Which business process should you automate with AI first?

Name the business outcome before the technology

“We need an AI agent” is a starting conversation. “Our account managers spend two days assembling every renewal brief” is a business problem you can investigate.

Describe the process in one sentence: when this input arrives, these people perform these steps to produce this accepted result. Include the handoffs. The opportunity often sits between systems, where people gather context, copy information, chase an approval, or check whether work is complete.

Then ask what a better result would allow the business to do. It might respond to customers sooner, handle more contracts without another queue, or let specialists spend more time on decisions. A faster technical step matters when it improves that whole outcome.

Look for recurring work with information friction

These are useful places to investigate. Their suitability depends on your data, systems, permissions, and review requirements.

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These categories are established automation opportunities, not evidence of a particular return. For example, UiPath describes invoice automation around finance workflows. Your discovery work still needs to establish what is feasible in your environment. Explore our concrete transformation opportunities for more examples.

Use a scorecard to expose the tradeoffs

First confirm the metric: which existing business KPI would improve, who owns it, and where is the baseline recorded? A process without measurement may need instrumentation before you can make a credible investment decision. Then score each candidate from one to five on the following dimensions. One means weak or unknown; five means strong and supported by evidence. Treat the score as a conversation aid, not a mathematical prediction of success.

1. Business value. Is the volume, cost of delay, or capacity constraint material? Can the process owner explain the consequence?
2. Input readiness. Can you access representative documents and the relevant context with appropriate permission?
3. Outcome clarity. Can a reviewer distinguish an acceptable result from a plausible but wrong one?
4. Integration readiness. Is there a supported way to read and update the systems involved?
5. Ownership and adoption. Will a named business owner provide examples, review outputs, and help the team change how it works?

Assess risk separately. A high total score should never cancel out an unacceptable consequence of error. An invoice preparation workflow that retains payment approval is a different proposition from a system that can initiate payments independently.

NIST’s AI Risk Management Framework organizes risk work around Govern, Map, Measure, and Manage. Use that structure to make responsibilities and review decisions visible. It is a voluntary framework, not a certification earned by adding a checklist.

Choose the smallest complete workflow

A useful first scope reaches an accepted outcome. “Extract text from a PDF” may leave most of the manual work untouched. “Receive one document type, validate the required fields, attach the source, obtain approval, and update one system” has a clearer business boundary.

Keep variation manageable: one intake channel, one category of work, one destination system, and a defined reviewer. Choose enough scope to test the real handoffs while keeping the dependencies understandable.

Use AI where language, context, or unstructured inputs create the difficulty. Keep predictable rules and calculations explicit. Anthropic’s workflow and agent guidance supports starting with simple approaches and adding complexity when it improves the outcome. You do not need the most autonomous architecture to create a meaningful change.

Turn the shortlist into a decision you can defend

Before implementation, gather a representative sample and map the current process with the people doing it. Record normal cases, missing information, edge cases, and the decisions that need judgment. Separate examples used for development from the cases used to assess quality.

Set acceptance criteria across speed, quality, cost, and human review. For a contract workflow, faster preparation is useful only if the required terms are captured accurately and material exceptions reach the right person. Have the business owner decide what errors matter and how reviewers will handle them.

Compare your top candidates using a consistent ROI model, then take a bounded investment request to the sponsor. Our example business case shows how scope, dependencies, human approval, and evaluation fit together. That is the starting point for a process your team can trust and a result your leadership can assess.