead. It was quite an instant decision to leave after 15 years in a great company such as Vodafone and move to become part of a solution provider.”

Drawing on Experience

Both Jeyaprakasam and Rozales were involved in building custom orchestration solutions prior to the recent explosion of procurement orchestration tools which have provided them a front-row seat to recent transformation. “When I started in procurement, we used a tool called IBM Lotus Notes 20 years ago,” explains Rozales. “While it wasn’t officially an orchestration tool, it could handle various processes, like configuring workflows for expenses or procurement requests. However, as SaaS solutions emerged, we had to adapt our processes to fit their limitations, making procurement less user-friendly.”

Jeyaprakasam believes that one major challenge with building custom solutions is integration. She explains that connecting to various applications becomes a significant hurdle, especially when dealing with legacy systems like financial ERPs. “Developing in-house solutions often requires technical resources and results in a complex system architecture,” she explains. “For example, it once took us five months just to figure out integrations. This was because we lacked the necessary expertise for older systems. In my view, solving technology complexity is much harder than addressing process complexity.

Overcoming Disruption

“Custom-built products often become too technology-heavy, making updates and changes difficult. This is why I appreciate solutions that are easy to integrate. As a non-technical person with a process-focused background, I can explore and work with technology but can’t sit back and build codes. Yet, I was able to build processes within weeks at ORO Labs because the system is so user-friendly. Integrations that I once thought would take weeks now only take days. My biggest takeaway is that companies often overcomplicate their technology stack instead of buying off the shelf and putting it in.”

Reflecting on past experiences, Jeyaprakasam reveals that her team could have achieved significantly more with the correct tools. Jeyaprakasam explains that the supplier onboarding and intake processes she worked on at IBM were complicated by differences in categories and countries. “The tools we used often required technical expertise, so non-technical users like me couldn’t make changes on our own,” she tells us. “Even a small tweak, like changing a button from ‘Yes’ to ‘Approve’ had to go through the CIO or technology team. This meant long queues, multiple reviews, and a frustratingly slow process. With the tool I’m using now, I can easily make changes myself. If we had access to something like this back then, it would have made a huge difference. I’m sure IBM users would have been much happier.”

Transformational Tech

Rozales explains that ORO Labs technology is a game-changer because it breaks down silos and allows for better collaboration. According to Rozales, in previous projects he has been involved in, there was always a separation between the applications used by end-users and where processes, rules, and forms were set up. “With ORO, I feel like we’re creating a completely different experience,” he tells us. “Now, I can see what’s happening, understand what triggers what, and even share ideas to improve how things are prepared for customers. This transparency not only boosts confidence but also makes me feel like I’m part of the process. Customers, too, can see what’s going on and contribute ideas, like suggesting a question to add or changing the sequence of steps.”

In today’s world, businesses require different things than they did 20 years ago. Indeed, the procurement function has undergone a seismic technology transformation and the impossible is now possible due to an acceleration of next-generation digital tools. “The procurement tech industry has significantly evolved over the last decade, with many new solutions emerging, particularly for purchasing,” discusses Rozales. “One big challenge has been tying these solutions together. For example, whether someone is buying pencils, making a donation, or managing a large implementation project, they might need different tools and systems. But how do people know which tool to use or how to raise the right request?

“As systems became more complex, the lack of an orchestration solution made things harder. Whenever a new solution was introduced, there was always hesitation around whether this would make things even more complicated, or will it help business users easily find what they need. I think that’s one of the main problems that was holding organisations back as the cost is not just the implementation cost but also the price of bringing innovation to the organisation. I think that was too high.”

Unlocking Value

Despite still being relatively new within ORO Labs, Jeyaprakasam explains that the organisation provides a ‘family feel’ offering a great support system that truly makes a difference. “Coming from a well-established corporate career, there’s a safety net if things go wrong,” she tells us. “But here, everyone genuinely wants you to succeed, and that teamwork has been invaluable. Whenever I face a challenge, I just share it with the team, and within minutes, several people step up to help brainstorm solutions. 

“The clients I’m working with are really seeing the value of orchestration. Some are in the POC stage, while others are already implementing ORO. What’s exciting is how much they trust us—not just to provide the tool but to guide them on their overall procurement processes. They look to us for advice on things like thresholds, process optimisation, and best practices, often asking, ‘Are we doing this right? What does the industry do?’ This trust and collaboration are significant wins for us. It’s not just about technology; it’s about becoming partners in shaping their procurement strategy. Seeing this play out in our current implementations has been incredibly rewarding.”

Future Focused

Looking ahead, Rozales is full of optimism about what the future of procurement looks like. He places particular emphasis on how ORO Labs can play its part in driving the function forward.

“ORO has become a strong, reliable solution that helps organisations effectively manage their needs,” explains Rozales. “Like everything else in life, ORO continues to evolve in positive ways. As new technologies emerge, they will likely become part of ORO’s orchestration capabilities. One of ORO’s key strengths is its simplicity. Users don’t need to worry about which tools they need to raise or track a request—ORO provides everything in one place. Looking ahead, I imagine a future where users might even interact with ORO through voice commands, similar to how we speak to some solutions today. This could mean using ORO not just on laptops or devices but having it act as a digital procurement assistant. Although this isn’t currently a roadmap feature, it’s exciting to think about ORO becoming more than just a tool—transforming into a true partner for its users.”

ORO Difference

Jeyaprakasam adds that where ORO is set to thrive in the market is by offering companies the potential to transform the way they manage their technology ecosystems. “Humanising the experience is exactly what we’re aiming for,” she says. “ORO is a highly procurement-focused product designed to address the specific challenges procurement teams face. Procurement is far from simple, and many companies struggle with issues like fraud and compliance violations, often resulting in costly fines.

“That’s where ORO stands out—it can become an essential part of a company’s DNA. By integrating seamlessly into their procurement processes, ORO helps organisations enforce checks and balances, ensuring compliance and reducing risks. This not only simplifies operations but also saves companies significant amounts of money by preventing compliance issues and potential lawsuits. That’s the exciting future we see for ORO—being the backbone of procurement technology.

“At a high level, I see ORO as becoming the DNA that connects all technologies together. The market is enormous, and many organisations aren’t even aware of orchestration. Some clients have 50 to 60 systems in place and struggle to manage them, leading to significant technology investments. With ORO, they could potentially simplify everything by eliminating unnecessary legacy systems. This one tool can streamline their operations and reduce complexity. That’s what excites me most about the future.”

Procurement software solutions provider Ivalua is the latest in a string of organisations to launch procurement automation tools using conversational artificial intelligence (AI). 

Increasingly, the legacy siloes that defined the procurement process are being broken down. The process has left the back office and, today, requires procurement teams to liaise with stakeholders throughout the business. Procurement teams must collaborate with Finance, IT, Facilities, Legal, HR, and Supply Chain teams to capture new value-creation opportunities. 

At the same time, the frequency and risk level of disruption is on the rise. From political tensions and changing regulatory frameworks to economic pressures, procurement teams are being forced to navigate a complex landscape. The daily challenges procurement professionals face range from lack of technology to supply chain delays, and the function’s increasing importance to the business as a whole leads to rising pressures and employee burnout. 

Pascal Bensoussan, Chief Product Officer (CPO) at Ivalua, identified this as a “persistent challenge in procurement: how to handle an increasing volume of intake requests at enterprise level, while ensuring transparency and compliance.” 

He notes that managing the many, varied requests from stakeholders is often overwhelming for procurement teams. Requests frequently arrive through different channels and often lack the necessary details. This, he explains, can lead to delays and inefficiencies. As procurement becomes a more integrated enterprise service, it needs a user friendly, intelligent front end where employees submit requests. At the same time, it also requires back-end automation to manage and fulfill those requests efficiently and transparently.

Natural language AI onboarding 

The AI-powered Intake Management solution, which launched this week, guides procurement professionals to “express their needs simply and efficiently while ensuring effortless compliance with procurement policies.” Using a built-in orchestration engine, the solution can fulfil each intake request across distributed systems, providing real-time updates on progress, status, and pending approvals. Ivalua claims the solution will foster “a new era of employee engagement, process scalability, and trust.”

Ivalua’s AI-powered Intake Management solution claims to bring “structure to this chaos.” Using AI, the tool provides a “conversational and collaborative experience” for procurement teams. By harnessing natural language processing capabilities, the tool enables procurement professionals to submit multiple types of request—whether related to suppliers, sourcing, contracts, purchases, or even cross-departmental needs like MRO or new employee onboarding—through one unified orchestration system and interface.

Key Capabilities of the Ivalua Intake Management Solution

The Ivalua Intake Management Solution has four main features that make it stand out:

• AI Guidance Throughout the Process. An AI assistant guides employees through the process, helping them provide relevant information by extracting key details from documents. It also asks follow up questions, and offers suggestions when they are stuck.
• Seamless Integration Across Systems. A robust event based integration layer to manage flows across Ivalua and third party applications.
• Actionable & Collaborative Tracking Interface. A dashboard supports teams as they track the progress of requests and collaborate with stakeholders.
• Flexible Configuration. Ivalua uses a no-code platform to help procurement teams set up and adjust intake forms and distributed orchestration workflows more easily.

“Our solution allows procurement leaders to scale up operations, by managing all intake requests efficiently, reducing risk, increasing their impact on company spending, and ultimately providing better service across the organisation,” Bensoussan adds. 

In 2025, all signs point to the ongoing convergence of geopolitical tensions, economic volatility, and sustainability that defined 2024. Increasingly, organisations are placing their procurement functions at the centre of organisations’ efforts to combat these challenges. Consequently, procurement leaders are searching for new ways to mitigate headwinds while transforming the function into a lever for strategic value creation. 

Industry experts widely agree that artificial intelligence (AI) is at the heart of technology-minded procurement leaders’ attempts to generate value and protect both operation and resilience. However, two years after the launch of OpenAI’s Chat-GPT, early adopters of AI tools are struggling to see a reasonable rate of return, and the blue sky promises made by AI advocates are failing to materialise. 

However, there are those who believe that AI — both generative and the more traditional versions — will to play a critical role in how procurement will tackle the obstacles that await in 2025 and beyond. 

