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Microsoft Copilot and AI

Responsible AI

Policy, risk classification, human review design and monitoring that your risk function can defend.

Talk to an expert All Microsoft Copilot and AI

Technologies

  • Microsoft Purview
  • Azure AI Content Safety
  • Microsoft Entra ID
  • Microsoft 365 Copilot

Responsible AI fails when it becomes a document nobody reads. We build it as an operating model: who classifies risk, who approves a scenario, where a human must review, and how incidents are handled.

Business outcomes

Defensible position

A written stance on acceptable use, agreed once rather than debated per scenario.

Proportionate control

Scrutiny that follows consequence, so low-risk work is not blocked.

Incident readiness

A defined route when an AI output causes a problem.

Capabilities

Policy and acceptable use

What may and may not be entered into AI tools, agreed with legal and risk.

Risk classification

A scheme that sorts scenarios by consequence and sets review requirements.

Human-in-the-loop design

Where a person must review, approve or override, and how that is evidenced.

Monitoring and response

Logging, quality review cadence and an incident route.

How we deliver it

  1. Assess

    Evaluate data readiness, permissions, licensing and candidate scenarios against value and feasibility.

  2. Prepare

    Curate content, review permissions, assign ownership and establish the governance position.

  3. Pilot

    Build and evaluate with a cohort whose daily work matches the scenarios, measured against a baseline.

  4. Scale

    Extend to further scenarios with champions, enablement and a standing content backlog.

  5. Operate

    Monitor quality, review gaps weekly and maintain grounding sources on a fixed cadence.

Next step

Considering Responsible AI?

We will give you an honest view of the effort involved, the prerequisites and the risks, before anyone signs anything.

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