AI Over 40 Series - Week 12: The Questions You're Not Asking (And Why That's the Real Problem)

When the breakthrough isn’t finding the right solution—but finally asking why you’ve been living with the problem.

As a Microsoft partner, I’ve spent years asking: What problems can I solve for my clients? I’ve searched for patterns—shared pain points that justify building repeatable, scalable solutions. The challenge? Most clients have learned to live with their problems. And that means I have to.

That realization launched my AI for the Over 40 journey. Before I could help clients solve their challenges, I had to face my own personal transformation before organizational transformation.

But what surprised me most was this: our biggest challenge isn’t identifying problems—it’s noticing the ones we’ve stopped seeing.

The Moment Everything Changed

In Week 10, I shared my contract routing nightmare—copying details from Word documents, pasting into emails, hunting down missing info, manually building distribution lists. It was slow, error-prone, and miserable.

And I lived with it. Because it was “good enough.”

It took hours—not weeks—before I finally built a better solution using Microsoft Forms and Power Automate. The tools were right there, and the pain was obvious. Yet I ignored it until I couldn’t anymore.

That’s the part that haunts me. If I tolerated something that broken for that long, what else am I overlooking?

Why this matters now

Many leaders assume AI agents will “just build it” if they ask nicely. The truth is that understanding AI’s capabilities and limitations—knowing how to craft clear natural-language designs and request iterative code reviews—is where the real leverage lies. Agents can automate routine tasks, but literacy unlocks creative problem-solving at scale.

If we skip literacy and rush to agency, we risk deploying fragile bots that don’t address the core business needs. When everyone around you insists something’s too complex to prototype, your AI-savvy team can prove them wrong.

When the House Is Always on Fire

Here’s the pattern: when one house is on fire, there’s no time to optimize processes. And when one fire’s out, we can always find another to fight.

We spend so much time on urgent issues that we never address the chronic ones—the clunky, frustrating, time-wasting processes we’ve normalized. AI hasn’t just helped me solve problems; it’s helped me see them. AI’s real value isn’t giving you answers—it’s helping you ask better questions. The ones that force you to notice what you’ve been ignoring.

The Meta-Question That Changes Everything

Instead of asking, “Help me find the right problem to solve,” I now ask, “Help me ask the right questions to surface what I’ve stopped seeing.” The problems aren’t hidden—they’re embedded in our daily frustrations, our workarounds, our “that’s just how we do it” excuses. Asking the right questions changes everything.

The Operational Debt Diagnostic

Working with my AI advisory board, I developed a framework for uncovering what I call operational debt—the inefficiencies we’ve learned to live with. Try asking yourself these:

1. What processes embarrass you when training others? If you ever say, “I know this seems inefficient, but…,” you’ve found operational debt. Embarrassment is the tell.
2. What do you do manually every week that makes you think, “There has to be a better way”? You probably dismiss the thought because fixing it feels too expensive or time-consuming. But with AI, exploring solutions costs hours—not thousands of dollars.
3. What information have you given up on ever having? For us, that was visibility into whether client review meetings were actually addressing strategic goals. With a little AI help, we used Forms, Power Automate, and Dataverse to fix it in hours—and immediately improved our client conversations.
4. What depends entirely on who’s doing it rather than how it’s done? If things fall apart when someone’s on vacation, you’re relying on tribal knowledge, not systems.
5. What would you never recommend another company do your way? If you wouldn’t advise someone else to copy your process, that’s a clear sign of operational debt.
6. What problems have you stopped calling problems? When “that’s just how we do it” replaces “this isn’t working,” you’ve normalized inefficiency.

Why This Matters Now

The economics have changed. Fixes that once required expensive consultants or custom development can now be built with AI in a few focused hours. But only if you notice the problems in the first place.

AI doesn’t just automate solutions—it helps you see where you’ve been living with dysfunction and calling it normal.

Your Week 12 Challenge

Answer these questions honestly. Write them down. Then, bring your most uncomfortable answer to your AI advisory board—not with “solve this for me,” but “help me understand why I’ve been living with this.”

1. The Embarrassment Test: What processes are you embarrassed by when training others?
2. The Weekly Frustration Test: What manual tasks make you think “there has to be a better way”?
3. The Accepted Limitation Test: What information have you given up on ever having?
4. The Person-Dependent Test: What falls apart when specific people are unavailable?
5. The Professional Standard Test: What would you never recommend others do your way?
6. The Normalization Test: What problems have you stopped calling problems?

The real transformation isn’t technical—it’s psychological. AI helps us ask the questions that reveal what we’ve accepted for too long.

Stop looking for fires to fight. Start asking why you’ve accepted living in a burning building.

This post is part of my “AI Over 40” series. It first appeared on LinkedIn: AI for the Over 40 [Week 12]: The Questions You’re Not Asking (And Why That’s the Real Problem.

Next Up: We’ll explore more stories of pursuing AI literacy before agency and personal transformation before organizational.

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