While Sam Altman’s goal of an artificial general intelligence (AGI) seem like they’re hitting what people in silicon valley are increasingly calling “the wall”, some believe that 2025 will be the year that generative AI tools start to take on more autonomous, decision-making roles. 

2025 will be the year we see “AI agents” take over procurement

This year, “AI agents powered by Generative AI, aka Agentic AI, will become a reality, accelerating procurement from a transactional department into a strategic force for the business,” argues Vishal Patel, VP Product at Ivalua. According to Patel, “these sophisticated systems will be embedded into comprehensive spend management platforms, designed to perform complex tasks with minimal human intervention.”

Patel believes that the next generation of Large Language Models (LLMs) — the ones that need even more copyrighted data and stolen hollywood scripts or whatever it is they’re feeding them now, than the last generation — will finally have the processing power and diminished propensity to hallucinate fictitious nonsense necessary to “access and analyse data, evaluate options, make informed decisions, and take action. Operating within a multi-layered framework, agents will integrate enterprise and/or other data sources, orchestrate workflows, interact with users and much more.”

Patel notes that, “to date, Generative AI features have operated on a ‘one-and-done’ basis—delivering outputs that serve primarily as drafts or prototypes. However, advances in LLMs now enable multi-agent AI ecosystems that perform complex reasoning, validate outputs, and provide actionable insights.”  

Such a shift in generative AI’s potential would allow tools using the technology to use adaptive, real-time conversational AI capabilities to elevate procurement’s potential, Patel adds. As an example, he highlights the fact that “rather than relying on isolated AI features, smart source-to-pay platforms will leverage AI agents to manage tasks like spend analysis, RFP generation, and contract negotiation autonomously.” This, he continues, will allow procurement professionals “to focus on high-value decisions, driving productivity and strategic value. To leverage AI securely and reliably, organizations must ensure Agentic AI solutions rely on privacy-first multi-instance architecture to isolate sensitive data, utilise no-code tools to increase flexibility and rely on a unified data model to ensure outputs are accurate.”

Unstoppable evolution meets immovable regulation 

The other trend intersecting with procurement and its use of increasingly autonomous AI tools relates to the ways in which governments are working to regulate the technology.  

“2025 will be the year where AI regulation moves from theory to practice,” explains Patel, noting that the new EU AI Act will play a leading role in setting the regulatory pace for AI globally. “Unlike the slow rollout of sustainability regulations, the global nature of AI technology means requirements will cascade rapidly across multiple countries and regions,” he says. 

However, in 2025 Patel predicts that, regardless of regulation, businesses will put into place clear documentation and transparency around AI decision-making—whether required not by governing bodies. “While some organisations may view this as a constraint, these regulations will accelerate AI adoption by providing the governance framework many organisations have been waiting for,” he explains. “The key for businesses will be transforming these compliance measures into AI solutions from the ground up, rather than treating them as an afterthought. For procurement and IT teams, this means really understanding what AI is in the tech that is being purchased, what the data privacy and security policies are, how models are being trained and much more.”

Tonkean, a process orchestration platform for enterprise internal service teams, together with Beroe, a procurement decision intelligence solution company, has today announced a new partnership and the launch of Market Intelligence-Infused Orchestration for procurement processes.

A new partnership

The new partnership brings real-time, actionable category and supplier intelligence directly into procurement workflows—starting from the earliest stages of intake—empowering enterprises to make more cost-effective, compliant sourcing decisions and proactively manage supply chain risk.

It also brings together Beroe’s trusted datasets and Tonkean’s intake and orchestration capabilities, enabling procurement teams to create and run internal processes that unify external market intelligence, organisational policies, and business context from the first moment of intent with orchestrated, AI-assisted workflows across the entire request lifecycle.

“Tonkean and Beroe’s new partnership changes the game for procurement teams, and further sets Tonkean apart from other intake solutions, which force requesters and procurement teams to look elsewhere for important data when they need it most,” said Tonkean co-founder and CEO Sagi Eliyahu. “Instead, we can now translate market intelligence into actionable guidance by deeply integrating it with workflows, empowering smarter, more compliant decision-making at every step.”

Vel Dhinagaravel, Founder and CEO at Beroe, said, “Our mission at Beroe is to empower procurement professionals to make informed business decisions using reliable data and insights. This integration with Tonkean’s process orchestration platform furthers our commitment to providing intelligence to our customers at the point of decision making and ensures that we fit seamlessly into their wider technology stack. Beroe’s unique approach fuses artificial intelligence and human ingenuity to ensure that market intelligence is curated and validated, and having such a reliable data foundation for various processes is key to improving business outcomes.”

New capabilities

The new combined capabilities improve a variety of key procurement processes, including:

• Supplier selection: When requesters complete purchase request intakes and are prompted to select a supplier, Tonkean surfaces intelligence from Beroe and overlays it onto the context of the request, the project it is related to, and the company’s policies, to help the requester make more informed decisions. This helps guide the requester toward compliant, cost-effective suppliers, improving procurement efficiency and adherence to policy.
• Aligning costs, budgets, and policies: When requesters complete purchase request intake for a commoditised good/service and are prompted to provide a budget for each line item, Tonkean surfaces cost benchmarks, including geography-specific benchmarks, from Beroe’s extensive datasets to help the requester properly file the request, give the procurement team a frame of reference for the sourcing process, and support policies that require purchases to be made within a given range of the cost benchmarks. 
• Requester support: When requesters need high-level information on existing suppliers, cost and pricing benchmarks, etc., they can ask questions in natural language on the Tonkean AI Front Door portal, through Microsoft Teams, Slack, or email, and even within intake workflows, to get timely answers.
• Supplier consolidation: Tonkean and Beroe can identify existing suppliers that meet company and project criteria and help procurement teams deflect unnecessary supplier onboarding. 
• RFP/RFI generation: When requesters and/or procurement need to provide inputs for an RFP or RFI, Tonkean can insert recommended questions for the category from Beroe and automatically create the RFx in the S2P system.

In practice, leveraging these capabilities in key internal processes empowers procurement teams to create all kinds of new business value for their organisations. 

Faster, smarter procurement decision-making

By providing real-time insights on supplier options and compliance requirements at the point of request, Tonkean ensures requesters can make smarter, policy-aligned choices without delay. The integration of Beroe’s decision intelligence into all key processes helps procurement teams identify cost-saving opportunities, assess supplier risks proactively, and optimise spend management with data-driven decisions. 

Plus, with contextualised risk insights, teams can anticipate and mitigate supply chain disruptions, enhancing resilience and stability in procurement operations.

“Great internal process experiences that serve to truly move the needle in terms of improved operational performance rely fundamentally on both quality data and the ability to orchestrate across people, teams, and systems,” said Eliyahu. “This partnership delivers to procurement professionals the ability to execute precisely those kinds of processes consistently and at scale.”

The future of procurement is here and it isn’t hanging about.

In a world with so much complexity, traditional operating models are quickly becoming displaced due to a lack of flexibility to cope with the demands of the modern world.

As procurement functions grapple with an ever-increasing list of issues such as the likes of cost pressures, market volatility and supply chain disruptions, businesses are desperate for ways to achieve sustainable, profitable growth in the market.

Understanding the urgency of the situation is dynamic trio Pierre Laprée, Chief Product Officer at SpendHQ, Kathryn Thompson, EMEA Sourcing and Procurement Market Offering Lead at Deloitte, and Michael van Keulen, Chief Procurement Officer at Coupa. In a joint conversation at DPW Amsterdam 2024, they reveal the power of working together to unleash 10X thinking quicker.

“Practitioners should start embracing this ecosystem mindset because alone, you cannot succeed,” reveals Laprée. “It’s important to be aware that you can’t know everything. It’s about learning how to surround yourself with the right voices, don’t stay on your own or you will never achieve 10X. Find the people who can help you move the needle. No one will do everything on their own, but when we come together we have a better chance of succeeding.”

The notion of 10X was apt as that was this year’s theme at DPW Amsterdam. The meaning of 10X is how AI and a moonshot mindset can transform a company from incremental to exponential impact. 10X showcases the necessity for organisations to think and act 10 times bigger than their current capacity.

SpendHQ is a leading best-in-class provider of enterprise spend intelligence and procurement performance management solutions. SpendHQ’s Strategic Procurement Platform empower procurement to generate and demonstrate better financial and non-financial outcomes. Laprée references the battle between integrated suites and best-of-breed solutions and stresses the importance of collaboration to reach the promised land. “You need proper foundational data, but then you also require more agile solutions that can help you overcome the problem of the day,” he says. “It is the power of all of us that makes the difference.”

Procurement transformation

As someone who is no stranger to driving procurement transformations, van Keulen is well aware of the ingredients needed to succeed in the digital-driven procurement world of today. Van Keulen’s company helps other organisations better manage direct and indirect spend, mitigate third-party risks and address supply chain volatility and resiliency. Through the compounding effect of AI, Coupa has combined its total spend management platform with its community-generated AI to introduce The Margin Multiplier effect. This is real-world AI informed by $6 trillion worth of spend, created over 15 years and across a community of 10 million suppliers.

“What that really means is how can you go from where you’re operating today to where you could and should be operating through the power of people, process and technology,” explains van Keulen.

“What is extremely critical is that you have the right data foundation, but it’s also important that we understand how AI is going to influence your end-to-end process. How is AI trained and what underlying data is used to train your AI? In our case, it’s based on real data, real companies, real suppliers who are all doing real business with each other. And that’s where the AI comes in. When you think about 10X, I think technology is a key enabler. I truly believe that you need to have reliable data to train AI and then it’s the power of all of us together, which we’ve always called the community element, to get the 10X multiplication or the margin multiplier that we can be in procurement.”

10X Vision

In order to make achieving 10X a reality, Laprée stresses in no uncertain terms that people are at the heart of that journey. According to Laprée, SpendHQ helps its clients build their data infrastructure to support acceleration and velocity. “Businesses move fast, the world moves fast and data moves even faster,” explains Laprée. “We help our client make sense of all of that. How does your spend evolve? How do your suppliers evolve? What are the areas of risk that you should be looking at? And that’s a constant monitoring process. Having a strong data foundation is an absolute prerequisite to achieving 10X speed because otherwise you will crumble under your own weight. That’s the key.”

