Beyond Prompt AI Studio

Applying AI in practice

Identify your own AI-ready processes

Before investing in an AI project, it's worth asking: which process in your business is the best fit for a first test run? Three simple criteria help with the choice.

Four examples – to remember it

Try it yourself: is my process a good first AI pilot?

Rule-based & low-riskHighly variable & high-risk

Possible, but needs oversight

The process varies somewhat or has noticeable consequences if it fails – a pilot can work, but with human spot-checks.

Not every process is equally suited to being first

Your first AI pilot shapes how the whole team thinks about AI in the business afterward. A deliberate choice instead of a random start meaningfully raises the odds of a visible, fast win.

Criterion 1: Does the task repeat often enough?

A process that only comes up once a year is rarely worth the effort – the time saved only adds up with frequent repetition, say daily or weekly.

Criterion 2: How costly is a mistake?

For a process with low consequences if it fails – summarizing an internal note, say – you can experiment freely. For high risk, like legal text or payments, oversight needs to be built in from the start (see module 4, limits and risks).

Criterion 3: Is the information even available digitally?

An AI system can only work with information it can actually reach – emails, PDFs, spreadsheets, systems with an interface. A purely paper-based process with no digitization at all is usually not a good starting point.

Why this matters for you as a decision-maker

A well-chosen, manageable first case with a visible win builds trust for the next steps. An overly ambitious first attempt can do the opposite – and discredit the whole topic of AI in the team for a long time.

Key takeaways

  • Not every process is equally suited to being your first AI pilot.
  • Three criteria help with the choice: does the task repeat often enough, how costly is a mistake, is the information available digitally?
  • A process with low risk and frequent repetition is a good starting point.
  • For high risk (legal, payments), human oversight needs to be built in from the start.
  • Your first AI pilot shapes the team's trust – better to start small and successful than big and risky.

Where does automation actually pay off? Why most ROI math is too optimistic

Quick check: did it land?

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Which criterion most speaks FOR a process as a first AI pilot?

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