Governance
Acceptable use, data classification, privacy, DLP, platform suitability, Shadow AI risk and human oversight.
AI Adoption Case Study
Governance → Pilot → Adoption → Measurement → Scale
A practical approach to introducing generative AI in a professional-services environment: establish guardrails, test real use cases, measure adoption and use evidence to decide what should scale.
Context
AI adoption as an operating-model problem.
In an organisation of approximately 120 staff, a governed AI pilot covered about 40 employees. The objective was not simply to introduce an AI product, but to understand where AI could add practical value while protecting organisational information and retaining human accountability.
Pilot
Use cases included tenders, data analysis/statistical modelling, coding assistance and QA.
Adoption
Focus on repeatable usage and useful business outcomes rather than licence assignment or one-off experimentation.
Measurement
Microsoft 365 usage reporting through Graph/PowerShell provided repeatable telemetry to support adoption analysis.
Measurement
Measure behaviour, not enthusiasm.
Microsoft Graph and PowerShell were used to build repeatable Microsoft 365 usage reporting,
including reporting patterns using Reports.Read.All,
Invoke-MgGraphRequest and CSV extraction from reports such as
getM365AppUserDetail(period='D7').
The purpose was to support analysis of active and repeat usage, adoption trends, workload usage and whether observed behaviour aligned with the pilot's intended use cases. Qualitative user feedback remained important because telemetry alone does not prove business value.
This should be understood as adoption and usage measurement capability. It is not presented as proof of Copilot-specific adoption unless the underlying Microsoft report explicitly supports that conclusion.
Scale
Use evidence to decide what happens next.
Expand repeatable, valuable use cases with acceptable risk.
Improve controls where data handling or operating risk needs work.
Redesign or stop low-value or poorly controlled use cases.
Measure again after material changes to platform, users, data, workflow or risk.
Leadership Principle
Success is not the number of licences assigned.
It is governed, repeatable usage with evidence of value.