Where should you start with AI adoption?

With a concrete, recurring problem — not with the tech. Pick a process that's frequent, clearly bounded and noticeably costs time today. That becomes your first use-case.

How long does a first AI project take?

A working prototype is often shippable in about two weeks. To full productive use including integration and small iterations, typically a few more weeks.

What's the most common mistake in AI projects?

Starting too big — instead of with a small, clearly bounded prototype. It makes everything more expensive, slower and riskier than it needs to be.

Adopting AI: 7 mistakes almost everyone makes (and how to avoid them)

The uncomfortable truth: most AI projects fail not on technology — but on mistakes you could have avoided from the start. The expensive part: you only notice once the budget is gone. Here are the seven most common pitfalls — and how to get around them.

Mistake 1: Starting with the tech, not the problem

"We want to do something with AI" isn't a goal. Start with a real, annoying problem — the tech is just the means. Remedy: pick one concrete, time-consuming workflow as your first use-case.

Mistake 2: Starting too big

The "AI mega-project" across all departments sounds ambitious and usually fizzles out. Remedy: a small prototype, live fast, measurable value — then scale.

Mistake 3: Postponing data protection

Consider EU hosting and GDPR only at the end and you'll rebuild expensively. Remedy: design with data protection from day one — it's standard today, not an extra.

Mistake 4: Not making success measurable

Without a number up front, no one can say whether it paid off. Remedy: define in advance the time or cost you want to save — and measure afterwards.

Mistake 5: Leaving the team out

The best solution is worthless if no one uses it. Remedy: involve the people who'll actually work with it early — and train them briefly.

Mistake 6: Trusting AI output blindly

AI sounds convincing even when it's wrong. Remedy: add a human approval step for important actions instead of running fully autonomous.

Mistake 7: Choosing the wrong partner

Consultants who only deliver PowerPoint cost time and money. Remedy: choose a partner who actually builds something that runs — and shows it early.

The common thread

Nearly all the mistakes share the same root: too big, too abstract, measured too late. The remedy is always the same — start small, ship fast, measure, then scale. It's unspectacular, but it works.

Conclusion

Adopting AI is no black art once you know the typical traps. Find your right first use-case with the AI use-case check. What to watch for when choosing a partner is in Choosing an AI agency: 7 criteria, and what it all costs is in What does AI software cost?.