Thompson, who has worked at consultancy giant Deloitte since 2012, believes that one of the biggest barriers in the way of achieving 10X is getting bogged down in the mechanics of reporting instead of value delivery. “Finance directors want you to put numbers to whatever you’ve done but you shouldn’t get too drawn into those conversations,” she says. “I think keeping a focus on value delivery rather than value reporting and measurements is where the magic happens. It can get a bit distracting so you need tools to help.”

According to van Keulen, the importance of trying new things and being proactive is essential. He draws comparisons to his own career and explains that part of the journey is to be comfortable with the uncomfortable.

“I fundamentally believe that if you want to drive transformation, then you have to be bold,” he reveals. “You will potentially make some mistakes along the way, but you have to get started. I’ve been fortunate enough in my career that I’ve had the ability to do procurement transformation a couple of times and support our customers in that journey. The ones that do it at a high level are the ones that are getting out there and talking to people out there in the community and want to share, be vulnerable and are okay with all of that. Those are the ones that are in our community, but also those are the ones that are the highest performers. But you have to get out there and you have to be bold to start with.”

GenAI Drive

Looking at the potential of GenAI in procurement, Thompson admits while the future is exciting the function still has some catching up to do as other sectors are further ahead in terms of GenAI adoption. As part of her role with Deloitte where Thompson also leads life science practice in the firm’s UK operations, her organisation leverages GenAI to accelerate clinical trials and research product development. 

“That speed to market and the difference it makes for timing on product launch is more than tenfold value return – it’s huge,” she explains. “Now the difference in procurement, a lot of the case studies we saw early on were like, summarise a contract or an RFP, but while you can save some time, it isn’t touching the sides. Of course, the CEO might say, ‘Show me all your GenAI use cases and this speed to market on R&D or product launches is more interesting than some of what we have done so far’. Now, we are beginning to see some exciting stuff like negotiations and the way that we can triangulate data for spend reporting. Indeed, there are insights we can get that we couldn’t get before. But ultimately, I think procurement is still relatively early on the journey.”

Digital future

Laprée adds that it is important users think carefully about the problem they wish to solve rather than shoehorning a GenAI solution into it. According to Laprée, SpendHQ has spent the past year evaluating what AI means to its clients and how it can help get to the desired outcomes quicker. “What we found is that our clients want faster refreshes where we can make our AI into a touchless entity that is essentially real time,” explains Laprée. “It’s about how we collect risk, financial and past sourcing information to generate insights that actually make sense. It’s about bringing this depth into the insights and stop forcing your user to look at pie charts and dashboards to get an answer. We have to make procurement more conversational and intentional.”

“But GenAI is just one tool in the toolbox. It’s one flavour of AI whereas natural language processing and machine learning have been here for longer than we can remember. Not all tools can solve your problems. When all you have is a hammer, everything looks like a nail. That’s pretty much the GenAI situation today. Understand that GenAI is not the be all and end all of artificial intelligence. Intentionality is key. What are you trying to do and what do you want to do? Define and think in terms of outcomes, not technology.”

Find out more about SpendHQ here.

Certa was born with a founding mission – simplify the way businesses work with third parties.

For CEO Jag Lamba, that mission hasn’t shifted since the company was created in 2015. Lamba came up with the idea for Certa after witnessing the many inefficiencies and complexities of the third party lifecycle at large organisations. He discovered that managing third party risk and compliance was always more challenging than it should be, so he was determined to do something about it.

Certa’s goal is to improve the way businesses manage third party relationships by simplifying workflows, automating processes, and delivering full visibility. Now, more than 100,000 users do business via Certa.

“What differentiates Certa is that it is a full spectrum of risk compliance and sustainability as it relates to third parties,” explains Lamba. “It’s comprehensive, but it can be deployed in a modular manner. Secondly, it’s very agile, so it’s easy to make changes with all the different regulations which is really important because companies need a very agile solution in today’s world. Lastly, it is intelligent. What I mean by that is beyond rules-based decision-making, we have generative AI embedded into the platform, and that makes lots of tasks much, much easier.”

A common joke in procurement is that the majority of practitioners fall into the space by accident. Not for Lamba. His journey into the industry was more of a conscious decision. “Previously, I was a consultant with McKinsey and I was working across clients. I noticed that one of their biggest pain points was that working across third parties was really challenging,” says Lamba. “As soon as I realised this, I understood that what’s challenging is all the risks and the compliance requirements that you need to cover when you work with third parties because you can’t work with just anyone. That’s what got me interested in this space as I wanted to solve this challenge.”

Lamba speaks to CPOstrategy at DPW Amsterdam 2024. This year’s conference focuses on the theme of 10X, the notion that companies should aim for a moonshot mindset instead of an incremental approach. “This is the first time that I actually see the 10X vision possible,” explains Lamba. “The main reason for this is because of the improvements in generative AI. For the first time, we can see this tectonic platform shift into what we’ve been calling the new productivity revolution. Companies in the procurement space and otherwise can now deploy AI Copilots and agents. Copilots can improve productivity by up to 50%. But AI agents can actually improve productivity 10X because AI agents are like coworkers. You can actually give them tasks and manage outcomes. That is your path to 10X.”

However, one of the biggest barriers to achieving 10X is getting buy-in. Change management is about delivering new ways of working in a considered and strategic manner while showcasing the benefits of giving up legacy systems and processes. “Change management is a difficult hurdle,” he says. “How do you sell that internally? How do you get adoption and how do you change your company based on all the new capability and automation that’s available to you? It’s the biggest problem procurement faces.”

Generative AI is changing the game in procurement. Through Certa AI, users can use natural language to create workflows, directly engage with data for sharp insights and supercharge supplier onboarding with automatic form-filling. For instance, instead of asking suppliers to answer hundreds of questions manually, businesses can use Certa AI to synthesise past responses and live data from the web to auto-complete questionnaires. Certa’s Risk AI also analyses and reasons via documents, extracting key information to enhance decision-making and streamline risk management.

“We were quite early adopters of generative AI,” explains Lamba. “We have generative AI live with 10 large enterprise clients which is rare. Now we are seeing incredible productivity benefits. Overall, generative AI is a tectonic-like technology platform shift that is ushering in this productivity revolution. Over five years, it’ll be as impactful as the communication revolution behind it, even potentially the industrial revolution before it. This is going to be massive. Generative AI will go through disillusionment phases, but can you imagine your life without the internet now? That’s how transformational this technology is and we’re only at the beginning.”

However, Lamba is well aware that generative AI adoption is not a straightforward and smooth process. According to him, there are four key considerations that should be thought about before leveraging generative AI into operations. “The reason why evaluating generative AI is tricky is because it’s relatively easy for software providers to create a sexy demo,” explains Lamba.

“You can actually do that in as little as six weeks, but to create a production-level system requires a lot more than a sexy demo. Now to get a product to completion, you need efficacy and reliability, ideally in the real world. As an evaluator, you want to ensure that the solution provider is giving you hard metrics on how efficacious and reliable the technology is.

“Secondly, you need a detailed audit trail because generative acts on your behalf so you want to understand all the steps that it did. Thirdly, you want some guardrails because the technology is still new and you need to follow company policies. And lastly, which most providers aren’t doing yet, is ongoing monitoring because the underlying models change and evolve over time. Traditional software has a defined set of inputs and outputs. With generative AI, the reverse is true, and you have an unlimited number of inputs and outputs. It’s a lot more challenging.”

With so much digital transformation and innovation at procurement’s fingertips today, Lamba is keen to stress how excited he is for the future ahead. “Working across companies, which is what procurement and supply chain does, is mainly an unstructured data problem because there’s no centralised database across companies,” he discusses. “Finally, we have a technology, generative AI, that is designed to work with unstructured data. As far as I am concerned, in the last 20 years this is the most exciting time to be in procurement. This function will be at the forefront of this revolution.”

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Most procurement executives agree that artificial intelligence and other advanced technologies will be transformational additions to their teams. Two-thirds see mastering artificial intelligence (AI) and generative AI (Gen AI) as the most critical issue they will face in the next few years, according to a recent survey by The Hackett Group.

They aren’t wrong. Our own forecasts suggest procurement process costs may fall by as much as 47%. We also predict that Gen AI will greatly enhance decision-making insights. However, this will only happen when the technology develops to a point where organisaitons can thoroughly integrate it into the supply chain. Nevertheless, those gains are only part of the potential.

The combination of AI, machine learning, advanced data analytics, and other digital advances will enable procurement to be much better informed about their supply base, giving teams the opportunity to play a much more proactive and strategic role in the business, and deliver on a range of other urgent priorities beyond cost to include supply innovation, sustainability, and third-party risk management.

Surveys, as well as feedback heard at The Hackett Group’s Gen AI Breakthrough conferences, confirms that organisations are in the exploratory stage with these new technologies. Procurement is lucky, with some great innovative tools including new capabilities already proven and commercially available. 

About a quarter of companies surveyed are piloting autonomous sourcing and/or negotiations, or contract lifecycle management. The same number again are further ahead with the implementation of supply analytics. 

Five best practices

If your company belongs to the uncertain majority, chances are good that you are still struggling to develop a strategy for integrating these new technologies into your ways of working. This can be overwhelming: with many systems to evaluate and priorities to rank, it’s not easy to know where to start. However, although every company is different, the experiences of the early adopters that are already piloting AI and other advanced technologies provide useful guidance to accelerate your own course for digital integration. 

Most of these companies belong to an elite group of top-quartile performers we call the Digital World Class^®. Already market leaders because of the skill with which they have innovated their operating models to embed the latest best practices, Digital World Class^® companies are undertaking this next stage of their journey in a very disciplined way. When we talk with them about what they have learned handling this transition, five lessons stand out: 

Don’t boil the ocean. 

Just because AI and Gen AI can be used in many contexts doesn’t mean you should try to do everything at once. Digital World Class procurement teams focus on specific use cases. They select suitable pilot partners. They find the data they need, make sure it’s digital and preferably structured, and back it up with whatever external sources are required. Where you should start will depend on your business, but in response to a multiple-choice question, procurement executives ranked supply market insights and analytics as the greatest opportunity (59%), followed by contract management (43%), and supply risk management (33%). 

