Agent Adoption Lab

A hands-on guide to adopting agentic AI in the enterprise. Play an organization that is new to agents and work through twelve decisions in five phases, from choosing where agents fit to proving they are safe and scaling them. Each step produces part of your Adoption Plan.

Start the journey How the lab works

Decide

Where should agents be used, and why?

Define the value thesis and agent fit
Pick high-leverage use cases and sequence them

You produce: A value thesis and a sequenced use-case portfolio.

Open

Organize

Who owns what, and what may the agent do?

Establish an operating model
Put governance and risk controls in front

You produce: A RACI and an autonomy policy.

Open

Build

What platform, boundaries and knowledge does an agent need?

Build the technical foundation
Engineer for reliability with agent boundaries
Data readiness and knowledge governance

You produce: A platform checklist, boundary settings and a data readiness score.

Open

Prove

Is the agent good enough and safe enough to release?

Evaluation, testing and release management
Security architecture for agents

You produce: An evaluation report and a go/no-go release decision.

Open

Run and scale

How do people work with it, what does it return, and what comes next?

Human integration and change management
Measurement, ROI and cost governance
Scale-out roadmap and capability maturity

You produce: An ROI model and a scale-out roadmap.

Open

Capstone: Incident Response Agent

Does your plan hold up during a real incident?

A production service starts returning 5xx errors. An agent built from your decisions gathers context, proposes a plan and asks for approval, while your policy, boundaries and controls decide what it may do. Then take away the finished Adoption Plan.

Open