Podcast
Pierre Mitchell | Will AI Replace Procurement Teams?
47 minutes
Description
Pierre Mitchell of Spend Matters has spent years helping companies answer one of procurement’s hardest questions: where is the money actually going? Even now, many teams still lack clear spend visibility, which makes it harder to find savings, manage risk, and make better decisions.
Pierre breaks down why spend analytics is still difficult, why AI is different from past hype cycles, and which areas will be automated first. He explains why contracts are a strong use case for AI, why AI needs the chassis of deterministic systems, and why human judgment still matters.
The conversation also covers supplier negotiations, e-auctions, sourcing automation, and why direct versus indirect is the wrong debate. The real line is complexity.
Speakers
Spencer Penn
CEO & Co Founder
Pierre Mitchell
Spend Matters
Key moments
CFOs have a ledger. Why don't CPOs?
After 25 years, why spend visibility still isn't a given, and how the ROI death march derails it.
Spend analytics: The hardest part
As procurement looks beyond simple sourcing, the difficulty of spend analytics goes up dramatically.
AI in procurement: Hype or here to stay?
Is AI just another hype cycle like blockchain? Spencer and Pierre agree it isn't.
AI optimism vs. skepticism
Real value comes from fitting probabilistic AI together with deterministic SaaS systems.
Future AI areas
Which parts of procurement AI will change most, starting with language-heavy work like contracts.
AI and automated tasks
Why RPA was so fragile, and how LLMs can make automation more robust.
RPA is dead. Agentic AI is the fix
How agentic AI links low-level APIs into high-level automation that finally works across systems.
AI as a workforce replacement
The real divide isn't direct vs. indirect. It's low complexity vs. high complexity.
Direct and indirect automation
The sweet spot for quick automation is low-complexity, highly repeatable work, wherever it sits.
The technology Pierre is most excited about
Why ontologies and knowledge graphs could bridge AI and a company's deterministic data.
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