Strategy2 min read
Do not start with AI. Start with what slows your team down.
A simple framework to find a useful opportunity without automating for the sake of it.
By the team at Daleki Lab
Watch one task from start to finish
Adopting AI starts with understanding real work. Choose a process that repeats, has a clear owner and lets you describe what doing it better would look like. It could be answering inquiries, preparing proposals or finding internal information.
Look at where time is lost, where errors repeat and which decisions require experience. Not every problem needs an AI model: sometimes it is enough to fix a form or connect existing tools.
Weigh value, data and risk
An attractive opportunity combines a meaningful benefit with usable information and a risk you can control. High volume is not enough if the data is incomplete or if every error has consequences that are hard to reverse.
Compare opportunities with the same questions: who benefits, what information is needed, what action can the system take, and when should a person step in? The answers let you prioritize without depending on the tool of the moment.
Define how you will know it works
Before the pilot, document how the process runs today. Depending on the case, you can track time per task, errors, response quality or number of revisions. You do not need to promise an improvement percentage to define a useful measurement.
Test the first version with comparable situations and keep its limits visible. An early result does not prove it will work the same at full volume or with cases you have not tested yet.
Leave a human way out
Every automation needs a way to stop, be corrected and escalate an exception. Define owners and permissions from the first stage, especially when there is sensitive data or actions on third party accounts.
Our recommendation is to start with a scope you can review and expand with evidence. The best first solution is the one your team understands, can use and knows when it should stop running.