Build the right team. 

Integrating these advanced tools demands much more than bolting on a new software package. To take full advantage, you will need an agile team of specific skillsets that understands both the business opportunity and technological development. Organised as a centre of expertise, this team will need to be savvy enough to build a bot, an analytical dashboard, or algorithm. Needless to say, they will need good change management skills. Without them, it’s unlikely they can adopt and ensure your pilot projects successfully.  

Own your data. 

Only use enterprise versions of Gen AI engines. Trying to save money by using the free version will put your data at major risk of leakage. Take care with your data. Amend contracts appropriately to ensure you remain secure and compliant.  

Keep it real, don’t hallucinate. 

Particularly with your first experiments, remember that Gen AI can confabulate details. Taking your bot at its word can lead to some serious mistakes: just ask the New York lawyer who was disciplined after submitting a court brief that cited imaginary cases. Context can also be a problem. (For example, if you direct your Gen AI to find a way to modify a pizza recipe to make sure the cheese doesn’t slide off, it might advise gluing it down!) Although organisations can mitigate such problems through using retrieval-augmented generation (RAG), an algorithm that gives your bot the virtual blinders it needs to focus on a specified data set, don’t assume that the machine is infallible.

Buy the right stuff. 

So far, much of the Gen AI technology development for procurement has focused on enhancing core source-to-pay tools, mainly category, sourcing, contracting, and purchasing operations tools. Using any of the modern CLM tools, for example, Gen AI can generate contract clauses, review and summarise contracts, flag non-compliant terms and associated risks, and guide on, or even negotiate, improved terms. Some of these technologies are advanced enough to make buying off the shelf better than building. In other areas, such as data or contract analytics, you’ll likely be better off building yourself, because you’ll want insights tailored to the specialties and greatest challenges facing your business. 

The road ahead

Even before Gen AI arrived on the scene, Digital World Class procurement organisations were already outperforming less tech-savvy colleagues. On average, they needed 32% fewer employees. This gave them the ability to redeploy significant resources into strategic procurement and helped position them to take the impressive leaps forward they are making today.

No one knows just how much further the Digital World Class organisations will get with this next generation of digital, data analytics and AI, but it’s clear that it will put more distance between the best and the rest – which is why you need to start following their lead now.  

Procurement software developer Beroe has announced a suite of new features and upgrades to its procurement intelligence platform, Beroe Live.ai. According to the company, the enhanced features provide procurement professionals with unprecedented insights and support. Their platform reportedly excels at combining AI with expert human insight.

The new features include enhancements to Beroe Live.ai’s Category Watch and Risk Watch modules. Also Beroe has made upgrades to Abi, the company’s AI assistant. Beroe is also launching ‘Category Digest’, a groundbreaking AI-generated category podcast.

Data driven insights with human expertise 

A large part of the way Beroe approaches designing its procurement solutions is driven by the understanding that AI tools should exist to support human decision making. 

“Businesses deserve smarter, more powerful solutions combining reliable, data-driven insights with human expertise,” said Prerna Dhawan, Chief Product Officer at Beroe. “At Beroe, we believe there’s a different way to make procurement decisions, and the new features and updates we are announcing today reinforce our commitment to empowering procurement professionals to make confident choices every day, helping them to be in the know, always.”

The new and upgraded features coming to Beroe Live.ai include:

Category Health Score: One Metric for a Holistic View

With the introduction of ‘Category Health Score’, a unified weighted indicator that provides a quick and comprehensive signal of category performance, Beroe is enabling faster response times in a dynamic market.

Category Digest: AI-Generated Category Podcast Series

Initially for a limited set of categories, these AI-generated monthly podcasts powered by Beroe’s expert-curated data will provide a new way to catch up on significant developments and market dynamics wherever you are.

Supplier Disruption Monitoring

This new capability enables customers to gain real-time insights on global and local events impacting their suppliers. The soluton categorises insights for relevance, mapping them visually to enhance supply chain resilience and continuity.

Abi, Beroe’s AI Assistant, with enhanced HITL capabilities 

In addition to Abi’s multilingual features and industry-leading integration with enterprise collaboration tools such as Microsoft Teams, Slack and Zoom, Beroe has further strengthened its HITL (Human in-the-loop) capabilities, ensuring accurate and nuanced responses tailored to customers’ needs.

With this release, Beroe is expanding its tools’ category coverage. It now provides insights on 2,300 direct and indirect categories at global and regional levels. This is an increase from 1,500 at the start of 2024. Coverage of commodity price forecasts and other macro indicators has also increased from 8,000 region-grade combinations to more than 12,000.

“We understand that many procurement professionals are dealing with cognitive overload managing large amounts of data across disparate tools. To help address this, our product roadmap is focused on simplification and contextualisation, delivering not just reliable data but intelligent recommendations,” Dhawan added. “We will continue to expand our category coverage and strengthen ecosystem partnerships with leading procurement technology and solution providers to ensure our customers can make smarter, faster, better decisions.”

Contract negotiation is a cornerstone of the procurement process. Training procurement professionals to negotiate for lower costs and better outcomes has always been a critical part of the sector’s talent pipeline. However, a rising demand for procurement professionals, growing amounts of work, the changing nature of the job, and an industry-wide skills shortage threaten to undermine the ability for procurement teams to effectively train the next generation of talent on vital skills like negotiation. 

Organisations have had some luck plugging the skills gap with virtual training. One of the key issues, however, is that good negotiation training relies on a nuanced back and forth between teacher and student. In traditional in-person training workshops, learners would often rely on the ability to ask the trainer to elaborate on specific points. Virtual training, while efficient, lacks this level of interactivity.

LavenirAI, an artificial intelligence-powered procurement training platform operator, claims that its new feature, Ask Harini, is a step towards solving this problem. 

Ask Harini — Personalised, interactive procurement training 

Representing “a major leap forward” for interactive, on-demand learning, AskHarini is a tool available within the LavenirAI Procurement negotiation training platform. It allows learners to engage with Harini, an intelligent, photorealistic avatar, powered by AI, to ask questions at any point during their e-learning content. Whether seeking further explanation on complex concepts or additional insights on negotiation strategies, users can rely on Harini to offer instant and considered responses that deepen their understanding and enhance the overall learning experience. 

Ask Harini supposedly eliminates this pitfall, bringing the same level of engagement found in physical classrooms to the digital learning environment. Learners can now ask Harini questions in real time, just as they would with a live trainer, closing the knowledge gap and giving each learner an experience closer to 1-to-1 training with a human. 

“Ask Harini is a game changer for digital learning, not just in Procurement but across the learning sector as a whole,” said Clive R Heal, CEO of LavenirAI. “It’s like having a virtual mentor alongside you, ready to help whenever you need it. We believe this feature will significantly enhance the learning experience for our users, empowering them to gain deeper insights and truly engage with the material.” 

Change is all around us.

Failure to adapt to the latest trends and leverage the latest technologies could leave you lagging behind the crowd. Equally, jumping too soon with a scattergun approach without real purpose or direction could be a costly mistake too. In truth, Chief Procurement Officers have never had quite so much on their plates. This is where an effective change management strategy can pay dividends.

Observing this all too well is Erin McFarlane, Vice President of Operations at Fairmarkit. A procurement software and systems leader, specialising in digital supply chain transformations using machine learning and AI, McFarlane has a passion for sourcing, contract negotiation and spend analytics and an infectious enthusiasm for her work. She helps procurement departments to embrace digital transformation and automation.

According to McFarlane, companies that leave risk behind and adopt generative AI solutions now have the opportunity to operate with radically improved insight and efficiency. In today’s fiercely competitive and ever-changing world, can procurement functions afford to be left behind? 

“I think if your organisation has already been on a modernisation journey, it’s possible for you to say you can hold back on GenAI,” explains McFarlane. “You might say the risk is too high and you’ve got your processes in line and you’re not suffering. But for the organisations that have not invested in procurement technology in the last decade in a significant way, I don’t think they can afford to go without because they are probably already suffering from a lack of agility.

“The only way that they’re going to be able to continue to control their operational expenses is to innovate and do that leapfrog. I think it depends on where you are. The people who have spent the last 10 years modernising are the ones who are even more excited and ready to adopt further. But I think anyone that is really far behind needs to take this opportunity to do that leapfrogging or it’s just going to get worse.”

In order to achieve a successful transformation journey, McFarlane stresses there are some steps Chief Procurement Officers need to implement first in order to help them down the right path of solving inefficiencies within their procurement functions.

“My first guidance to CPOs is firstly make sure that there is a lot of alignment with the CEO and CFO office to really understand the strategic objectives happening at the company and how procurement can either support or defeat those objectives by getting in the way or by being an enabling factor,” explains McFarlane. “Sometimes we get down into the nitty gritty details while forgetting the big picture “why”. That big picture why is what enables the process change. The technology in itself is amazing, but if you are automating a broken process, all you’re doing is making that process break faster. That doesn’t help anybody. Where modernisation has to come in is that you have to recognise that the existing way that you buy is fundamentally antiquated.”

However, despite the significant potential GenAI has, the line is not linear. With any new innovation or implementation, there will be teething problems. One of the biggest concerns is data security and how secure the information you input into chatbots really is.

“If you are careful, you can correctly contract and engage with one in a way that protects your data,” says McFarlane. “Where there’s a zero retention policy is where your data is not used to teach the model where your data is protected. But if you just go for the free and easy stuff by nature, everything you put into it teaches it, which means that everything you input has now become part of that public domain. And that’s really dangerous from a copyright perspective, from an IP perspective and from a data loss perspective. For the companies that I work with that has to be the number one concern because data privacy is so important.”

McFarlane emphasises that one of the biggest problems is hallucinations. AI hallucination is a phenomenon whereby a large language model (LLM) perceives patterns that are non-existent to humans by creating outputs that don’t make sense or aren’t accurate.

“It’s not just wrong, it’s very confidently wrong. It’s using such an enormous data lake that GenAI has the potential to say things that are wildly inaccurate,” she explains. “It can automate mistakes so they happen even faster. I think it’s important to consider the risk with any AI project and to start in a place with relatively low risk and automate the boring stuff first to make sure that you have monitors and guardrails to catch them.

