The AI plateau: What smart CIOs will do when the hype cools
Summary
Generative AI has moved from headline-grabbing hype into a more sober, practical stage the article calls the “AI plateau.” Rather than signalling failure, this phase marks the shift from experimentation to embedding AI into core business processes. CIOs face the real work of scaling, governance, data quality and measurable outcomes. The piece outlines a pragmatic playbook: focus on business problems, adopt a two-speed strategy, and build minimum viable products (MVPs) to iterate quickly and avoid over-engineering.
Key Points
- The “AI plateau” describes a maturity phase where novelty gives way to operational implementation and accountability.
- CIOs should prioritise business problems over chasing AI for its own sake; select use cases that clearly drive measurable value.
- Adopt a two-speed approach: fast, tactical projects for quick wins and slower, governed projects for core systems that need robust data and integration.
- Start with minimum viable products, learn fast and iterate — long, all-encompassing projects risk becoming obsolete before delivery.
- Main obstacles at scale include data quality, integration complexity, governance gaps and vendor costs; addressing these is essential to realise value.
Why should I read this?
Because this isn’t another breathless AI puff piece — it’s a short, practical checklist for CIOs and IT leaders who want to stop wasting time on shiny pilots and actually deliver value. If you’re responsible for turning AI experiments into business outcomes, the three takeaways here will save you grief (and budget) down the line.
Author style
Punchy and no-nonsense. Tim Murphy pulls the plug on hype and pushes CIOs to be selective, pragmatic and accountable. If you’re in IT leadership, the tone says: act smart now or get left doing expensive experiments.
Context and Relevance
This article matters because enterprise AI is entering the stage where costs, governance and scale determine winners. It mirrors past tech cycles (think dot-com → internet stabilisation) and aligns with industry research showing most organisations haven’t scaled AI widely. For CIOs, the guidance supports broader trends: tighter governance, focused use-case selection, and iterative delivery — all essential to sustainably embed AI into organisational workflows.