AI readiness assessment
Find the gap between your AI ambition and your IT reality.
A practical review of current AI use, data exposure, Microsoft 365 readiness, cybersecurity controls, workflows, and support risks — with a prioritised roadmap at the end.
What the assessment covers
1. Current AI usage
Where AI is already being used, which tools are approved or unmanaged, and where staff may be creating avoidable data or compliance risk.
2. Data and permissions
Whether your Microsoft 365, SharePoint, Teams, identity, and file permissions are ready for AI tools that can surface information quickly.
3. Security foundations
MFA, conditional access, endpoint protection, backup, monitoring, and the basic controls that need to exist before AI scales across the business.
The output is deliberately practical
You get a clear view of risk, quick wins, priority fixes, recommended AI use cases, and what needs to be governed before rollout. No theatre. No 80-page shelfware strategy.
- AI risk summary
- Approved-tool guidance
- Data exposure priorities
- Microsoft 365 and Copilot readiness notes
- Automation opportunity shortlist
- Governance roadmap
- Security control gaps
- Implementation and support plan
Who it is for
Leadership teams that know AI matters, but do not yet have a controlled path from policy to secure implementation and daily support.
What an AI readiness assessment should answer
Before investing in Microsoft Copilot, private AI, or custom AI agents, you need to know whether your data, permissions, security controls, policies, and workflows are ready. Our assessment gives you a prioritised roadmap rather than a generic report.
The MonitorLabs AI Readiness Framework
The assessment scores readiness across six practical dimensions, giving leadership a clear view of where AI can be adopted safely and where risk needs to be reduced first.
1. Strategy and business value2. Governance and ownership3. Data readiness4. Security and compliance5. Platform and integration6. Adoption and change
Maturity scoring
Each area is scored from unmanaged to optimised, with evidence, risk notes and recommended next actions. This avoids vague consultancy language and gives procurement, IT and leadership a measurable baseline.
Assessment outputs
Typical outputs include an executive summary, maturity scorecard, AI risk register, data and permissions findings, prioritised use-case roadmap, governance actions and a 30/60/90-day implementation plan.