Enterprise AI faces 2026 reckoning to scale or stall

Summary

In an opinion piece for CIO, consultant Michael Bertha argues that after two years of pilots and proofs‑of‑concept, 2026 will separate organizations that can scale AI from those stuck in perpetual experimentation. He describes a growing "expectation versus execution" gap: boards have read the same reports promising double‑digit productivity gains, but many CIOs lack the operating model and capacity to deliver them. The article sketches a playbook that starts by turning IT itself into a productivity showcase—using tools like GitHub Copilot to measurably cut development time—then federating AI delivery via domain‑specific centers of excellence rather than a single, overloaded central team. Bertha stresses that the winning model is a hub‑and‑spoke structure where a central AI group provides platforms and guardrails while business units own outcomes and funding. For enterprises staring at mounting AI spend with limited ROI, the message is blunt: 2026 is the year you either architect for scale or risk losing credibility with both leadership and frontline teams.