AI agent readiness check
Seven quick questions to get a rough read on how ready you are to start running AI agents day-to-day. The result is directional, not a verdict — we use it as a starting point for a conversation about where you should actually begin.
What the check looks at
- How you use AI agents today and how documented your workflows are
- Data readiness — whether you know where data lives, who owns it, and how sensitive data is kept separate
- Governance and sign-off — who gets to decide that an agent acts on your behalf
- How you would measure whether an agent actually delivers value
- How often the task runs and how soon you want something live
- Early stage — exploring
- The basics need to land first: which flows benefit from an agent, who owns the data, and who approves. Most teams start here, and a Mindset workshop points out the right first steps.
- Ready to pilot
- You have documentation, named owners, and a task that recurs often enough. A sandbox pilot runs it in a scoped environment, measures the value, and lets you sign off before anything touches production data.
- Ready to build
- You have structure, measurability, and clear urgency. The next step is reviewing what you already have on its way into production — design, controls, and approval chains before you go live.
- Eager — but the team needs enablement first
- Governance and urgency are in place, but what decides whether the agents stick is whether your team can run them day to day. Skillforging equips your people to design, review, and improve agents themselves.
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