Most failed AI initiatives were predictable — the warning signs were visible before a dollar was spent. A good adoption checklist surfaces them early, when they’re cheap to fix. Here’s the checklist, and how dgm works through it. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry.)

Before you start: readiness

During: build it right

  • Integration plan — how AI connects to your real systems and workflows.
  • Governance and security — access controls, human oversight, and any compliance requirements.
  • Model and vendor flexibility — avoid lock-in.
  • A pilot with real users and clear success criteria (see how to run a successful AI pilot).

Around it: people and measurement

The items teams skip (and shouldn’t)

Three checklist items quietly sink projects: data readiness, governance, and change management. They’re less exciting than the tool, so teams skip them — then discover the data isn’t usable, there’s no oversight, or no one adopts the system. Don’t skip them.

Use it to start small

The checklist should lead you to one high-ROI use case, proven before scaling — not a company-wide big-bang launch. Phased adoption, guided by the checklist, is how AI actually succeeds.

How dgm helps

dgm runs this checklist as part of its $399 assessment — readiness, first use case, integration, governance, change, and measurement — then implements at $3,999/month with no per-seat fees. If you’d rather explore the platform yourself first, go straight to osFoundry; if you want the checklist worked through and delivered, that’s where dgm comes in.