By Erin McFarlane, VP of Operations at Fairmarkit

For years, procurement leaders have been caught between aspiration and execution, eager to harness AI’s potential, yet constrained by fragmented data, legacy systems, and cautious internal cultures. But in 2026, the industry crosses the threshold from experimentation to impact. This is the year AI moves out of the lab and into the day-to-day rhythm of procurement operations, not as a bolt-on capability but as the structural backbone of how work gets done.

AI is the catalyst for procurement teams to reimagine their operating model: from workflows that require constant human activation to environments where digital agents anticipate, orchestrate, and adapt. We’re already seeing partners viewing AI as a teammate rather than a tool, supercharging contributors and team leaders alike.

Why 2026 Marks the Tipping Point for Full-Scale AI Integration

Across the last decade, enterprises have upgraded key pieces of the tech stack: cloud platforms, real-time data infrastructures, and embedded analytics. AI has remained in pilot mode for some time, and understandably so. The technology continues to move fast, with mainstream stakeholders still waiting to get a better grasp on how performance can influence cycle times, savings and other key metrics.

Those who got off to an early start are now seeing cycle times drop up to 90%, savings lift significantly, and teams operating with greater visibility and efficiency than ever. This stems from a few root developments:

First, data maturity has reached a point where AI systems can consume, correlate, and interpret procurement information without months of normalization. Enterprises spent the past few years consolidating ERPs, modernizing sourcing workflows, and cleaning the kind of messy metadata that once undermined models. Clean data is no longer the dream; it’s the expectation.

Second, cloud modernization has made AI scalable. Instead of selective use cases with narrow inputs, procurement teams can now run continuous analysis across categories, regions, and suppliers without drowning IT in custom integrations. Infrastructure can finally support the ambition.

But the most significant catalyst is the rise of agentic AI: models that don’t just recommend but act. Predictive analytics was the warm-up. Autonomous decisioning is the main event. With mature data pipelines, modern compute environments, and AI agents capable of reasoning and execution, procurement’s operating model fundamentally changes.

Once organizations experience that level of speed, savings, and strategic lift, there’s no going back.

How Agentic AI Is Reshaping Expectations for Procurement Tools

The industry has long imagined procurement tools that behave less like static software and more like strategic collaborators. Agentic AI gets us there not by adding more dashboards, but by eliminating the need for them.

These systems proactively initiate sourcing events when demand spikes, monitor supplier risk in real time, negotiate dynamically based on market shifts, and escalate only when human judgment is essential. They think, act, and learn, functioning more like digital coworkers than digital filing cabinets.

This raises the bar for what teams expect from technology. It’s no longer enough to offer automation or insights. Tools must demonstrate autonomy, adaptability, and continuous improvement.

In earlier eras of AI, procurement leaders asked: What can the system automate for me? In 2026, the question becomes: What can the system autonomously achieve without me?

That shift reframes procurement’s value proposition. With AI agents handling the heavy operational lift, people can finally focus on work that demands creativity, relationship building, and strategic vision.

The Cultural and Skills Gaps Still Slowing Adoption

Our top-performing customers display a mindset rooted in curiosity, continuous learning, and a bias toward progress. They encourage teams to experiment, celebrate iteration, and pursue “better” over “perfect.” They recognize that innovation is a habit, not a one-off initiative. And they treat AI as a chance to redesign work for smarter, faster outcomes, not simply to maintain the status quo more efficiently.

Many organizations are still operating with a pilot mentality. They’re locked in patterns of risk aversion, siloed decisioning, and over-reliance on legacy processes that were never designed for automation. This mindset creates a confidence gap in trusting AI with decisions, even when those decisions are low-risk and high-benefit.

A second challenge is skills. Procurement teams don’t need to become data scientists, but they do need data literacy: enough understanding to evaluate AI outputs, question assumptions, and iterate with confidence. They also need stronger change-management muscles. Implementing agentic AI reshapes how teams work. It changes decision paths, handoffs, and the pace of execution in ways that go beyond installing new tech.

The most successful organizations pair powerful AI with thoughtful human-in-the-loop models, ensuring teams remain confident and in control. In practice, autonomy amplifies what people do best. The system carries the routine load so teams can focus on judgment, creativity, and the priorities that actually move the business.

How Leaders Can Measure Real Impact Beyond Automation

Forward-thinking procurement leaders are shifting their metrics from “How much time did we save?” to “How much advantage did we create?” That includes:

• Resilience: Can AI diversify suppliers, surface alternatives, and predict disruptions before they impact the business?
• Predictability: Are forecasts more accurate? Are processes more stable and reliable?
• Compliance: Does AI drive better adherence to policy through intelligent routing and real-time monitoring?
• Decision Velocity: Are insights and recommendations delivered fast enough to influence outcomes, not just report on them after the fact?
• Spend Influence: Is procurement expanding its impact across more spend categories and more stakeholders?

Agentic AI delivers compounding value. The more it learns, the better it performs; the more data it sees, the more predictive and prescriptive it becomes. Traditional ROI frameworks rarely capture that compounding effect. Leaders need a measurement model that reflects strategic lift, not just operational efficiency.

2026 will be a Breakthrough Year for Procurement

Procurement has reached a decisive moment. The technologies are ready. The infrastructures are stable. The AI models are capable. What remains is the critical choice to shift from pilots to adoption, from hesitation to confidence, from manual orchestration to autonomous execution.

In 2026, AI becomes procurement’s backbone: operational, intelligent, and deeply embedded in how value is created. The leaders who embrace that shift will shape more resilient supply bases, more informed decisions, and more strategic influence across the enterprise.

This is the year procurement stops imagining what AI could do and starts realizing what AI can achieve.

Erin McFarlane is the VP Operations at Fairmarkit. A former procurement executive, Erin has held leadership roles in the financial services and technology sectors. She resides in the greater Boston area.