Insights, strategies, and lessons from the frontlines of AI implementation. Real stories from real projects.
Picture your CIO in a board meeting two years ago, confidently presenting a three-year AI platform contract. The model was state-of-the-art. The vendor promised the moon. The ink dried on a commitment that felt like smart, long-term thinking. Now fast-forward: a newer model arriv
Picture a mid-market manufacturing company in Ohio. They've run three AI pilots in the past eighteen months: a document extraction tool in accounting, a demand forecasting model in operations, and a customer service chatbot their sales team stood up with a vendor they found at a
A mid-market CIO approves seven AI tools over eighteen months. When asked what they've returned, there's a pause. That pause is worth $16.3 billion across U.S. mid-market companies annually. Freshworks' Global Cost of Complexity Report , a 2026 study of 12,021 IT decision makers
Four vendor announcements. One week. And enough "AI teammate" messaging to fill a keynote graveyard. In the span of roughly seven days, Zoom, Microsoft, Snowflake, and Asana all launched products they're calling some variation of an AI agent for enterprise workers. ZoomMate turns
Picture a 70-year-old gum company, the one whose comic strip wrappers you collected as a kid, deploying agentic AI workflows to forecast demand, develop new candy formulations, and deal with tariff-driven supply chain disruption. That's Bazooka Candy Brands in 2026, and it's one
Somewhere right now, a finance team is opening an invoice that will ruin their quarter. They won't see it coming, because no one told them AI billing works differently than every other line item in the budget. One uncapped license can quietly multiply across automated workflows u
Three in four enterprise AI customer service agents get rolled back or shut down after deployment. Not before launch. Not in testing. After they're live, after the budget has been spent, the vendor has been paid, and the internal announcement has gone out. That number comes from
Picture a senior executive at a well-known public tech company. She runs roughly a thousand engineers. Nearly every one of them uses AI. And yet, as Azeem Azhar recounted in Exponential View , the needle won't move on her bottom line. This isn't an isolated story. MIT research fo