You know what’s kind of wild? These days, when someone says, “Hey, I think this might be an AI problem,” they’re usually not wrong. That wasn’t the case just 6-12 months ago. AI was still the thing you tagged on a slide deck to sound smart. Now? People have seen it work. They’ve used it. And they’re showing up to the conversation with better questions.
That’s progress.
But it also creates a new risk. People start with “What should we build with AI?” instead of “What would be valuable to solve?” And that’s when things get weird.
A competitor launches a copilot. Your board says the word “automation.” Suddenly, you’ve got a six-week deadline to integrate OpenAI. No plan. No clear outcome. Just duct tape, enthusiasm, and a vague sense of FOMO.
Here’s my advice. Pause. Maybe you do have an AI opportunity. But maybe what you actually have is a leverage problem. Or a workflow problem. Or a growth ceiling you didn’t know you were bumping up against until now.
So let’s say we’re having coffee, and you ask, “We’re thinking about using AI. What should we do first?”
This is where we start.
Start With a Strategic AI Lens
Before you think about tools or vendors, you need to get clear on the impact. Not just impact for your users, but for your business.
Use these four questions to help you explore areas of opportunity:
- How might we use AI to meaningfully change what our product does for the user?
- How might we use AI to evolve how we acquire, activate, or retain users?
- How might we use AI to deepen our moat instead of making us easier to copy?
- How might we use AI to improve how we make money and how much of it we keep?
1. Use Case: Are You Where the Work Happens or Just a Shortcut?
If your product is the place your users go to do the work — their daily cockpit — then AI can enhance that experience. It can give them leverage. Help them move faster. Make better decisions. Help them feel more in control.
But if your product is more of a pass-through or utility, something that aggregates or formats other things, you might be more vulnerable. AI is good at shaving the top off shallow workflows.
Ask yourself:
When AI gets better, do we become more essential or more replaceable?
If your core value is judgment, coordination, or creativity, AI is an amplifier. If your product just summarizes or repackages things, you might be in the blast zone.
2. Growth Model: Will AI Help Us Grow Faster or Just Cheaper?
AI might accelerate your loops. It might reduce costs. But the better question is whether it gives you leverage that compounds.
Let’s say your growth engine is outbound sales. Can AI make reps more efficient and more effective? Great. But if it just lets you blast more generic messages, you’re increasing noise without adding value.
Or maybe your growth is driven by content. AI can help you scale creation, but it can also make you indistinguishable from everyone else doing the same thing.
So ask:
Where can AI give us an edge that others can’t easily copy?
3. Defensibility: If Someone Rebuilt This Tomorrow, What Would We Still Own?
This is where a lot of teams get uncomfortable. If someone cloned your UI and added AI, would your customers stay? Or would they leave for something that looks similar but costs less?
If your moat is just your look and feel or even your data model, that’s not very durable. What’s more durable is deep integration into workflows, proprietary data, and hard-to-replicate distribution.
Ask yourself:
If we stripped away the interface, what would still make us hard to beat?
AI tends to collapse shallow moats quickly. You need to understand what your advantage really is.
4. Business Model: Are We Creating New Value or Reducing It?
This is the one that gets tricky fast.
AI can help you reduce the cost to serve. That’s great. But if it also reduces the perceived value of what you offer, then you have a different problem.
Say you sell insights. AI might let you deliver them faster or in more useful formats. That’s good. But if you sell content or tasks, things AI now does in seconds, your perceived value might drop.
Ask:
When we add AI, do customers feel like they’re getting more? Or does it feel like they’re paying the same for less?
And then ask:
Can we reframe what they’re buying so the AI becomes part of what makes it premium?
In many cases, AI shouldn’t just be a feature. It should change the story.
What Happens Next
When we work through these questions, the conversation always shifts. It stops being about features and becomes about strategy.
Instead of asking “what can we build with AI?”, we start asking:
- What’s the real problem worth solving here?
- Where are we already well-positioned to win?
- How might we turn this shift into something only we can deliver?
And from there, things get clear fast.
Sometimes it leads to a roadmap reframe. Sometimes to a GTM shift. Sometimes, to the realization that the best AI investment right now isn’t a product — It’s operations.
But every time, it starts with those four questions, the Strategic AI Lens.
It’s not a template. It’s not a checklist. It’s just a way to make sure you’re solving for the stuff that actually matters. And it works best before you start stitching together APIs or rewriting your roadmap.
So yeah, maybe you’ve got an AI problem. But more often than not, what you really have is a strategy moment. And AI just happens to be the flashlight that helps you see it.
Let’s dig into it. I’ll bring the coffee.
