How to choose your first AI implementation project

Bring three pieces of unfinished work to your first AI planning meeting. A stack of quote requests, a queue of incomplete orders and a folder of service reports will tell you more than a list of tools. For each, ask the person who does the work to show where time goes and what a good finished item looks like.

Look for work with a clear finish

A good first project has a repeatable starting signal, an accessible source of facts and someone who can recognize a good answer. A company might receive requests to price replacement parts. An agent could extract the part number, check whether the customer provided a quantity and prepare a draft for the estimator. The estimator still owns pricing. The finish line is a complete request waiting in the estimator’s queue.

Compare that with asking AI to “grow our sales.” Different people will picture different deliverables, and the pilot could finish without answering whether the system worked.

Make a decision with actual cases

Take the last ten examples of each candidate. Mark which ones a new employee could complete using written instructions. For the others, write down the additional judgment or information required. A missing part number can become a visible exception. A pricing decision that depends on a conversation nobody recorded is a harder starting point.

Then estimate the cost of checking the output. If reviewing a draft takes as long as doing the original work, try a narrower step. Finding and organizing the supporting documents might save the estimator more time than drafting the quote.

Before committing funds, name the reviewer, agree on one measurable outcome and set a stop condition. For the parts example, track minutes spent preparing complete requests and the number of incorrect part numbers that reach the estimator. Those two measures make it possible to accept the pilot, revise it or move on.

Put this into practice

Bring a sample of the work and the tools your team uses. We can help define a first project, who reviews it, and how to tell if it works.

Explore AI implementation · Discuss your project with Escencion