AI & automation

Choosing your first AI workflow

A practical way to move from broad AI ambition to one useful, measurable task.

Start with the work

Look for a task your team performs repeatedly and understands well. Search, document review, preparation, and routing can be useful places to investigate. Describe the inputs, output, exceptions, and person responsible.

Know the baseline

Measure the current friction before judging a new approach. Time spent, repeated corrections, and delays are more informative than a broad goal to become more efficient.

Check the information

Find out where the source information lives, how it changes, and who can access it. Inconsistent inputs and unclear ownership can make a promising pilot difficult to operate.

Define a bounded test

Choose representative tasks, including difficult examples. Assess output quality, latency, running cost, source support, and handling of uncertainty.

Keep the next decision clear

A pilot should tell you whether to expand, change direction, or stop. Define that decision before the build so success is based on useful evidence rather than a polished demonstration.

Worked example: incoming document review

An illustrative services team receives documents in several formats. Start by mapping the document types, fields needed for the next step and cases a person must review. Test a bounded workflow that prepares fields and flags uncertainty without making the final business decision. Compare the output with a person-reviewed sample, track corrections and include the time spent reviewing. Continue only if the evidence supports a useful next investment.

A conversation is a good place to start

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