Investing in AI without a clear strategy is like buying tools without knowing what to build. In this guide, we share our methodology for helping companies identify where AI creates the most value.

Step 1: Map your processes

Start by mapping your most time-consuming and repetitive processes. Ask yourself: - Which tasks take the most time? - Where do the most errors occur? - Which decisions require the most manual analysis?

Step 2: Assess AI readiness

Not all processes are ready for AI. To succeed, you need: - **Data:** Access to relevant data of sufficient quality - **Volume:** Enough transactions or events - **Measurability:** Clear KPIs to measure success

Step 3: Start small, scale fast

Our advice is always to start with a pilot — a scoped project that can demonstrate value within 4-8 weeks. Once you've proven the concept, you can scale with confidence.

Common pitfalls

Too broad ambitions: Don't try to solve everything at once
Ignoring data quality: Garbage in, garbage out applies to AI too
Lack of buy-in: AI projects without leadership support stagnate

A good AI strategy isn't about using the latest technology — it's about solving the right problem in the right way.