Most AI projects that fail, fail in predictable ways — the same handful of mistakes, made over and over. The good news: knowing them lets you avoid them, usually at the cheap planning stage. Here are the common ones, and how dgm’s process sidesteps them. (dgm implements osFoundry, a separate company’s platform — we are not osFoundry.)

Mistake 1: Starting from a tool, not a problem

Teams see an impressive demo and build around the product, then work backward to justify it. Start from a business problem and ROI instead, and let technology serve it (see how to build an AI strategy).

Mistake 2: Underestimating data and integration

The model is rarely the hard part — data readiness and integration are. Scattered, messy data and disconnected tools sink projects. Address them early (see how to prepare your data for AI).

Mistake 3: Doing everything at once

The big-bang approach spreads effort thin and risks everything on one launch. Prove one high-ROI use case first, then scale (see how to pick the right AI use case first).

Mistake 4: Skipping change management

A technically perfect system nobody uses delivers nothing. Adoption is engineered, not assumed (see change management for AI adoption).

Mistake 5: Vendor lock-in

Building entirely on one model or vendor ties your economics and roadmap to them. Stay model- and vendor-flexible.

Mistake 6: No ROI baseline

If you don’t capture a baseline, you can’t prove the return — and can’t defend or expand the project (see how to measure AI ROI).

Mistake 7: Over-automating

Using AI where a human (or a deterministic rule) should stay in the loop creates risk. Keep humans in the loop where stakes are high.

Mistake 8: Treating launch as the finish line

AI degrades without upkeep — models change, data drifts. Plan to operate and improve after launch.

How dgm helps

dgm’s process is built to avoid all of these: a $399 assessment (start from the problem, check data), one prioritized use case, data preparation, a pilot, phased scaling, and ongoing operation — with change management and no lock-in throughout, 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 AI done without the common mistakes, that’s where dgm comes in.