Scaling AI across a company is where many initiatives stumble — usually by trying to do it all at once. The companies that succeed phase the rollout: prove, then expand, then scale. Here’s how, and how dgm does it. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry.)
The phased approach
- Prove one use case. Start with a high-ROI use case — pilot it, then take it to production. This is your evidence and your template.
- Expand to adjacent use cases. Move to use cases that share data, workflows, or teams with the first — you reuse what you built and learned.
- Scale across teams. Roll the proven patterns out more broadly, team by team.
Never a company-wide big-bang — that’s the approach that fails.
Why phasing works
Each phase builds evidence, savings, and adoption that fund and de-risk the next. You prove value early (rather than waiting for a distant launch), build internal confidence, and can adjust as you learn. Big-bang rollouts spread effort thin, delay results, and bet everything on one launch that often slips or lands flat (see AI implementation roadmap).
Each phase is an adoption checkpoint
Scaling a system people aren’t adopting just spreads the problem. So treat each phase as an adoption checkpoint — involve the users, train them, prove value, and measure adoption before expanding (see AI change management playbook). Change management runs through every phase, not just the first.
How many phases?
As many as it takes to go from one proven use case to your target scope — one sensible step at a time. There’s no magic number; the principle is that each phase is small enough to deliver and prove, and builds on the last. Quality of each step beats a set count.
How dgm helps
dgm rolls out AI in phases — a proven first use case, then adjacent expansion, then scaling what works — with training and adoption built into each phase, at $3,999/month after a $399 assessment. Phasing is how dgm de-risks and scales AI across a company. If you’d rather explore the platform yourself first, go straight to osFoundry; if you want a rollout that scales without disruption, that’s where dgm comes in.