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Why AI Stalls.

Most AI initiatives stall somewhere between the demo and production. The documented failure modes, the real numbers behind them, and what crossing the deployment gap actually takes.

Pillar

Why AI pilots fail

MIT found 95 percent of organizations investing in generative AI see no measurable return. The failure modes behind it, and what the 5 percent do differently.

Analysis

21 Aug 2026 · 5 min

T-50

Proof of concept vs production AI: different questions, not different polish

A PoC asks whether the model can. Production asks whether the organization can depend on it. Confusing the two is how 29 in 33 PoCs stall.

Definitions

02 Oct 2026 · 5 min

T-45

Pilot purgatory, and how to leave it

The state where AI pilots neither die nor ship has a name, three tells, and one exit: replace the renewal decision with a binary one.

Analysis

18 Sept 2026 · 5 min

T-30

The AI deployment gap

Models keep clearing benchmarks while 95 percent of organizations see no measurable return. The gap between those facts has a shape: three distances, closable.

Definitions

11 Sept 2026 · 5 min

T-17

From AI pilot to production: the crossing, step by step

Most pilots never make it: IDC counted 4 in 33. The six-step crossing that gets an AI system into production, written for operations-scale teams.

Playbooks

21 Aug 2026 · 6 min

T-16

AI project failure statistics: every number, sourced and reconciled

95%, 88%, 80%, 42%, 40%, 30%: the AI failure statistics quoted everywhere, what each one actually measured, and why they do not contradict each other.

Analysis

21 Aug 2026 · 6 min

Other topicsForward-DeployedAI AgentsInternal ToolsProduction AIAutomationChoosing a Partner

03 · Start

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