Despite heavy investment, 95% of generative AI (GenAI) pilots are failing1 and, at the same time, more than 50% of businesses report moderate to severe technical debt that’s expected to reach 75% by 2026 as AI intensifies pressure on already strained systems2. These failures aren’t about AI being...
Nearly all AI conversations start with sweeping promises and buzzword bingo—transformation, automation, reinvention, optimization. Yet most businesses don’t need aspiration; they need a roadmap they can trust. Traditional AI roadmaps have become moving targets: unfocused, unachievable, and rarely tied to the outcomes that matter. What leaders want is a clear, measurable path that shows how AI can deliver ROI in...
I had the opportunity to present at HIMSS 2026 on something that keeps me up at night—how healthcare organizations can actually deploy AI in ways that work. Not the hype, not the theory, but the real infrastructure and governance you need to make this stuff operational. Here’s my take on what matters. The Need for Trusted AI Healthcare has...
Why the gap between “able to move” and “able to run well” is wider than most expect. Not too long ago, assessing cloud-readiness meant simply virtualizing or moving an app. In hyperscale deployments, though, organizations began to understand that “cloud-ready” wasn’t the same as “hyperscale-ready.” Many apps can run in the cloud, but shouldn’t because of performance, cost, data, and...
