Elli Peterson's TechCrunch

When our procurement organization first embarked on integrating artificial intelligence into our sourcing operations three years ago, we approached it with a mix of excitement and trepidation. Like many teams managing complex supplier networks and multi-million dollar category strategies, we faced mounting pressure to reduce Procurement Cycle Time while simultaneously improving spend visibility and supplier performance measurement. What we learned through trial, error, and eventual success offers valuable insights for any procurement professional navigating this transformation. The journey toward AI Procurement Integration began not with technology selection, but with a hard look at our most painful operational bottlenecks. Our Spend Analysis process consumed weeks of manual data cleaning, our Supplier Risk Assessment relied on outdated spreadsheets, and our RFQ management system couldn't predict which suppliers would actually deliver competitive bids. These weren't abstract p...

When our procurement team first embarked on integrating artificial intelligence into our operations five years ago, we had ambitious goals but little practical understanding of what the journey would actually entail. Like many enterprise procurement organizations managing billions in spend, we saw AI as the solution to our persistent challenges around spend visibility, supplier risk management, and contract compliance. What we discovered through trial, error, and eventual success has fundamentally reshaped how we approach procurement transformation. These lessons from the frontlines of implementing AI in Procurement Operations offer practical insights that go far beyond vendor whitepapers and conference presentations. The initial push toward AI in Procurement Operations came from our executive leadership after a particularly painful quarter where supplier disruptions cascaded through our manufacturing operations. We had the data—purchase orders, supplier scorecards, contract terms, in...