← Selected work

Responsible organisational adoption

AI adoption connected to real work

An anonymised programme combining practical training, workflow implementation, accountable governance and adoption reporting.

Training tied to workHuman accountabilityMeasured adoption
OPERATING ARCHITECTURESYSTEM / CONTROL / EVIDENCE

A governed adoption layer connecting approved tools to real workflows while retaining human decision ownership.

EXTERNAL BOUNDARYOrganisation data boundaryApproved model providers
  1. 01
    People and rolesMake accountability explicit
    • Workflow owner
    • Practitioner
    • Reviewer
  2. 02
    Approved capabilityBound the technical choices
    • Approved tools
    • Prompt patterns
    • Knowledge sources
  3. 03
    Workflow layerApply capability to work
    • Task intake
    • Assisted production
    • Human review
  4. 04
    Governance and measureControl and improve adoption
    • Risk register
    • Usage evidence
    • Outcome review
ASSURANCE BOUNDARYRisk classificationData-use boundaryNamed reviewerPeriodic outcome review
KEY CONNECTIONS
  1. 01Role to permission
  2. 02Workflow to approved tool
  3. 03Output to human review
  4. 04Usage to measurement
Illustrative architecture — anonymised reconstruction.
ACCOUNTABLE PROCESS FLOWINPUT / OWNER / OUTPUT / EXCEPTION
  1. 01
    Workflow ownerIdentify
    Input
    Operational need
    Output
    Candidate use case

    ExceptionNo accountable owner

  2. 02
    Governance leadClassify risk
    Input
    Candidate use case
    Output
    Permitted handling route

    ExceptionRestricted data or decision

  3. 03
    PractitionerPrototype
    Input
    Approved route
    Output
    Test workflow

    ExceptionQuality threshold missed

  4. 04
    Adoption leadTrain
    Input
    Tested pattern
    Output
    Role-ready capability

    ExceptionConfidence gap

  5. 05
    Workflow ownerDeploy
    Input
    Approved pattern
    Output
    Controlled live use

    ExceptionBoundary breach

  6. 06
    Named reviewerReview
    Input
    Assisted output
    Output
    Accepted human decision

    ExceptionOutput rejected

  7. 07
    LeadershipMeasure
    Input
    Usage and exceptions
    Output
    Adoption decision

    ExceptionLow use or weak outcome

Illustrative process flow — anonymised reconstruction.

A fictional interface reconstruction showing the principal operating controls described in this case study.

Illustrative interface — anonymised reconstruction.

Situation

The operating context

People had uneven confidence, fragmented experimentation and no shared operational standard for the safe use of generative AI.

Mandate

The work to be done

Move beyond awareness sessions by connecting learning to real work while keeping people accountable for decisions and outputs.

Delivered

What the work connected

  • Role-relevant training and upskilling
  • Practical workflow implementation
  • Governance and usage boundaries
  • Documentation and reusable patterns
  • Adoption and usage reporting

A useful first conversation

If your system is fragmented, start with the whole view.