“Don’t just set it, forget it and walk away because the potential does exist for some really unusual outcomes to happen, even some that aren’t necessarily wrong, but since we’re using existing data biases in the data it can perpetuate an algorithmic scale. If there is bias in the underlying data that you didn’t even realise was there, it can get even more thrown out of proportion. I believe it’s really important to understand where you use automation versus where you use what we call decision support. Automation is when the computer goes off and does its own thing. Whereas decision support is where you take all the information from GenAI, but the humans actually still make the final call and have a certain amount of oversight.”

With an eye on the future, McFarlane is full of optimism about the next few years in procurement. She explains that she is looking forward to the potential of more responsible sourcing as a result of an increased adoption of GenAI. “In procurement, we’ve always focused on risk aversion and cost savings,” she explains. “But I think there’s an opportunity for procurement and supply chain to lead, rather than just being the people who operate toward operational efficiency and avoiding risk, we can create competitive advantages for an organisation. Pharmaceutical companies during Covid were able to use an incredibly agile supply chain to deliver a vaccine in record time by changing the way in which they function. If they had been unable to pivot their supply chain into a completely different arm of manufacturing, they wouldn’t be where they are. 

“I think that stories like that are where innovation can come from. It is visionary procurement and supply chain leadership that can enable an organisation to make changes to produce products and services that are needed just in time. Whereas companies that are still operating the old way simply can’t change that fast. They can’t pivot their entire manufacturing operations from one product to a different product in six weeks. It’s just not something that you can do unless procurement is willing and able to make that kind of a pivot.”

Given the widespread consensus that the future is AI-driven, there’s one observation that never fails to amuse us. Time and again, people are still shocked by the idea that not all AI is created equal. 

AI is not new. Workflow automation has been around for decades. The technology dates back to when we first started tinkering with process flows at the turn of the century. The real change? AI has simply become accessible to the masses (thanks, ChatGPT!). More importantly, it’s found its voice, literally, through conversational models.

The current hype around AI barely scratches the surface of its potential, particularly when we compare generative AI to configured conversational AI. But this is just the tip of the iceberg. What many miss is that there are significant technical, procurement, and long-term delivery implications tied to the AI solutions you choose to invest in.

It seems like everyone is suddenly an AI “expert.” Practically overnight, the same technophobes who wouldn’t have touched a data model or architectural diagram with a ten-foot pole are now rebranding as digital innovators, hell-bent on revolutionising their industries with AI. It’s both fascinating and slightly ironic. In the case of Procurement and supply chain management professionals, the utilisation of AI capabilities is a real thing – advanced demand forecasting, optimising supplier selection and more recently, autonomously negotiating contracts, are all tangible examples.

Choosing the right path to AI  

But the real question is: where does your business start its AI journey? In our view, there are three primary paths to consider. 

First, we have AI extensions—enhancements to existing products, adding functionality without reinventing the wheel. Then there are AI solutions, typically targeted at specific industries or use cases. Finally, there are AI platforms, which act as an integration layer, connecting various workflows across your technical architecture. 

Each option has its pros and cons. Your choice will shape the costs of future innovation, the level of expertise your organisation will need, and, crucially, the longevity of your IT architecture, data security, and—most importantly—your organisational culture. 

With Gartner predicting at least 30% of GenAI projects will be abandoned after the proof-of-concept phase, organisations and more specifically, procurement and supply chain functions must recognise that AI is more than a tool. It’s the DNA of your business’s future.

AI everywhere, people-centricity nowhere

Businesses are mutating into organisms, industry convergence is everywhere, and corporate battlelines are being redrawn. However, very little emphasis has been given to human-centricity. Not in the workplace anyway. 

Procurement functions, for example, need to drive strategic value, manage both internal and external relationships, as well as sustainability. Yet, despite all this transformation, we’re still drowning in a sea of outdated procurement systems and rigid processes that treat people as cogs in a machine. There’s little thought given to how these tools affect the people using them. Procurement professionals need intuitive, user-friendly systems that let them focus on value creation rather than bureaucratic box-ticking

Whilst we have been busy teaching machines how to think, they’re teaching us to question everything. Cost-cutting, efficiency, data-governance, and the almighty bottom line. We are seeing a proliferation of new cultural norm data is no longer merely ‘collected’ or ‘feared’ — it’s now worshipped. 

Attitudes towards AI crystalise 

Data-cultures have become the norm. Cultures predicated on data are a collective mindset/practices within an organisation that define how data is handled, valued and leverage to drive decision making and innovation. 

 Are you on the right (Dovish): Do you align your company environment to Big Tech giants (Apple, Amazon, or IBM) who see data as an endless, extractive resource?

Or are you on the left (Hawkish): Do you lean into the push for data ethics (Salesforce), privacy (Motorola), and the emerging ethos of digital rights?

Gone are the days when AI was confined to optimising logistics or predicting consumer trends. Now, it’s a reflection of who we are—our biases, our ethics, and our societal hierarchies. 

Then again, that is the weird part: AI models carry the same prejudices we, as humans, can’t seem to shake. You’re not just buying a machine learning solution. In reality, you’re onboarding the assumptions and blind spots of an entire culture of developers, data scientists, and executives. And that is the crux of the problem today.

Our data shows that around 52% of software functionality in procurement and supply chain functions is never used. These are important statistics for commercial professionals looking to deploy AI and/or any software across the function. We cannot be the guardians of the bottom line if we cannot get our people to use the software we’re crying out for. 

AI success (or failure) is cultural, not technological 

If you don’t think about the cultural implications of the AI systems you’re integrating, you are profoundly at risk. Today, AI has a bit of a trust problem. Tomorrow, it will be embedding your future corporate values. And those values can make or break a company in this era where what you do with data can be as important as what you do with your product. For any sustainable competitive advantage, the birth of the inseparable triplet – Culture, data and AI is upon us, but the advantage will be with organisations that weigh them in that order. 

Remember, organisational culture is everyone’s and no one’s problem. In an age of AI-everywhere, without a robust, governed, and harmonised data-culture, people will become the problem and, honestly, AI won’t be the solution.

AI-powered spend management platform provider Globality has launched a suite of new tools to enhance the functionality of its offering. The upgrades reportedly add “game-changing Next-Gen AI-driven capabilities” to Globality’s platform.

AI-driven visibility from end-to-end 

Globality’s latest round of tools now deliver enhanced visibility across all organisational spend. This ranges from large, complex purchases to straightforward, unmanaged tail spend. It does this through enhanced features across key areas in the sourcing process:

• Next-Gen AI-Based Scoping: The platform uses Generative AI, along with Globality’s AI and proprietary data, to quickly identify end-user needs. It can then define the scope of a purchase more accurately than ever before.
• Workflow & Journey: Globality’s AI Agent, Glo, enables procurement to set oversight and approvals, and guides users through an optimal project journey that balances end-user efficiency and commercial outcomes.
• Line Items: Users can quickly specify items, descriptions, quantities, and units of measure for tail spend and request for quote (RFQ) events. According to Globality, this not only saves organisational time but also improves precision and ensures more comprehensive pricing capture. 

“We’ve introduced powerful, dynamic functionality to the platform, enabling the most tailored journeys for every project type,” said Matt Malden, Chief Product Officer, Globality. “These updates reinforce our commitment to a technology platform that delivers next-generation AI-driven capabilities while creating an intuitive experience for all users.”

What the customers want 

Globality says it has developed the latest round of upgrades in direct response to feedback from large scale enterprise customers. These include UK telecom operator, BT. BT has been using Globality’s AI platform to boost the effectiveness of its procurement processes for over a year now. The platform is reportedly used to manage more than £2.5 billion of project spend within the company. Globaility’s AI tools allow procurement teams to delegate activities like bid writing and drafting statements of work to stakeholders. The savings this creates are a key part of BT’s plan to realise substantial cost reductions through digitalization by 2025. 

Other organisations consulted by Globality when developing the latest enhancements included Fidelity Investments, Santander, T. Rowe Price, Tesco and UCB Pharma. These companies reportedly use the platform to drive more value from the tens of billions of dollars they spend each year, reducing costs by up to 20%, increasing operating efficiencies by 70% and improving speed to market by 90%.

“Procurement is the lowest hanging fruit across the enterprise to reduce costs, capture efficiencies, and improve business operations,” said Lior Delgo, Co-Founder and President, Globality. “Globality is the only sourcing platform that modern global enterprises can depend on to manage critical spend, leveraging AI to save hundreds of millions of dollars, accelerate decision-making, and unlock new opportunities for investment and growth.” 

The use of intelligent automation has steadily grown in recent years. At this point, it seems inevitable that machine learning will continue to become a bigger and bigger part of business.

Now a new kind of artificial intelligence has caught everyone’s imagination: Generative AI or “Gen AI,” a technology that can generate text, code, speech, and even images based on what the application has been trained to create.

For procurement, such a tool offers opportunities that previous AI tools did not. Unlike past automation tools, such as robotic process automation and predictive analytics, which generally demanded structured data, Gen AI can be useful in handling complex and ambiguous situations that the procurement function tends to have in abundance.

Based on our research, we expect that the way you spend your day as a procurement professional will soon be very different than how you worked before:

• You receive 15 responses to a request for information. Instead of spending days copying and pasting, reading, paraphrasing, and comparing the responses, your Microsoft Copilot presents a table summarising their important differences in seconds, cross-checks those figures against different data sources and automatically drafts your clarification emails, and sends an enquiry to your legal or quality colleagues. Finally, imagine training an AI tool to understand your organisation’s context so it can assess supplier proposals without any human preconceptions, and give you an independent score?

• Your new procurement cockpit will give you instant visibility into sourcing activities across your 17 operating companies, drawing on 30+ ERP, e-sourcing, and spend analysis systems, giving you an instant understanding of your activity across suppliers. Imagine training your Gen AI procurement colleague to keep an eye on your trusted financial stability data sources, market intelligence partners, key commodity prices and global news publications to proactively notify you about your firm’s own leverage and opportunities?

• Imagine saving 90% of the time you spend going back and forth with your legal colleagues because your tool has already learned to draft text in a style that the lawyers might recognise as their own. (This timesaver is not that far away: the leading contract lifecycle management tools can already deliver detailed contract reviews and analysis at high speed, extract metadata from a large quantity of scanned contracts, and provide an audit trail of the contract negotiations with external parties.)

