Many companies have tested a chatbot or two, but few can say what AI has changed in their figures. The problem is rarely the technology. It is the lack of a method for choosing where AI should go first.
Week 1: list the time sinks
Spend thirty minutes with each team. Ask which tasks are repetitive, which ones create errors and which ones slow customers down. You will quickly collect twenty to forty candidates.
Week 2: score value and effort
For each candidate, estimate the hours saved per month, the impact on revenue or quality, and the effort involved: available data, systems to connect, risk if the AI gets it wrong. Keep the five with the best ratio.
Week 3: prove one use case on real data
Build a small proof of concept for the most promising candidate, using your own documents and data. What you are after at this stage is evidence: does it work on your cases, and how often?
Week 4: decide and plan
With real results in hand, decide what to build, buy or drop. Write a short roadmap for the next six months, with a budget and a success measure for each step.
Do not forget the people
- 01Give each use case an owner on the business side
- 02Set simple rules for using AI tools and company data
- 03Train the teams who will work with the new tools
We run this exact process with companies of every size. A free audit is a good way to cover the first week.