How would you improve adoption of an AI feature inside a company?

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ANSWER MODE

WRITTEN ANSWER

### Signal to interviewer

I can grow enterprise AI adoption by coupling change management with product integration and measurable workflow outcomes.

### Clarify

I would clarify target teams, mandatory versus optional usage context, current process pain, and leadership sponsorship level.

### Approach

Build an internal adoption flywheel: embed in core workflows, activate champions, share wins, and iterate enablement by function.

### Metrics & instrumentation

Primary metric: weekly active adoption in prioritized workflows. Secondary metrics: repeat usage depth, task completion acceleration, and champion-driven expansion rate. Guardrails: policy violations, low-trust feedback, and support burden per active team.

### Tradeoffs

Wide launch increases awareness but can create shallow usage. Focused launch improves depth but may appear slow to stakeholders.

### Risks & mitigations

Risk: tool switching friction; mitigate with native integration. Risk: manager skepticism; mitigate with team-level ROI snapshots. Risk: abandoned pilots; mitigate with adoption milestones and ownership.

### Example

In finance operations, AI is embedded in month-end variance analysis with champions sharing before/after cycle-time improvements.

### 90-second version

Improve company adoption by anchoring AI in real workflows, proving value with measurable outcomes, and scaling through local champions rather than top-down mandates.

FOLLOW-UPS

Clarification

Which internal workflow should be the first adoption beachhead?
How will you define meaningful active usage versus superficial clicks?

Depth

How would you design a champion program that scales across departments?
What telemetry proves adoption is driving productivity, not novelty?

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