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AI: from pilot to production

Most organisations can already run an AI demo. The hard part is embedding it in a process, assigning ownership, measuring quality and operating it safely.

100 pilots about a quarter arrive DemoPilot AcceptanceProduction no owner of the result quality = “accuracy”, no error criterion
The two stopping points are labelled with their cause. The share is an estimate from the deployment catalogue, not a measurement.

Mechanism

What separates a pilot from operations: data, accountability, economics. A catalogue of 1,352 deployments, the Competence Centre, an industry study.

Who it is for

  • CIOs and transformation leads
  • Process owners
  • Teams whose pilot never reaches production

Typical tasks

  • Selecting use cases with measurable effect
  • Auditing a stalled pilot
  • Defining data and ownership
  • Acceptance criteria for a probabilistic output
  • Vendor and scaling requirements

Formats of involvement

  • Pilot audit
  • Strategy session
  • Production-readiness checklist

Related cases

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