Native platform applications. Gen AI is being powered by broad platforms serving a variety of needs at scale. Examples include OpenAI’s GPT-4, and ChatGPT, Anthropic’s Claude 3, and Meta’s Llama 3. Organisations can integrate and build Gen AI solutions leveraging these platforms by directly working with the provider or through their preferred cloud infrastructure provider such as AWS or Microsoft Azure.

Procurement suites and point solutions. Most procurement-specific technology vendors are also planning on integrating and embedding intelligent automation and Gen AI into their tools. But be on your guard when discussing these new features with a vendor: these capabilities will help all the vendor’s clients in a similar way thereby providing very little competitive differentiation, a fact that should be taken into consideration when evaluating these solutions.

Domain-specific solutions. These Gen AI solutions, trained on specific industry data and language (such as that in contracts or regulations), enable you to address domain-specific use cases with greater accuracy and relevance.

While all three forms of Gen AI will be useful to procurement, we believe domain-specific solutions are likely to have the biggest impact. Having a digital assistant on tap that understands all the nuances of your industry’s vocabulary, your company’s business strategy, and its operational realities, is likely to be very helpful to over-stretched procurement professionals.

Notice that we said assistant, not replacement. That’s because although a lot of the coverage of Gen AI has focused on its potential to replace people, we believe CPOs will find it much more beneficial to use the technology to increase the amount of spend their teams can influence, the risks they can mitigate, and the value they can add. As good as these systems are going to be, they will be better working in partnership with an experienced procurement specialist freeing up time to become a trusted advisor to the business.

This is not to say that the procurement function won’t be changing. Far from it. In the next few years, we expect to see major changes in how procurement specialists work and where they focus their time. 

Five next steps

For CPOs, succeeding in this transition will require a lot of preparation. Five steps in particular should help ensure that it proceeds relatively smoothly:

1. Bust the myths. There is a lot of hype out there about Gen AI that is either incomplete or inaccurate. Vendors are making enormous promises that they have yet to deliver on. At the same time, as the examples above suggest, Gen AI has potential to be a real game changer. You need to educate and inform your executive team and level-set their expectations.

• Identify your biggest opportunities to add value with Gen AI. Talk to experts who can guide you through heat maps of where AI would generate the most value for you. Rank your priorities by value and ease of implementation.

• Mind the gaps. Review your data quality and availability, skills, governance, and infrastructure to ascertain your readiness. Most of all, make sure you have the talent on your team to understand your data streams and processes. Procurement teams aren’t going to be replaced by Gen AI tools, but they will need to learn how to prompt them and incorporate them into their processes.

• Study use cases that apply to your particular situation. Examine real life examples of use cases that have been implemented and learn the critical success factors from the early adopters. 

• Start practicing now. Set your team to work on low-risk pilots using their new Gen AI tools as soon as you can, to give them experience and confidence, and to build momentum and enthusiasm for more change.

The bionic buyer

Far from being a technology that replaces procurement professionals, Gen AI will make you even more productive. As a machine learning solution, Gen AI will learn right alongside you, helping you manage your company’s spend with more intelligence than ever before, and sharing that knowledge with your entire enterprise and your partners.

Vicky Kavan is a Director of The Hackett Group‘s Sourcing and Procurement Executive Advisory team.

In our many conversations with procurement professionals and leaders across the sector, a consistent problem is the various ways in which procurement sometimes lags behind other parts of any given business. The upside to this is the innovative companies that spring up to solve these issues.

Arkestro was spawned due to the ongoing issue of how long it takes to collect and compare supplier quotes. As a predictive procurement orchestration solution, Arkestro sits in the quoting process between companies and their suppliers. It leverages behavioural science and game theory to create much faster procurement cycles and better cost outcomes at scale. It does this in a radically simple way, enabling procurement to use predictive AI to act first in the negotiation, or generate counter-offers based on data.

“By using predictive AI to be proactive, procurement is in the driver’s seat with the supplier from the get-go,” explains Edmund Zagorin, Arkestro’s Founder and Chief Strategy Officer. “It allows you to unlock areas of value that the more reactive procurement process can’t do.”

We caught up with Zagorin at DPW NYC in June to discuss the state of procurement and how AI relates to it, as well as the current roadblocks stopping procurement from being the best it can be. One of the main issues discussed across the event was the talent shortage.

Addressing the talent shortage

According to Zagorin, that challenge shortage isn’t going anywhere – not without a serious overhaul to make procurement look much more appealing, at least.

“There’s a talent shortage in a lot of back office roles, not just procurement,” he explains. “The one in supply chain, though, is expected to get worse. It’s most acute in developed countries where jobs in warehouses, tracking, and admin jobs come with low pay. They’re very stressful and don’t have great options for career advancement. This creates challenges with hiring and retaining talent.”

One of the many great things AI is doing for procurement is to make roles more attractive. AI is becoming an increasingly integral part of the future workforce and is creating new job opportunities for people. AI also allows people to focus on being more strategic in their jobs rather than pushing papers all day and other admin tasks that can be automated.

“I think we’re going to see AI orchestration that runs across multiple embedded platforms,” says Zagorin. “That has the potential to dramatically improve the quality of day-to-day procurement work. In the short term, this will help address the talent shortage by making it more appealing.”

AI as a strategy

Adopting these kinds of AI solutions across procurement is the biggest trend in the sector right now, according to Zagorin. AI as a procurement partner was discussed extensively at DPW NYC, but one of the takeaways from several speakers was that AI is not just a tool – it’s part of the strategy.

“There was a survey done recently about the biggest problems businesses are using AI and procurement to solve,” says Zagorin. “Number one for many companies is something called ‘inflation clawback’. During the pandemic, most suppliers raised their prices across categories, and they haven’t subsequently decreased those prices. Companies that have cost reduction programs know they need to be asking for reductions systematically and competitively. They need to be benchmarking themselves against their peers, and assessing whether they’re leaving money and value on the table.”

“The second problem is the talent shortage. Some businesses are being motivated to leverage AI to make the job more attractive to new recruits. But there are some jobs which are particularly difficult to hire for. As technology matures, AI is increasingly becoming a core skill that humans must learn how to use successfully. Failure to learn how to utilise the likes of generative AI correctly could prove costly as AI models continue to develop and companies adopt new processes at speed.

Solving decarbonisation

“The third biggest issue AI is helping to solve is decarbonisation. This is a big deal in Europe especially, with some of the world’s largest logistics companies having decarbonisation programs in place, and/or an internal carbon tax. “This carbon tax is implemented through procurement,” says Zagorin. “If you spend money on something that increases emissions, you pay for the cost of those emissions out of your budget. That money goes into a slush fund and gets redistributed to people who reduce carbon. So, this is affecting headcount plans, budgeting processes, and it’s creating real behaviour change.

“As that becomes the norm more and more in Europe, it’ll begin to cross the Atlantic and you’ll see US corporations begin to adopt that as well,” Zagorin continues. In order to do that, businesses need to be able to measure the carbon cost of a gallon of fuel per mile travelled for the mode of transport in a lane of logistics. And here, AI is able to step in once more.

“This is a data-intensive taste. So that’s something else where we’re seeing AI playing a role. It’s helping compute, track, and forecast the carbon cost of various logistics, footprints, networks of freight, and procurement activities.”

Texas-based energy industry software-as-a-service (SaaS) platform provider Enverus has announced the acquisition of BidOut, a Houston-based startup that uses generative artificial intelligence (AI) to automate elements of the request for anything (RFx) process. 

It’s the latest in a long line of procurement and supply chain organisations looking to integrate generative AI into the procurement process for its potential to automate significant portions of the procurement professional’s workflow. 

However, the announcement comes at a fraught time for the sector as hype gives way to trepidation. AI chip-maker NVIDIA’s share price continues to slide, and investors in Google, Microsoft, and OpenAI have begun to question the viability of sharply rising Cap-Ex over the coming years with no profitable practical applications in sight. Nevertheless, AI spending still continues to be considerable.

What is BidOut and what does it do? 

Enverus has described BidOut as “the industry’s premier AI-powered procurement platform”. The company’s press team has also called the acquisition marked “a significant milestone” for Envervus’ business automation offerings. 

BigOut’s generative AI-powered offerings help procurement teams to more easily and quickly source bids from multiple suppliers. Traditionally a labour-intensive process, Enverus claims that, by using AI, BidOut’s solutions dramatically accelerate the request process. BidOut was founded by 2020 and is backed by capital investment from Ascent Energy Ventures & Leazar Capital among others. Since launching, BidOut has rapidly expanded its customer base, leading to their recent acquisition. 

What is RFx? 

In procurement, RFx means “Request for anything”. The exact nature of what’s being requested can vary dramatically throughout the lifecycle of a procurement project. 

An RFx refers to a formal and structured process executed in a document form. It’s used by organisations and businesses to acquire information, proposals, quotes, and bids from various potential suppliers. It could refer to a request for proposal (RFP), request for quotation (RFQ), request for information (RFI), or something else.  

Procurement SaaS synergy 

Enverus pointed to the synergy between BidOut’s RFx platform and Enverus’ existing Source-to-Pay solution. It argued that the purchase presents “an exciting opportunity” for the energy industry. By bringing together BidOut’s buying capabilities with Enverus’ solutions, users can now manage their entire procurement process in a single Source-to-Pay platform, they say. The integrated offering will also reputedly enhance decision-making, save costs and time. Enverus added it will also improve compliance and supplier management, ultimately making the procurement process better and enhancing supplier relationships.

“The acquisition of BidOut marks a transformative milestone in accelerating Enverus’ vision to become the foremost end-to-end provider of business automation solutions for the energy industry,” stated Manuj Nikhanj, CEO of Enverus. “Currently, Enverus partners with more than 450 buyers and 40,000 suppliers, facilitating more than $250 billion annually in digital invoicing for our customers. By integrating BidOut’s cutting-edge technology into our expansive network, we will immediately enhance value for our clients with our complete Source-to-Pay solution. This strategic acquisition underscores Enverus’ commitment to driving efficiency and technological advancements across the energy sector.

