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AI Adoption·7 min read

Where to Start an AI Opportunity Audit (Without Boiling the Ocean)

Most AI adoption stalls because teams try to automate everything at once. Here's the sequencing we use to find the highest-leverage starting point.

Start with cost, not capability

The instinct in most AI adoption conversations is to start with what the technology can do. That's backwards. Start with where your operating cost is actually going — payroll hours on repetitive tasks, response-time lag that's costing you leads, manual reporting that eats a day a week from someone valuable.

Once you have that list, AI capability becomes a filter, not a starting point. You're no longer asking 'what could AI do here?' in the abstract — you're asking 'does an AI tool solve this specific, already-identified cost?'

Rank by effort-to-payoff, not novelty

It's tempting to start with the most impressive-sounding automation. We rank opportunities instead by a simple ratio: implementation effort versus measurable payoff within 90 days. The unglamorous automations — intake forms, lead routing, report generation — usually win that ranking, and winning early builds the internal trust to tackle bigger initiatives later.

Assign a number to every recommendation

Every item on an opportunity audit should have an estimated hours-saved or cost-reduced figure attached, even if it's a range. Vague recommendations don't survive budget conversations. Specific ones do.

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