Your next steps for agentic transformation

Moving from agent pilots to production-ready, governed agents doesn't require months of planning. It requires focused action on the right things in the right order.

This plan is organized into three phases. Each phase builds the foundation for the next. Use it to move from "we experimented with agents" to "we run agents as a business capability."

Before you start: What to decide first

Before you begin, make three decisions. Without these decisions, the plan stalls.

1. Which pattern are you pursuing? Review the transformation patterns overview and choose one or two patterns that match your current priorities and maturity level.

2. Who is your named owner? For each pattern you're pursuing, name a specific person, not a team, who is accountable for outcomes. This person is your Business Owner. Without a named owner, there's no accountability.

3. What does success look like? Define at least one measurable outcome for each initiative. Don't use "agents are deployed" as the outcome. Use a specific business metric that improves. Write it down before day one.

Phase 1: Foundation

Goal: Understand where you are, decide where to focus, and establish the minimum structures needed to operate.

Assess your current state

• Run the maturity diagnostic across all five capability drivers for each pattern you're pursuing. Take the Agent Readiness Assessment for a guided experience, or use the Agentic AI adoption maturity model as your guide.
• Map your gaps: For each pattern, compare your current maturity to the target maturity profile. Identify the biggest gap—that's your scale-breaker.
• Audit your agent inventory: How many agents exist in your tenant today? Who built them? Who owns them? Are any running in production without monitoring or named owners? This audit often reveals governance risk no one knows about.

Choose your focus

• Pick one or two patterns that match your current priorities and your organization's maturity level.
• Identify one or two agents to take to production in Phase 2. Choose meaningful, lower risk agents where failure is recoverable and learning is visible.

Establish minimum governance structures

Even from the start, some governance is required:

• Define your agent risk classification tiers.
• Establish a named owner requirement. No agent goes to production without a named owner.
• Define your acceptable use policy: what agents can access and what they can't.
• Set up a simple intake form for teams to submit new agent requests formally.

Stand up the CoE seed

You don't need a fully staffed CoE on day one. You need the minimum viable operating rhythm:

• Identify who will cover each CoE role, even part-time.
• Schedule a weekly check-in for the core CoE team.
• Create a shared space for patterns, templates, and guidance.

Phase 1 checkpoint: You can answer these questions:

• What pattern(s) are we pursuing?
• Who owns each initiative?
• What does success look like for each?
• What is our top scale-breaker?
• How many agents are in production today and who owns them?

Phase 2: Stand up

Goal: Deliver agents to production with monitoring from day one, and establish the operating rhythm that sustains governance over time.

Define minimum governance guardrails

Translate your risk tiers into enforceable requirements:

• Tier 1 agents: Named owner, basic monitoring, standard release checklist.
• Tier 2 agents: Named owner plus domain expert validator, knowledge quality monitoring, formal release gate.
• Tier 3 agents: Full governance stack. Learn more in Govern agents by risk.

Document these requirements and publish them to a shared location where makers can easily find and reference them.

Deliver your first agents to production

Choose one or two agents that:

• Align with the pattern(s) you chose in Phase 1.
• Have a named owner and defined success metric.
• Are lower risk, with recoverable failures.
• Can be monitored from day one.

Deploy these agents with monitoring active from the first day in production. Don't deploy and then set up monitoring. The two must go together.

Establish the intake process

Create a formal intake process for new agent requests:

• A submission form that captures: use case, expected value, pattern type, proposed owner, data sources, and expected user volume.
• A triage meeting (weekly, initially) where you assess requests for value, risk, and feasibility.
• A clear response time so agents know what to expect after submission.

Start weekly health checks

For every agent in production:

• Review key health metrics weekly: usage, accuracy, user feedback, escalation rate.
• Address anomalies before they become incidents.
• Log decisions and changes for audit purposes.

Launch enablement for your chosen pattern

• If you're pursuing Employee AI enablement: Launch your first role-based training cohort and establish your champions network.
• If you're pursuing Business expert empowerment: Engage your first domain expert and establish the knowledge curation process.
• If you're pursuing Workplace and IT services: Communicate the new service model to employees and define your SLAs.
• For higher-maturity patterns, ensure business owners have clarity on their governance responsibilities.

Phase 2 checkpoint: You can answer these questions:

• Do we have at least one agent in production with monitoring active?
• Does every production agent have a named owner?
• Does the intake process work? Are requests being triaged?
• Are we running weekly health checks?
• Has enablement started for our chosen pattern?

Phase 3: Scale

Goal: Treat agents as production services, measure outcomes, and decide what to scale next.

Measure outcomes, not just adoption

Usage metrics tell you whether people are using agents. Outcome metrics tell you whether it's working. Report both, but prioritize outcomes. For example:

• Employee AI enablement: Time saved per use case, decision quality, output quality, not just active users.
• Business expert empowerment: Deflection rate, answer accuracy, expert time freed, not just questions answered.
• Workplace and IT services: Resolution time, satisfaction, cost per resolution, not just tickets handled.
• Core business process transformation: Cycle time, throughput, error rate, not just process coverage.
• External engagement: Customer satisfaction, resolution quality, escalation rate, not just interaction volume.

Run your first monthly scorecard

Present the following information to leadership:

• Outcome KPI status for each active initiative
• Agent adoption rate and usage trends
• Reliability metrics: uptime and accuracy
• Risk posture: any governance gaps or incidents
• Cost-to-serve trends
• What's working well and what isn't

This scorecard is the foundation of ongoing governance. Establish the cadence now, even if the data is incomplete.

Review maturity progress

• Has your scale-breaker improved since you started?
• Which capability driver is now the new constraint?
• Update your maturity assessment with what you learned since Phase 1

Decide what scales next

Use what you learned to make deliberate investment decisions:

• Which agents should expand to more users or domains?
• Which initiatives should accelerate with more resources?
• Which agents aren't delivering value and should be retired or redesigned?
• Which new patterns are you ready to pursue, given your improved maturity?

Phase 3 checkpoint: You can answer these questions:

• Are we measuring outcomes, not just adoption?
• Have we run a leadership scorecard?
• Has our scale-breaker improved?
• Do we have a clear view of what scales next, and why?

Common stalls and how to unblock them

Related information

• Choose the right transformation pattern
• Agentic AI adoption maturity model
• Build an agentic Center of Excellence