AI Infrastructure: Hype or Horizon?

Q1. Which technology transformation programs have you been directly accountable for, and what business outcomes or investment decisions ultimately defined their success?

Sixteen years in, the programs I'm most proud of aren't the ones with the biggest budget; they're the ones where architecture genuinely moved a business decision.
I've led transformation initiatives across IoT, cloud-native, and AI/ML platforms for energy and industrial clients in the US, the UK, Europe, Japan, and South Korea. But the moments that defined success were specific. One program I led directly informed a multi-million-dollar asset modernization investment for a Fortune 500 energy client; the business case was built on predictive maintenance savings and operational risk reduction that my architecture work uncovered.
Another was replacing legacy SCADA integrations with a cloud-native data platform that reduced time-to-insight from days to minutes, changing how procurement and scheduling decisions were made downstream.
What I've learned is that transformation programs succeed when Enterprise Architecture stops being a governance function and starts being the bridge between technology options and investment-grade decisions. That shift in positioning changes everything.

Q2. What structural shifts are driving the current wave of investment in AI data centers, and how sustainable do you believe this growth trajectory…