Nobody agreed what success means
A pilot built to explore AI has no finish line, so nobody can say whether it worked. Pick one number before you start: hours saved, errors avoided or turnaround time. If the pilot moves it, you have a case for going further. If it doesn't, you've learned that cheaply.
It was tested on clean data
Demos run on tidy examples. Your business runs on scanned invoices, half-filled forms and customers who write three questions in one email. Test on real examples from your own work, including the awkward ones, and measure how often the answer is right.
It isn't connected to anything
If someone has to copy text into a chat window and paste the answer into your CRM, the tool adds a step instead of removing one. Most of the work in a production system is the connection to the tools your team already uses, along with permissions and error handling. Plan for it from day one.
People don't know when to trust it
Teams stop using a tool when one bad answer embarrasses them and they can't tell when it will happen again. Decide which decisions a person must review, show where each answer came from, and make it easy to correct a mistake.
Nobody owns it after launch
AI systems change as your data, your processes and the underlying models change. Name the person responsible for quality and cost, and give them a way to see both.
Before you start your next pilot
- What number should this move, and by how much?
- Have we tested it on real and messy examples?
- Which systems does it need to read from and write to?
- Which decisions does a person still review?
- Who owns it once it's live?
If you can't answer these yet, that's the first job, and it costs far less than a pilot that goes nowhere.