AI has entered a post-promise phase, where the conversation has shifted from model excitement to the harder work of infrastructure, governance, data readiness, and operating model redesign. Spending continues to climb, with Gartner projecting $2.52 trillion in worldwide AI spending for 2026, yet more than half of CEOs…

This month’s thread: AI has entered the postpromise stage. The conversation is moving away from model fascination and toward infrastructure, data movement, governance, cybersecurity, workforce redesign, and operating model control.

This month’s thread: AI has crossed from novelty into controlled execution. The market still talks about models, agents, and intelligence, but spending has shifted to the infrastructure required to make AI usable: data, security, governance, compute power, and the people able to redesign work around it.

The market is still talking about models, agents, and intelligence, but the spend pattern has shifted toward the infrastructure required to make any of it usable: data, security, governance, compute power, and the talent able to redesign work around them. The strategic question is whether the enterprise can afford,…

A fast read on what’s changing—and what it means for leadership. This summary distills the key signals shaping enterprise AI, including uneven value realization, rising costs, and governance pressures. Built for boards and executives who need clarity on where to focus as AI becomes a core operating priority.

This month’s thread: the breakdown of the “AI promise curve” as it meets execution reality exposes cost structures, governance gaps, and architectural misalignment, forcing enterprises to shift from model-centric thinking to system-level design.