01
Personal / low-risk
Safe defaults
Approved connectors, personal productivity, limited data exposure.
Operate
Your agents need owners, identities, policies, budgets, and a lifecycle.
The moment AI moves from individual experimentation into production workflows, the operating problem changes. Centered Networks brings agent inventory, identity, security, governance, cost, performance, and continuous improvement into one managed discipline.
The next AI risk is sprawl
More agents do not automatically mean more value.
Agents can be created by central IT, business teams, citizen makers, vendors, or individual enthusiasts. Without an operating model, organizations quickly lose the answers to basic questions.
- What agents are running?
- Who owns each one?
- Which environment is it in?
- What identity does it use?
- What data can it access?
- Which tools and connectors can it call?
- What actions can it take?
- What does it cost?
- How often is it used?
- Is it still producing enough value to justify its existence?
Agent governance starts by making those answers visible.
Guardrails, not gridlock
Different work deserves different controls.
A personal productivity agent should not require the same process as an agent that writes to a system of record or can access regulated data. Centered Networks helps organizations establish practical governance zones based on risk and scope.
02
Department / partnered
Business-owned, IT-supported
Business-owned use cases with IT-supported environments, clearer lifecycle controls, and managed data access.
03
Enterprise / high-impact
Professionally engineered
Formal identity, test and evaluation, release management, runtime monitoring, defined approvals, and accountable ownership.
The goal is to let experimentation happen without allowing production risk to hide inside experimentation.
What gets managed
The operating disciplines
Inventory and registry
Maintain a current view of agents, owners, environments, purpose, connected data, connected tools, and operational status.
Identity and access
Use Microsoft Entra and the appropriate Microsoft agent identity and control mechanisms to scope who or what the agent is, what it can access, and how privileges are reviewed.
Data governance
Use Microsoft Purview and platform policies to reduce oversharing, constrain sensitive-data exposure, and create clear information boundaries.
Runtime security
Use Microsoft security capabilities and platform controls to monitor threats, suspicious behavior, connector risk, and agent interactions appropriate to the workload.
Lifecycle and ALM
Separate development from production, manage changes, test before release, document ownership, and retire abandoned agents.
Cost and consumption
Track AI usage, budgets, ownership, and the relationship between consumption and business output.
Performance and value
Review usage, completion, failure, override, adoption, and business measures appropriate to the agent’s purpose.
AI FinOps
AI spend should become an operating signal, not a surprise.
As agentic work moves toward usage-based consumption, organizations need to understand more than the monthly bill. Consumption tells you where AI is actually working—and where it is quietly accumulating without an owner.
Centered Networks incorporates those questions into Managed Intelligence so cost management and value management happen together.
What you need to know
- Which teams and agents are consuming AI resources
- Where usage is growing
- Whether spend has clear ownership
- How demand should be forecast
- Which guardrails or budgets should apply
- What output or value the spend is buying
Managed AgentOps
Production agents need an after-launch team.
Managed AgentOps is the ongoing operating layer for organizations that want agents to remain secure, useful, current, and accountable after deployment. Typical responsibilities include:
- Inventory and ownership reviews
- Policy and environment governance
- Change and release management
- Incident and exception handling
- Data-access review
- Usage and performance monitoring
- Cost and consumption review
- Agent testing and evaluation
- Adoption support
- Retirement and consolidation decisions
- Executive and board-ready operating reviews
For current scope and commercial terms, see the Managed AgentOps service page.
When you need this
Five signals the agent estate needs an operating model.
You have more agents than anyone can confidently inventory
Start with visibility and ownership.
Multiple teams are building independently
Establish governance zones, environment strategy, and lifecycle rules.
Security wants control and business teams want speed
Design guardrails that distinguish low-risk experimentation from production-critical agents.
AI spend is becoming material
Connect consumption, budgets, usage, and value.
Production agents exist but no one owns the aftercare
Move them into a managed lifecycle.
Bring the agent estate under command before it becomes another tool sprawl problem.
The 90-Day AI Roadmap identifies what is running, who owns it, and which governance moves matter first—before the sprawl compounds.