“As Enverus integrates BidOut’s products and services into our existing suite, we anticipate customers across all the verticals we serve will truly benefit. This investment will not only accelerate product development and innovation, but these enhanced offerings will help define some of our customers’ futures,” said Jeff White, general manager of Business Automation at Enverus. White will lead the integration of BidOut into Enverus’ platform.

Generative artificial intelligence (AI) is unquestionably the technology most loudly and obviously impacting the procurement sector (indeed, many sectors) in 2024. 

AI powered by large language models (LLMs) has been touted by McKinsey as the secret to new forms of value. It will supposedly empower content generation, enabled synthesis, augmented engagement, and accelerated software planning. Of course, many leaders in the procurement sector (and out of it) are skeptical. They argue that generative AI might be “a great toy” that’s “good to play with”. However, they also say their day-to-day work remains unchanged. 

Is generative AI the once-in-a-lifetime technological disruption people selling it claim it to be? Or, is it a flash in the pan headed the way of dinosaurs, crypto scams, and the metaverse? 

The peak of the hyper cycle 

Unintuitively, the closer you get to the peak of a hype cycle, the harder it is to see where you’re going to land. The more generative AI dominates the conversation, the more money gets spent on it. The waters get muddier. It gets harder to see if we’re headed for a bubble bursting or a gentle glide into sustainability. 

Gartner, however, remains optimistic. ”GenAI can already enhance many different workflows in procurement and 73% of procurement leaders at the start of the year expected to adopt the technology by the end 2024,” says Gartner’s Kaitlynn Sommers, “this  level of adoption, along with promising use cases, such as contract management, means GenAI will rapidly move through the Hype Cycle and reach the Plateau of Productivity at a faster rate than is typical for most emerging technologies in procurement.”

In the last 12 months, use cases for generative AI have rapidly expanded, as has the availability of generative AI tools. More capabilities are being added by vendors across the sourcing and procurement landscape every month, according to Gartner. 

Early examples of procurement and sourcing applications include contract management, sourcing, and supplier management. Down the road, Gartner also expects use cases to include supporting supplier performance management, P2P and analytics.

Third party LLMs support adoption

Of course, a major barrier to generative AI adoption is a potentially high cost of entry. However, as time goes on, procurement technology vendors are integrating third-party LLMs into their offerings. These can provide more affordable access to GenAI capabilities in line with digital process support. Third party LLMs can adapt to provide recommendations and support based on organisations’ data and an individual’s procurement role, such as category manager or buyer.

“The window for building competitive advantage through early adoption of GenAI in procurement is narrowing,” said Sommers. “Despite this, procurement technology leaders should remain aware of the obstacles to successful implementations, notably in the areas of data quality and integration of GenAI with their current systems.”

Zip has unveiled a powerful suite of new and enhanced AI capabilities that allow companies to gain control of their spending by streamlining procurement.

The AI-powered spend orchestration platform has built on its existing capabilities and now offers tools such as Zip AI assistant, AI document extraction and AI intake automation.

Simplifying procurement

The purchasing process can often be slow, complex, and riddled with inefficiencies, involving countless steps, extensive paperwork, and numerous approvals and security reviews. Zip’s AI-powered platform streamlines the entire procurement lifecycle, from initial request to final payment, thereby saving businesses valuable time and money, while enhancing spend visibility, risk management, and compliance.

Hundreds of industry leaders including Sephora, Discover, and Reddit as well as leading AI companies like OpenAI use Zip to increase operational efficiency, generate hard savings, and reduce risk.

The latest AI features bring even more advanced and impactful capabilities to Zip:

• AI assistant: Zip’s AI assistant guides employees through the purchasing process to reduce the time and effort required to navigate complex company spending policies. For example, if an employee wants to buy an Airtable software subscription for their team, they can send a message to Zip’s AI assistant as if messaging a coworker, and Zip AI will automatically start the purchase request, guiding them through what is needed to complete the request. 
• AI document extraction: AI document extraction parses data from order forms, contracts and other documents to create a comprehensive, single source of truth. With AI document extraction, users can scan documents such as MSAs, DPAs, NDAs, SOWs, Amendments, and more in seconds. This puts valuable information to work, allowing users to autmate more tasks.  
• AI intake automation: AI intake automation pre-fills purchase requests with data from order forms, eliminating manual data entry and saving time. Employees simply need to upload the order form they receive from their vendor to have key purchase and supplier information — such as price, item quantity, and billing frequency – automatically included in their purchase request, saving them valuable time and reducing the likelihood of errors. 

Better customer experience

“Zip has become an indispensable tool for OpenAI’s procurement process,” said Hugh Drinkwater, OpenAI’s Head of Procurement. “We are thrilled Zip has integrated OpenAI’s technology to power their Zip AI suite to help us further reduce time spent on manual tasks, create a better buying experience and improve the productivity of our teams across the organisation.”

With Zip’s suite of AI solutions, companies can eliminate thousands of employee hours and dramatically reduce the need for procurement, legal, security, finance, and IT teams to spend time on error-prone data entry and time-consuming vendor contract reviews. For example, Miro uses Zip AI to save time with the legal contract review process; Coinbase uses it to streamline millions of dollars of invoices per year; UCI Health is implementing it to rapidly scale contract conversions during a merger, ensuring inclusion of key stakeholders and continuity of patient care — allowing doctors and nurses to focus on providing life-saving medical treatment without administrative delays, or disruptions to services required.

Today, Zip powers global payments in over 140 countries and has helped customers save almost $4.4 billion in less than four years since the platform launched.

The potential for generative artificial intelligence (AI) to unlock new efficiencies and capabilities for procurement teams is a matter of widespread enthusiasm in the industry. However, challenges like poor data quality and inadequate governance may be holding back adoption. 

A new study by Ivalua found that the majority of the UK’s businesses are exploring generative AI’s potential to transform procurement and supplier management. Just under a quarter (24%) of businesses have deployed Generative AI tools in the last 12 months, and another 55% are either in the process of implementing or are considering implementing generative AI over the coming year. Just 19% of companies surveyed said they had no plans to adopt. 

The study also found that organisations that have adopted generative AI tools saw a 44% reduction in manual processes across the procurement and supply chain function. Organisations are most commonly applying the technology for task automation (69%), internet research (67%), document analysis (59%), and content creation (48%).

“Generative AI represents huge productivity gains and resource unlock for procurement,” Vishal Patel, VP of Product at Ivalua, commented. “But to succeed, careful change management and education are required to show employees Generative AI will enhance their role rather than replace it. With employees on board, businesses can focus on harnessing Generative AI to eliminate routine and time-consuming tasks while focusing on higher-value activities. But another key barrier remains – addressing a lack of progress on digitisation.”

Digital transformation hurdles slow Generative AI adoption 

Despite widespread enthusiasm for generative AI, adoption in the procurement sector faces some significant hurdles. Specifically, digital transformation has progressed slower in procurement than in other fields. This, according to Ivalua’s research, is hampering generative AI adoption in procurement. 

On average, organisations say they’ve digitalised 48% of procurement processes, compared to 45% in 2019. The report holds up the following as key reasons behind this lack of digital transformation initiative that’s impacting generative AI adoption.  

• Poor data quality: 22% of procurement leaders cited poor data quality as a challenge to adopting Gen AI in the procurement and supply chain function.
• Lower technical skills among teams: More than a quarter (28%) of procurement leaders say user resistance is a top challenge to adopting Gen AI, which suggests a lack of digital skills or technical confidence will hinder progress.
• Lack of guardrails and processes: One-third (33%) of procurement leaders are concerned their team is using Gen AI tools without their knowledge, which is why nearly seven-in-ten (68%) agree they need to put more guardrails in place to ensure the accuracy of Gen AI outputs.

“Businesses need a solid data foundation for procurement and supply chain teams to effectively harness AI to improve efficiency and contribute to effective and timely decision making. But the lack of progress in digitisation and common data challenges suggest there is a significant gap to be bridged before Gen AI can deliver more strategic value,” added Patel. “Most procurement leaders agree that if their organisation doesn’t embrace Gen AI in procurement, they will lose out on cost savings and broader value creation opportunities. So, businesses must act now to digitalise and close the technology and data gaps in their procurement function. If not, they will struggle to measure up against AI-powered competitors, potentially losing customers and market share.” 

Generative artificial intelligence (AI) exploded into the public consciousness in early 2023. Since then, the technology has attracted vast amounts of media attention, controversy and, crucially, investment. Now, tech companies are struggling to bridge the gap between hype and reality. Between the billions upon billions of dollars spent to bring AI to market and the reality that it may not be the game-changer it’s being sold as. Increasingly, it appears as though it might be a very expensive, complicated, ethically flawed, and environmentally disastrous solution in desperate search of a problem.

“AI chatbots and image generators are making headlines and fortunes, but a year and a half into their revolution, it remains tough to say exactly why we should all start using them,” observed Scott Rosenberg, managing editor of technology at Axios, in April. 

Nevertheless, Generative AI is seeing huge investment across virtually all sectors. In the procurement market, the technology is on track for substantial growth. Market projections estimate the value of AI in procurement to soar to more than $2.2 billion by 2032. 

Can we use AI for procurement?  

In January, Gartner found that 43% of procurement leaders were planning to implement the technology within the next 12 months. It’s worth noting that this investment in generative AI lags slightly behind the supply chain function in general. However, it’s still close to half of alll CPOs planning to buy an AI tool. Maybe a slower approach for the industry as a whole wouldn’t be such a bad thing. 

It’s likely that AI will have applications that are worth the price of admission. One day. 

Its problems will be resolved in time. They have to be; the world’s biggest tech companies have spent too much money for it not to work. Nevertheless, using “AI” as a magic password to unlock unlimited portions of the budget feels like asking for trouble. 

As Mehul Nagrani, managing director for North America at InMoment, notes in a recent op-ed, “the technology of the moment is AI and anything remotely associated with it. Large language models (LLMs): They are AI. Machine learning (ML): That’s AI. That project you’re told there’s no funding for every year — call it AI and try again.” Nagrani warns that “Billions of dollars will be wasted on AI over the next decade”. Applying AI to any process, including procurement, without more than the general notion that it will magically create efficiencies and unlock new capabilities carries significant risk. 

