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.

This month’s thread: the economic and operating model shift from AI as “capability” to AI as “execution” and what that does to software spend, governance, and workforce planning.

As AI spending by enterprises slows due to AI optimization, how will the economy fare in 2026—and more importantly, what will it mean for enterprise technology budgets? KPMG wrote, “We enter 2026 looking in two directions at once. One face sees the promise of AI and the stock market returns it is generating. The other…