Stop Chasing the Cheese: How to Avoid AI Overwhelm

Every day (literally) there’s a new AI model announced. Some are big deals (DeepSeek anyone?) while others are blips. But the pace of new releases, each showcasing eye-popping new capabilities of varying degrees, is intense.

The accepted wisdom in AI circles to this point has been, Just try out as many tools as you can; you won’t understand what AI is (and isn’t) capable of unless you try everything out.

I’m starting to think this isn’t good advice. There’s such an arms race going on at the big tech companies that it suits their needs to have us all running from model to model like mice constantly chasing the moving cheese. But it doesn’t suit your needs—the marketing leader, strategist, or business executive trying to pin down exactly how (and if) AI technologies can help you.

I was chatting with a friend the other day who is a CMO at a pediatric hospital. She’s a very savvy marketer who’s on top of the latest news and trends in AI, yet even she admitted that all of this can be a little crazy-making. "With the rate of speed at which all of the AI tools are evolving, [identifying the right AI tools to use] is like trying to hit a moving target."

This is someone who’s highly strategic, on top of AI trends, and investing serious time, energy, and money into AI adoption. And even she’s unsure if she’s making the right choices.

No wonder so many people are feeling AI paralysis.

So what’s an AI-curious professional to do? To some degree, I think you have to pick a lane and stick with it. Don’t chase every new release. Instead, make an intentional choice:

✅ Identify platforms that are highly capable.
✅ Invest time in learning them deeply.
✅ Maximize their value before jumping to the next shiny thing.

As we saw this week when OpenAI released its “deep research” product (as opposed to, you know, Google’s “Deep Research” product, which was released late last year), the models from the big players are increasingly offering similar functionality. That doesn’t mean that one model doesn’t do a certain thing better than another, but for the average user, these tools are already far beyond what they actually need.

This also applies to AI tools you might bring into your business. AI can make you more effective and efficient—but only if you focus.

I’ve said this before, but it bears repeating: Start small.

1. Identify specific problems you need to solve.
2. Find AI tools that claim to solve those problems.
3. Conduct a pilot—test them in real workflows.
4. If a tool works, expand its use. If it doesn’t, move on.

And one more thing: AI tech companies will try to get you into a long-term contract. Don’t let them. Things are moving too quickly to make significant commitments to tools that haven’t proven effective for you yet.

It is very easy to get swept up in the AI hype and to feel alternately on top of the trends and hopelessly behind them. I’m advocating for stepping off the madly spinning carousel and focus on a couple specific tools that will actually help you. Let big tech keep fueling the hype cycle. You don’t have to chase the cheese.