The Monday Morning Problem: How to Turn AI Curiosity Into Lasting Behavior Change

The simple practice routine that turns impressive demos into measurable time savings and better work

TL;DR: I’m delivering an in-person AI training tomorrow for a 250-person company, and it got me thinking about my philosophy for training and how to make it stick for organizations with wildly different backgrounds and skillsets. Some thoughts.

How to kickstart real AI adoption across your company

There’s a moment in every training where the room goes quiet. People see the demo, they’re impressed, and then they ask, “OK, but what do I do on Monday?” That pause is the gap between curiosity and new behavior. Close it and AI sticks. Miss it and you’re back to business as usual by next week.

Here’s the short version. You get people moving by lowering the bar to start, raising the ceiling over time, and giving them a safe place to try, fail, and try again. Teach the basics. Show relatable use cases. Make mistakes normal. Wrap it in simple guardrails so people know what’s OK to ship and what needs a second set of eyes. And yes, invest in strong tools and protected practice time so progress doesn’t stall.

Start with a shared foundation

If people don’t understand what the tools can and can’t do, they either underuse them or overshare junk. I start with three ideas in plain English. One, context windows are the AI’s working memory, so keep files tidy and set instructions once. Two, some jobs need thinking time while others need speed, so pick the right mode for the task. Three, hallucinations happen, so treat the model like a brilliant intern who can’t say “I don’t know.”

From there, we set five rules before anyone shares AI output with a client or the company:

1. Always verify important facts.

2. Add real context: audience, goal, constraints.

3. Iterate, don’t ship the first draft.

4. Humans make the final call.

5. Use the right tool for the job.

We keep these on a single slide and repeat them until they’re muscle memory.

Make it hands-on and low risk

Adults learn by doing. So give them safe, routine reps. Ten minutes at the top of recurring team meetings for “one small thing with AI” wins hearts. Sales tries call prep. Finance rewrites a monthly narrative with clear variances. HR turns a policy paragraph into a plain-language version and checks it against the original. Each rep shows time saved and quality improved. The work speaks.

And normalize mistakes. Create a channel called “AI tries” where people post wins and flops. Praise the practice, not just the polished output. When it’s OK to fail, usage climbs.

Give them real tools and real time

Free trials are good for demos, not for change. If you want daily use, give people access to at least two top models so they can compare strengths, plus a place to work with files and persistent instructions. Think ChatGPT, Claude, and Gemini as a practical starting trio. Turn on audit logs, publish sharing rules, and assign a couple of internal coaches who hold office hours.

Time matters just as much as licenses. If people can’t spend 90 minutes a week practicing in their own workflow, adoption plateaus. Put it on calendars and defend it like a client meeting.

Use cases that spark imagination

Don’t start with sci-fi. Start with the work they already do: email and message drafting in the right tone with red-flag checks; meeting prep and follow-ups that extract decisions and owners; first-pass analysis of a spreadsheet with two charts and plain-English captions; document clean-ups that shorten by 20 percent without losing meaning; research briefs with citations that a human skims and corrects. Each example should take 5 to 10 minutes live. That matters. People need to see “I could do that today.”

Make it concrete: a 30-day practice plan

Use this with your whole company. It’s simple, it’s paced, and it works. It’s also how I close training so people leave knowing exactly what to do next.

1. Week 1: Start small
   Summarize two long emails or documents, draft two routine emails and edit them, and brainstorm for one upcoming meeting or project. Keep it to 10–15 minutes a day. The goal is comfort, not perfection.

2. Week 2: Make it routine
   Begin the day by asking AI for your top three priorities. During work, use AI for one repetitive task, then end the day by having AI create tomorrow’s task list from today’s notes. Plan for 20–30 minutes a day. You’re building the daily habit.

3. Week 3: Go deeper
   Create one custom helper (a saved prompt, a small agent, or a template) for a task you do weekly. Use AI to analyze a dataset or research a complex topic. Upload a long document and have a conversation with it. Practice iterating when the first output isn’t great. Aim for 30–45 minutes a day.

4. Week 4: Share and scale
   Share one successful prompt with your team. Track time saved on at least three tasks. Teach one colleague something you learned. Identify your next use case for Month 2. Keep the 30–45-minute cadence.

Remember: you don’t need to be perfect. Every prompt is practice. Every weak output teaches you something.

What changes when you do this

Quality goes up because people write and think with a partner. Speed goes up because boilerplate disappears. Morale goes up because the annoying parts of work shrink. Leaders get visibility into where the time is going, which prompts are working, and which teams need another round of coaching.

There are tradeoffs. You will ship a bad AI draft once in a while. You will buy the wrong tool for a few seats until usage patterns settle. You will say “no” to risky use cases early on. That’s fine. The point is momentum with controls, not perfection.

Think of this like starting a gym routine across the company. Day one is light weights. By week four, people are adding plates and comparing notes. By quarter two, the wins stop being novelty and start being the way you work.

Crawl. Walk. Run. Then keep going. Make it normal. Make it safe. Make it daily.

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Business leaders are drowning in AI hype but starving for answers about what actually works for their companies. We translate AI complexity into clear, business-specific strategies with proven ROI, so you know exactly what to implement, how to train your team, and what results to expect.

Contact: steve@intelligencebyintent.com

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