Tom Whittaker, director at independent UK law firm Burges Salmon, warns that “Use of AI in procurement requires clear purpose. Purpose drives the design, development and deployment of an AI system, how it will be incorporated into existing systems and processes, and how those responsible for the AI system measure performance and legal compliance.” 

Without clear intention and thoughtful execution, AI risks becoming a multi-million pound albatross around a procurement department’s neck. 

The problem with AI chatbots and other “low hanging fruit” 

According to GEP, AI represents a broad array of “low hanging” fruit for the procurement sector. These low hanging druit include “automating invoice processing, optimising spend with AI and augmenting capabilities through AI chatbots.” Companies looking to drive quick value from AI can supposedly exploit these options to save money and easily increase efficiencies. 

But is that true? 

Let’s talk about chatbots. The technology has struggled to perform as a replacement for human customer service reps.

In the UK, a disgruntled DPD customer—after a generative AI chatbot failed to answer his query—was able to make the courier company’s chatbot use the F-word and compose a poem about how bad DPD was. 

In the US, owners of a car dealership were horrified when their AI chatbot started selling cars for $1.

After Chris Bakke, who perpetrated the exploit, received over 20 million views on his post, the car company announced that it would not be honouring the deal made by the chatbot. It argued that, because the chatbot wasn’t an official representative of their dealership, it didn’t have the authority to offer discounts. 

Evangelists for the rapid mass deployment of AI to the procurement sector seem all too ready to hand over vital processes like contract negotiation to AI that can, without much difficulty it seems, be convinced to sell items worth tens of thousands of dollars for roughly the cost of a chocolate bar.

If 2023 was the year of Generative AI hype, 2024 (and probably 2025, 2026 and maybe 2027, if we’re being honest) will be the year(s) where we have to figure out if this shiny, incredibly expensive (and morally dubious) new technology actually has real world applications that are worth the price of admission. 

Where procurement is concerned, given the mixture of factors creating new and interesting pain points for the sector, the benefits of generative AI can’t arrive soon enough. These factors range from the skills shortage to an overall strategic shift in the nature of sourcing and ongoing political (and economic) tensions, all of which have the potential to create profound pain points for industry leaders.

The risks of generative AI investment are not to be taken lightly, despite the allure of greater efficiency and lower costs. Specifically, risks range from AI “hallucinations” and unreliable unreliable outputs, to issues of IP ownership, inherent bias, and cybersecurity threats. However, the benefits are, some would argue, well worth the risk. This is especially true if the nature of generative AI deployment is well suited to the task at hand. 

Here are three levels to which Generative AI can be used throughout the procurement process: 

 1. Shallow deployment 

This is probably the least intrusive and easiest to execute in terms of Generative AI deployments. A shallow deployment might simply provide a superficial gateway to ChatGPT or other external GenAI tools. 

Results mirror those obtained by directly interfacing with ChatGPT outside of the procurement application. Solutions could be used for rephrasing communications, generating early-phase ideas, and other simple, language-related tasks. 

2. Contextualised and optimised deployment

The next level optimises the large language model underpinning a generative AI deployment. It does this by training it using specific data relevant to the procurement function or company as a whole. 

Essentially, a contextualised Generative AI deployment involves furnishing the GenAI model with information derived from data within the solution. This can include sources of information like raw sales data and compliance documents. The solution employs prompt engineering to enhance output quality. User prompts undergo repackaging or reformatting before being forwarded to ChatGPT or another external GenAI tool. A single user request may trigger multiple GenAI prompts managed concurrently. 

3. Tailored deployments

Lastly, a much more in depth deployment involves a solution that utilises its own LLM (a pre-trained language model that has been further refined) to enhance outputs and dramatically reduce the risk of hallucinations. Using AI in this way can also allow for a hybrid approach, in which the solution employs either the internal LLM or an external one depending on the specific use case. 

Overall, tailored generative AI solutions offer a range of benefits, including improved performance, reduced risks, increased efficiency, enhanced contextual understanding, and greater flexibility, making them valuable tools.

The procurement landscape is undergoing a period of radical change. Pressure is growing for procurement teams to operate more efficiently and strategically. However, this trend is also growing in tandem with the complexity of procurement teams’ workloads. At the same time, the severity and variety of pain points faced by procurement functions have never been more disruptive. 

At the heart of this sector-wide transformation is technology. This trend is reflected in a recent report by Deloitte. Researchers note that the rapid advancement of technologies like automation, AI, and machine learning is remaking business supply chains. Their implementation is “poised to transform how the procurement function delivers value.” For many organisations, “the application of these disruptive technologies to procurement is already fundamentally altering the impact of this function.” 

One pivotal way that procurement is being altered by the changing technology landscape relates to the emergence of “machine customers.” 

What are machine customers? 

The concept of machine customers has been around for several years. Now, however, the technology is hitting an inflection point where its impact on the procurement sector has become undeniable. 

Machine customers are nonhuman economic actors capable of selling or purchasing goods or services autonomously. Examples of machine customers are varied. They can include IoT devices capable of placing independent orders, intelligent replenishment algorithms maintaining product availability, and automated assistants suggesting new deals to consumers. 

Machines can conduct procurement functions from both sides of the table, and the increasingly capable automation of sourcing and procurement could have a dramatic impact on the procurement sector. 

Some industry experts argue that machine customers could account for trillions of dollars in revenue by 2030. Automating the process of buying and selling could completely change the nature of the procurement process. CEOs believe that by the end of the decade machine customers will account for 20% of their companies’ revenues. 

The risks and rewards of machine customers 

The study projects that, by 2026, more than 15 billion connected products will have the potential to behave as customers. These machine customers will be able to buy and sell goods and services autonomously.

These machine customers would, theoretically, have significant advantages over a human. Machine customers are unaffected by the cultural, emotional and sensory triggers that are used to manipulate humans into buying one product over another. Of course, cyber attacks that could influence the behavioural parameters of a machine customer could result in far greater misappropriation of spend. 

Machine customers are also supposedly more efficient and methodical, with the ability to weigh up much larger sets of data to make more informed decisions in real time. The obvious criticism of this is that decision-making AI is limited by the scope of its programming and directives. The ethical concerns that could arise over the procurement practices taken by an AI told to prioritise low costs without sufficient guardrails are obvious. Machine customers will need to be increasingly regulated the more autonomy and agency they are given.

In short, machine customers are undeniably on track to have a meaningful impact on the procurement process. However, while automating sourcing in this way carries obvious advantages, widespread implementation of machine customers also creates new threats to the integrity of the supply chain.

Last year was undeniably the year of Generative AI (hype). According to Muhammad Alam, President and Chief Product Officer of SAP’s Intelligent Spend and Business Network, “generative AI was like a bolt of lightning that compelled every business and technology leader to sit up and take notice.” 

Now the first flurry of investment and breathless hype seems to be settling down. This leaves organisations interested in the potential applications of generative AI to try and figure out what that might actually look like.

AI is only as good as its data

Alam notes that those looking to adopt will “see firsthand that AI is only as effective as the quality and availability of data.” 

One class of organisation with access to vast amounts of data is government and other public sector entities. This class of organisation also cursed with a host of problems ranging from inefficient organisation to compliance and shrinking budgets.

As researchers at Deloitte noted in a recent report, “Government procurement professionals need help.” According to experts, generative AI could hold the solution to these problems.

“If government is to achieve the ambitious aims that the public expects, procurement professionals need tools to process large volumes of data with precision and with attention to the unique circumstances of every contracting action,” the report adds. 

Public procurement under strain

Procurement is currenting caught in a rising tide of complexity. Over the past 10 years, government spending has grown around 4.5% each year in the US. Over the same period, the total number of contracting actions has increased by more than 22% each year.

Public procurement is drowning under layers of complexity which are growing faster than the public sector procurement workforce.

At the same time, workforce headcounts are being stymied by budgetary concerns and an industry wide talent shortage. This is being exacerbated by the fact the private sector has and always will pay better. Therefore, the amount of work being done by individual public sector procurement staff is rising.  

In 2022, for every Federal contracting officer, an average of 2,000 contracting actions had to be executed per year. Comparing that number to the 300 actions per year in 2013 reveals the scope of the problem. If government procurement departments are going to avoid buckling under this growing strain, technology in the form of automation, advanced analytics, and other potential generative AI applications could have a role to play. 

Generative AI still has optical (and ethical) problems

Generative AI is a somewhat nebulous umbrella term. It is often conflated with its most public-facing examples: Chat-GPT and image generators like Midjourney. This is why there appears to be a disonnect between what generative AI promises and what it delivers.

These models are less effective than humans at doing a lot of things like making art, generating movie scripts, and accurately retrieving or summarising information from the internet, etc. In addition to untrustworthy results and “hallucinations”, large language model AIs and imager generators also have significant ethical issues baked in. These stem from the uncredited work by writers and artists used to train these models.  

Applications for a generative Ai layer in public procurement

However, this doesn’t mean that generative AI is a useless or irredeemably immoral technology. Under the right regulatory constraints and in the correct context, Generative AI can create a vital unifying layer between several other pieces of technology. (Obviously more AI regulation is something to which tech industry people seem more reflexively averse than ipecac).

However, generative AI shows promise as an intermediary layers between automation tools, big data analytics, and e-procurement platforms. Deployed correctly, it could alleviate the growing complexity that plagues public sector procurement. 

Deloitte’s researchers note, similarly, that “the emergence of gen AI has put a missing puzzle piece on the table that can allow several different types of tools to fall into place. Because gen AI works differently than previous generations of AI, it has different strengths and weaknesses. While gen AI can do things that traditional machine learning (ML) cannot, such as creating new text or images, it can occasionally struggle with accuracy in ways that traditional ML does not. Similarly, all forms of AI can exceed a human’s ability to handle large volumes of data, but humans naturally excel at tasks that strain AI, such as highly variable or social tasks.” 

By contrast, tasks like documenting and reporting are hugely time consuming.

“From using gen AI to generate documents and reports to having ML produce demand forecasts, AI can help reduce the time needed to create and process procurement request documents such as market research reports, statements of work, and purchase requests,” notes the report.