Organisations that have integrated automation and generative AI into their procurement practices have already begun to reap the rewards, making clear cost savings, generating improved insights, and pulling ahead of competitors. With the emergence of agentic AI, we are now entering a new phase where technology goes beyond automation – it learns, adapts, and collaborates with human teams to drive smarter decision making and execution.
But, as with any technology, deployment is a process and success is not guaranteed. Procurement teams who want to reap the benefits of agentic AI must first build a robust cultural and technology foundation. Without this, even the most sophisticated AI tools are likely to under-deliver or fail outright. But where do teams start?
Building buy-in across the workforce
With agentic AI, procurement leaders must ensure they win the hearts and minds of employees to limit friction. Starting at the top will set a tone across the business. As leaders, the C-Suite must champion AI initiatives – demonstrating commitment and communicating the importance of AI to the rest of the enterprise. If employees believe that AI is simply an ‘IT experiment’ or a move solely designed to drive cost savings, the likelihood of success is far lower.
AI agents can be presented as valuable assets that will work alongside employees, reduce toil, learn from data to make decisions, execute tasks autonomously and even proactively highlight areas to focus on. But whether the team is made up of humans or a mix of employees and AI agents, it’s vital that everyone’s roles and responsibilities are clear.
To allay concerns around job displacements, organisations must be able to reassure employees that AI will create opportunities. With more time saved on menial tasks, procurement teams can spend more time adding value, building better relationships with the business and with suppliers
This has never been truer than with agentic AI, where the human role is indispensable. While AI agents can follow set workflows and eliminate manual effort, humans need to be there to give oversight of data-based decision making and offer critical judgments AI simply can’t provide.
Strengthening the digital foundations
While users need to be onboarded early on, there must also be a clear vision for how and where AI agents will deliver value. Often, these are the repetitive or data-heavy processes, like purchase order creation, invoice matching, contract compliance checks, supplier onboarding or autonomous sourcing, negotiations, etc. Having clear process maps will help procurement teams spot opportunities and uncover quick wins.
Then, teams must review their existing procurement technology and the organisation’s ability to access insights. AI needs clean, accurate, and available data to function properly. Collaborating closely with IT, procurement teams must ask themselves: is our data truly AI ready? Without accurate data, the value of agentic AI plummets rapidly.
A strong AI strategy is built on a strong data strategy.
Considering compliance and risk management
Inaccurate data isn’t the only pitfall to consider. Procurement teams need to identify potential compliance issues and ensure suppliers meet contractual obligations. For large organisations with suppliers across the globe, this means having to adhere to local regulations across a huge number of regions, meaning a one-size-fits-all approach to compliance is impossible.
Procurement leaders must be clear of company policies and remain up to date on national data privacy rules before deploying agentic AI to avoid costly financial and reputational errors. Organisations must then continuously scrutinise AI outputs, working to understand how AI agents arrived at decisions, ensure that the data is correct, and that it is offering valuable insights. With the right guardrails and transparency in place, agentic AI will be able to reduce the compliance burden and help with risks once deployed.
The road map to AI Agents
Once the initial foundations have been laid, procurement teams can begin their agentic AI journey. Initially, the technology must be introduced in a controlled and targeted way. Deploying an AI agent to initially automate a specific process is a great place to start. By tracking key metrics like time saved and error reduction, stakeholders will have clear evidence to value and the potential broader implications of AI across the business process.
Once there is evidence of success, procurement teams can begin to scale up and gradually integrate AI agents into more complex tasks like autonomous supplier onboarding or legal negotiations agent. Ultimately, for agentic AI success, organisations need a strong, central platform that will act as a single source of truth that orchestrates data and processes across Source-to-Pay. This will ensure data consistency, cross-functional visibility, and a centralised enforcement policy. Without this core platform, process and technology siloes will emerge at scale.For many procurement leaders, the goal is a seamless ecosystem where AI agents can communicate with the core procurement platform, data repositories, and company policies. With the centralised platform, cross-functional insights, like linking procurement data with financial planning, are possible. This framework will empower smart, more strategic decision-making across the organisation.
Solid systems, smarter agents
For CPOs, the value of agentic AI is clear – but success hinges on more than just simply deploying the latest technology. Organisations need to ensure their teams are ready for change, that there is a strong data foundation to build on, and that the right guardrails are in place before deployment even begins.
By addressing cultural concerns earlier and establishing processes to ensure that data is high-quality and compliant, CPOs can lead teams into a smooth and successful transition to using agentic AI. The potential is enormous, but rushing to deploy AI agents won’t guarantee procurement teams will reap the benefits – thoughtful, strategic implementation will.
By Vishal Patel, Senior Vice President of Product at Ivalua