You can outsource your thinking, but you can’t outsource your understanding.

AI & Copilot

Turn Microsoft AI capability into useful, governed business solutions

AI creates value when it is grounded in the right information, connected to real work and deployed with clear controls. I help organisations move from curiosity to secure, practical use cases across Microsoft 365 Copilot, agents, Microsoft Foundry and the wider Azure platform.

Understanding stays at the coreA head in profile with a rose at its centre, representing human understanding, while a network of AI connections reaches outward from it.
01

Copilot readiness and adoption

Microsoft 365 Copilot is the AI assistant built into Word, Excel, Outlook, Teams and SharePoint. Assess licensing, data quality, permissions, governance, priority scenarios and user readiness. Produce a practical roadmap rather than a generic AI strategy.

02

Copilot agents and extensibility

Copilot agents are focused assistants built for a specific task or team. Design agents that answer, reason and act using approved organisational knowledge and business processes. Select the appropriate route across Microsoft 365 Copilot, Copilot Studio, custom development and APIs.

03

Microsoft Foundry

Microsoft Foundry is Microsoft’s Azure platform for building custom AI applications and agents. Prototype and build governed AI applications and agents with managed models, tools, identity and deployment options, plus evaluation and observability capabilities where available. Capabilities change over time and some remain in preview. Choose between prompt-based and custom hosted approaches based on control, scale and operational needs.

04

Work IQ

Work IQ is Microsoft’s workplace intelligence layer for Copilot and agents. Explore permission-aware workplace intelligence for agents that need context from Microsoft 365 and connected business systems. Define safe use cases, integration patterns, governance boundaries and measurable outcomes.

05

Frontier evaluation

Frontier is Microsoft’s early-access programme for new Copilot and agent capabilities. Help IT teams evaluate emerging Microsoft Copilot and agent capabilities through controlled pilots. Define participants, success criteria, risk controls, feedback and the decision path from preview to wider adoption.

From prototype to production

AI engineering and governance

Start with a focused workshop or prototype and leave with a decision, architecture and next-step plan.

  • Use-case discovery and prioritisation
  • Retrieval, grounding and data access design
  • Agent instructions, tools and workflow design
  • Security, permissions and responsible AI controls
  • Evaluation, testing, observability and cost management
  • Human review and escalation patterns
  • Production integration and adoption support

Questions

Common questions about Copilot and AI agents

What is Microsoft 365 Copilot readiness?

Copilot readiness is the work needed before Microsoft 365 Copilot is rolled out: checking licensing, cleaning up permissions and oversharing, improving the quality of the content Copilot will draw on, setting governance, and choosing priority scenarios so users see value quickly.

Does Copilot respect SharePoint permissions?

Yes. Microsoft 365 Copilot only uses content the signed-in user already has permission to access. That is why readiness work focuses on permissions: if content is overshared, Copilot can surface it to people who technically have access but should not.

What is the difference between Copilot Studio and Microsoft Foundry?

Copilot Studio is a low-code tool for building agents that extend Microsoft 365 Copilot and connect to business data and processes. Microsoft Foundry is Microsoft's Azure platform for building custom AI applications and agents with more control over models, tools, hosting, evaluation and observability. The right choice depends on the control, scale and operational support you need.

How do you keep AI agents secure and governed?

By designing security in from the start: permission-aware data access, approved grounding sources, clear agent instructions and tool boundaries, responsible AI controls, human review and escalation for higher-risk actions, and evaluation, monitoring and cost management once the agent is live.

Where should an organisation start with AI?

Start with a focused workshop or prototype built around one real business question. The aim is to leave with a decision, an architecture and a next-step plan, rather than a generic AI strategy.

Discuss an AI use case

Make the next step specific and testable

Bring a business question, an existing pilot or a governance challenge.

Discuss an AI use case