Talking Supply Chain: Turning AI time savings into value

Artificial intelligence is often pitched to procurement teams as a straightforward productivity win—save time, automate work, and move faster. But in this episode of Talking Supply Chain, host Brian Straight digs into why those promised time savings don’t always translate into better decisions or cleaner execution. Joined by Erin McFarland, VP of Operations at Fairmarkit, the conversation quickly moves beyond hype into the operational friction that emerges when AI is layered onto outdated processes and governance models.

McFarland explains that while AI can dramatically reduce effort in areas like contract analysis and sourcing events, it often exposes bottlenecks elsewhere in the process. Speeding up one step only to hit a wall downstream creates hidden drag, sometimes increasing rework, invoice exceptions, or approval delays. Rather than fixing problems, AI can amplify them, making long-standing process and data issues impossible to ignore.

The discussion then turns to risk, governance, and the rapid rise of agentic AI. As AI systems move from making recommendations to executing decisions, McFarland stresses the importance of human-in-the-loop oversight, clear boundaries, and early testing in low-risk scenarios. She compares managing AI agents to managing a BPO—without checkpoints, parameters, and regular review, things can go wrong quickly and at scale.

Finally, the episode tackles the human side of AI adoption: fear, resistance, and opportunity. McFarland argues that most resistance comes from uncertainty, not unwillingness, and that winning over skeptics can turn them into powerful champions. The real value of AI, she notes, isn’t the hour saved, it’s what procurement teams do with that hour once repetitive work is removed. For leaders trying to move from AI pilots to real ROI, the takeaway is clear: define success early, measure outcomes relentlessly, and let technology serve strategy, not the other way around.

Listen today.

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