AI strategic coherence at 0.425: why projects drift inside the AI bubble

What does AI strategic coherence at 0.425 measure in the AI bubble?

Coherence belongs to domain A, internal alignment, together with integrity at 0.458 and resonance at 0.325. It measures whether an organization agrees with itself about AI: the aims written in the plan, the budget that follows, and the projects that run. A value of 0.425 puts the enterprise AI market in the fragile zone on this dimension. The study computed it from public data in April 2026.

The dimension matters for the AI bubble because valuations assume that announced plans become delivered products. Coherence is the check on that assumption. When the plan and the practice diverge, expected returns drift from real returns, and the gap grows with every new pilot that starts without a path to production.

How does a gap between AI strategy and practice show up in a company?

The gap has a recognizable shape. Meetings describe the company as AI-first, while the projects on the ground are proofs of concept that never reach production. The plan speaks of transformation, the budget funds experiments, and the people closest to the work see no change in their tasks. Each layer reports success to the layer above it.

The study calls such a mismatch dangerous. Reports can stay positive while real progress stalls, because each team reports against its own slice of the plan. A leader who reads only the plan sees a strategy, and a leader who walks the floor sees pilots. Coherence at 0.425 says the second view is common across the enterprise AI market.

Why do 31% of failed AI projects trace back to missing strategy alignment?

The study ranks missing alignment with strategy second among the causes of failure, at 31%, behind insufficient or biased data at 42%. It sits ahead of team resistance at 24%. Because the shares overlap, a project that lacks alignment often fails on other counts too, and the lack of a shared aim makes each other problem harder to fix.

MIT counted 95% of generative AI projects failing in production in 2025. Strategy misfit is one reason that pilots stall: nobody owns the step from experiment to operation, so the work stops when the pilot budget ends. The cause is organizational, which is why the study treats it as a structural dimension and not as a technical bug.

What does an AI strategy audit look like step by step?

The study recommends measuring the alignment between the stated AI strategy and what happens on the ground, and it calls a large gap a dangerous mismatch. A practical audit has 4 steps: write down the stated goals, list the running projects, match each project to a goal, and mark which ones have an owner and a production date. The whole exercise fits on one page and takes a morning.

Two simple ratios come out of the audit. The first is the share of projects that map to a stated goal. The second is the share of pilots with a production date. Low values on either ratio show where the plan and the practice separate, and repeating the audit each quarter shows whether the gap narrows.

Which AI bubble pressures push company strategy off course?

The study lists headline figures that frame the market in 2026: valuations up ×4 over 18 months, productivity gains of +40%, and 300 million jobs disrupted. Numbers of that size create pressure to announce an AI plan quickly. A plan written under pressure often skips the step that links it to existing operations.

A regulatory date adds to the pressure: AI Act compliance falls on 2 December 2027, according to the study. Deadlines focus attention, yet they also invite plans built to satisfy a calendar. A coherent plan starts from the business problem and works toward the deadline, and the order of those two steps decides the outcome. The same logic applies to boards that ask for an AI slide before they ask for an AI problem.

How far does the AI market score move when AI strategic coherence improves?

The third recommendation in the study targets coherence directly. Moving it from 0.425 to 0.55 means leaving behind the pattern of AI-first statements and proofs of concept that stay in the lab. The study frames it as an audit of strategy against field reality, repeated until the two descriptions match.

In the study the 4 corrections together lift the market score from 0.337 to 0.401 and cut the predicted failure rate from 94% to 82%. Coherence supplies one of the four steps, and each step lifts a different dimension. A team can start with the audit, since it needs no new tools, only a list of goals and a list of projects.

How should you read AI strategic coherence as an AI bubble signal?

Read low coherence as a delivery risk that sits under every valuation. Plans create expectations, and expectations create prices. If coherence stays near 0.425 while announcements continue, the distance between promised and delivered results can widen. This page is general information, not investment advice, and it reflects the study as of October 2026. Track the value each quarter and compare it with the previous one.

For your own organization, the Λ simulator estimates your φ(S) in about 10 minutes, and a 30-minute call with the EQOS Asia team can review your AI plan against the nine dimensions. You leave with a coherence value you can track each quarter and a list of the projects that lack an owner.

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About the author

Stéphane Jambu

President, EQOS Forecast Asia

Stéphane Jambu leads EQOS Forecast Asia and works as a consultant in e-commerce, search visibility, and AI. LinkedIn profile