How to Prioritize Enterprise AI Use Cases
The best first use cases are not necessarily the most impressive. They combine a meaningful problem, accessible evidence, manageable risk, and a team prepared to change the workflow.
Define the unit of value
Avoid scoring vague ideas such as “use AI in customer service.” Define a specific decision or workflow: summarize a case before handoff, draft a response using approved knowledge, identify missing documentation, or route a request to the right team. A narrow operating statement makes value, data, users, and failure modes visible.
Estimate value using a small set of measures: cycle time, avoidable effort, conversion, quality, experience, risk reduction, capacity, or revenue. Use ranges and explicit assumptions instead of false precision.
Score feasibility and risk separately
Feasibility should consider data access and quality, integration difficulty, model capability, evaluation design, security, process stability, and owner availability. Risk should consider potential harm, affected populations, data sensitivity, autonomy, reversibility, regulatory exposure, and reputational consequences.
Keeping these dimensions separate matters. A technically easy use case may be high risk, while a valuable low-risk opportunity may need difficult integration. The portfolio should show those tradeoffs rather than hide them in a single score.
Select a portfolio, not a winner
Balance quick operational improvements, strategic capability builders, and a limited number of higher-uncertainty bets. Include at least one initiative that builds reusable infrastructure or governance, even if its immediate value appears indirect. Avoid launching many pilots that compete for the same data owners and subject-matter experts.
Re-score after discovery and again after a pilot. The purpose of a pilot is to reduce uncertainty. A disciplined organization stops weak ideas, expands proven ones, and records what it learned so the next selection cycle improves.
Leadership checklist
- Describe each use case as a specific workflow or decision.
- Score value, feasibility, risk, and adoption independently.
- Include evidence requirements and a named owner.
- Stop or rescope initiatives when pilot evidence does not support scale.