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Description

Industrialising AI: Stabilising, Deploying and Maintaining Use Cases in Production

Taking a promising prototype past the barrier of production release and sustainable operation

  • 0.43 days — 3 h
  • In-person or virtual
  • Expert
  • Up to 6 participants

The prototype worked in the lab and impressed in the demonstration. Then come real volumes, edge cases nobody anticipated, data access questions, handover to an operations team and the true cost of daily use. Many use cases stop right there.

This short-format programme is designed for experienced professionals. It addresses scaling up: criteria for selecting the use cases worth industrialising, the technical and organisational requirements to be met, the production monitoring set-up and the conditions for decommissioning a use case that no longer serves a purpose.

Learning objectives

  • Assess whether a prototype can withstand real and sustained use
  • Define data, access and traceability requirements ahead of deployment
  • Organise the handover of the use case to an operations team
  • Set up monitoring of performance and drift in production
  • Decide whether to continue, develop further or decommission a use case

What makes this programme different

A maturity assessment grid is applied to the prototypes brought by participants
The operations handover pack is drafted during the session
Decommissioning conditions are formalised with the same rigour as launch conditions

Programme

1Assessing prototype maturity

Not every prototype deserves production

  • Gap between demonstration conditions and real usage conditions
  • Volumes, edge cases and boundary behaviours
  • Technical dependencies and reversibility of design choices
  • Running cost measured against expected usage

2Preparing for deployment

Meeting the conditions before you switch over

  • Data supply chain and quality controls
  • Management of access rights, secrets and audit trails
  • Deployment, rollback and versioning procedures
  • Documentation and operations handover pack

3Operating and evolving the solution

Going live is not the end of the project

  • Performance monitoring and drift detection
  • User feedback loop back to the product team
  • Reassessment cadence and management of model changes
  • Criteria and procedure for decommissioning a use case

Who is it for

Data and AI leads · architects · technical project managers and operations managers who have already run experiments.

Prerequisites

Having taken at least one AI experiment through to a working prototype.

Dates & locations

12 scheduled dates between November 2026 and December 2027. Seats are confirmed in the order enquiries are received.

November 2026

December 2026

January 2027

February 2027

March 2027

April 2027

May 2027

June 2027

September 2027

October 2027

November 2027

December 2027

None of these dates suit you? We open additional sessions on request, and any programme can be run privately for your team.

Practical details

Before the programme
Online positioning questionnaire. Your development objectives are shared with the trainer, who tailors the practical case studies to your context.
Teaching methods
Theoretical input, workshops and practical case studies. Digital course materials and method sheets provided.
Assessment
Multiple-choice tests and role-play exercises. Assessment of learning at the start and end of the programme, with immediate and 60-day follow-up evaluations.
After the programme
One year of access to the e-learning platform. Self-assessment of the skills acquired and a 30-day follow-up session with your trainer.
How to register
Registration online or on the basis of a quotation.
Lead time
11 working days after confirmation of registration.
Accessibility
Accessible to people of determination. Contact our accessibility coordinator to design a suitable solution: contact@mpf-academy.ae
Start dates
Rolling intake: in addition to the scheduled sessions, this programme can start on request.