Managed AI Operations
Someone owns it on Monday morning.
Implementations decay. Permissions drift, licenses change, models are retired, and the person who understood the design moves on. Managed AI Operations is the standing arrangement that keeps what we built, or what you already run, working and reviewed.
What it is
A continuing engagement with a named owner on our side, an agreed scope, an agreed change process, and reporting that tells you what changed, what it cost, and what needs a decision.
What this is not
We do not make production changes autonomously and we do not describe automated analysis as an autonomous operator. Changes follow an approved plan. Where automation proposes something, a person approves it before it is applied.
Who it is for
- Organizations without an internal team to hold the operational load
- Teams whose implementation has already drifted from its design
- Organizations that need continuity of ownership across staff changes
- Customers who want the same team that built it to keep running it
What we do
- Monitoring of the services and configurations in scope
- Permission, license, and configuration drift review on a set cycle
- Change management with approval before production changes
- Incident response within agreed responsibilities
- Microsoft roadmap and retirement tracking for what you depend on
- Reporting written for the person who has to make the decision
What you get
- Named service owner and documented escalation path
- Agreed scope and responsibility boundary
- Regular operational review
- Change log and configuration history
Related resource
Microsoft 365 AI Security and Governance Checklist
The identity, data and governance controls to verify in your tenant before Copilot and agents are switched on.
Preview the M365 AI Security and Governance Checklist