Did you miss the recent webinar “Agents of Change: How Agentic AI Is Rewriting the Source-to-Pay Playbook,” featuring Andrew Bartolini, founder and chief research officer for Ardent Partners, and Paul Blake, senior director, engagement for GEP?
The webcast provided a practical look at how autonomous agents are transforming source-to-pay operations, including how AI can enhance sourcing, contracting, compliance and payment with greater context, initiative and adaptability.
Today is Part One of a two-part article series that brings forth the key points from the webcast, with a link to the event.
Agents of Change: How Agentic AI is Rewriting the Future of Procurement
The business world is on the brink of another major transformation, and this time, it’s not about a revolution that has already taken place, but one that is steadily unfolding. The rise of agentic AI marks the beginning of a new chapter in procurement, supply chain, and ESG operations. This technology has the potential to fundamentally reshape how organizations operate — but as with any innovation of this scale, progress must be deliberate, responsible, and human-centered.
At GEP, leaders see this as the moment where the first few chapters of a new playbook are being written. Agentic AI systems are not simply smarter automation tools; they represent a generation of intelligent agents that are autonomous, adaptable, and capable of handling complex tasks once dependent on human judgment. These agents are ready, in principle, to take on meaningful roles within enterprise operations, but that does not mean businesses should rush to deploy them at scale. Safe, responsible adoption requires careful testing, real-world validation, and operational readiness. Governance and oversight must evolve in tandem with technology — because, as history has shown, it’s rarely the tool that slows progress, but the transition itself.
The challenge, then, is not just technical. It’s about change management. Roles, processes, and expectations must evolve in parallel with the technology’s maturation. Any vendor suggesting that agentic AI is “plug and play” is overselling the reality. What makes this moment unique is not that AI has suddenly appeared, but that we are crossing an inflection point — a shift from traditional automation to true autonomy. This is particularly relevant in procurement, where complexity, fragmentation, and disconnected systems have long been obstacles to efficiency.
Today’s procurement teams face the frustration of managing a tangled web of suboptimal processes, not due to lack of effort or poor technology, but because of the enormous complexity of global operations. Fragmented data and siloed systems make it difficult to gain visibility, act decisively, and adapt to changing conditions. This issue has persisted for more than a decade. Ten years ago, GEP began advocating for a unified source-to-pay (S2P) framework — a seamless process from opportunity identification through purchasing — but even now, many large organizations still struggle to break out of legacy silos.
This persistence highlights a critical truth: the barrier to transformation isn’t the sophistication of technology, but the inertia of existing systems and behaviors. Large enterprises, like massive ships, cannot turn on a dime. They require time and intent to change direction. While AI has already revolutionized sectors like media through generative content, its full impact on enterprise operations will unfold more gradually, following a path similar to the adoption of cloud computing or mobile platforms. Early adopters will take bold steps first, while most organizations will progress more cautiously.
What sets this wave apart, however, is the magnitude of its potential. The shift from automation to autonomy represents a profound leap forward — one that could redefine how procurement operates, but also one that carries risks if adopted recklessly. To understand this transformation, it’s helpful to think in terms of the “three A’s”: analytics, automation, and autonomy.
Analytics has long been the foundation of data-driven decision-making. It helps organizations extract meaning from information and make better choices based on patterns and insights. Artificial intelligence has supported analytics for years, even before the emergence of today’s generative models. Machine learning and Bayesian logic have helped procurement teams analyze spend data, identify trends, and uncover opportunities.
Then came automation, which entered the mainstream about a decade ago. Robotic process automation (RPA) and workflow bots became powerful tools for accelerating repetitive, rules-based tasks such as invoice processing and document management. Over time, these capabilities became integrated directly into enterprise software. A sourcing project for the IT category, for example, could automatically generate the appropriate questionnaires, assign stakeholders, and preselect suppliers — all without manual intervention.
This combination of analytics and automation brought significant efficiency gains and remains foundational to modern procurement. Yet these technologies still rely on human initiation and oversight. What’s emerging now — autonomy — takes this one step further. Agentic AI can not only analyze and automate but also act, reason, and adapt. These intelligent systems operate within defined rules and governance frameworks but are capable of initiating actions, making contextual decisions, and learning from outcomes. This convergence of analytics, automation, and autonomy signals the dawn of a new era for procurement.
Ardent Partners’ analysts recognize this as a genuinely transformative moment — one comparable in scale to the introduction of the internet. For years, procurement leaders have discussed the vision of an intelligent, data-driven operation. Now, for the first time, technology exists that can actualize that vision. Agentic AI does more than accelerate workflows; it contextualizes data, reframes goals, and helps organizations think strategically about value creation.
Bartolini draws an analogy to professional basketball. The objective of the game — to score more points than the opponent — has never changed. But how the game is played has evolved dramatically due to analytics. Data-driven insights have reshaped strategies, redefined positions, and introduced new styles of play. The same kind of intelligence is now within reach for procurement. By leveraging AI-driven insights, teams can identify new opportunities, adapt to shifting markets, and make better decisions with speed and confidence.
Still, the road ahead requires balance. The technology must continue to mature, but organizations also need to prepare culturally and operationally to trust AI with greater autonomy. The transition from human-led to AI-augmented decision-making is not a switch that can be flipped overnight. It requires building confidence, establishing safeguards, and defining clear roles between people and machines.
Agentic AI represents both the next step and the next challenge in procurement’s digital evolution. It offers the promise of a more intelligent, adaptive enterprise — one that learns, anticipates, and acts in real time. Yet its success will depend on the same principle that has guided every major technological transformation: thoughtful implementation and human leadership.
The future of procurement is not being rewritten overnight. It is being drafted now, one deliberate step at a time — by those ready to become true agents of change.
