Tips

Top 10 for a business deploying AI

Short enough to bookmark and paste into Slack. Each line is the rule. The sentence under it is why.

1

Start with one painful process, not a platform.

Why: A tool with no home in Friday’s work becomes shelfware; a single process with a baseline can prove the idea.

See the first-use-case article
2

Write the “before” number down this week, before anyone logs in.

Why: If you did not measure the old time, error rate, or cycle time, you will not be able to defend the new one.

See the scoreboard article
3

Buy the sanctioned seat before you write the ban.

Why: People are already pasting work into personal chat tools; a usable official option is the only ban that holds.

See the shadow AI article
4

Name what must never be pasted (customer files, passwords, pricing, health or payment data).

Why: Most leakage is a helper trying to finish a task, not a bad actor.

See the shadow AI article
5

Make a person, not “the AI,” accountable for anything that leaves the building or moves money.

Why: Confident wrong answers are a business risk; a named reviewer is the control that actually gets used.

See the process article
6

Train inside the real job, not in a generic prompt class.

Why: People keep habits they practiced on live work and drop habits they only saw in a slide.

See the process article
7

Appoint helpers, not hobbyists, as champions.

Why: Early adopters chase features; champions translate the tool into a coworker’s actual Tuesday.

8

Clean the source of truth for that one process before you automate it.

Why: AI on a messy customer relationship management system (CRM) or a stale knowledge base just produces faster, more confident errors.

See the data-readiness article
9

Count all-in cost (license, setup, training, review, usage), not just the monthly fee.

Why: Firms that cannot see operating cost are the ones that cannot show return, and usage-based spend is easy to miss.

See the scoreboard article
10

Give every pilot a review date and a kill rule.

Why: Stopping a weak use case is how you protect budget and trust for the next one.