AI today feels like stepping into an enormous, undeveloped landscape. Not crowded. Not constrained. Just open in every direction. Opportunity stretches farther than you can see, and that abundance is both exciting and disorienting.
The challenge is not a lack of possibility. It is the opposite. There is so much room to explore AI strategy that it becomes difficult to know where to begin, where to commit, and where to build something that will actually last.
When the landscape is this wide open, indecision becomes the biggest risk. Not because the opportunity disappears, but because someone else eventually chooses a spot and starts building.
Progress does not begin with certainty. It begins with commitment. Homesteads are not built at the perfect crossroads. They are built where the land looks promising enough and the water is close enough to sustain life. Everything else follows.
This is how AI should be approached. You do not need to understand the full map. You need to choose a problem worth solving and plant a flag there. Build something small but real. Something your customers can step into, even if only a few are ready at first.
From those early homesteads, paths start to form. Usage patterns emerge. Feedback creates direction. What felt like an overwhelming expanse begins to organize itself around real value.
The companies that win in AI will not be the ones who explored every direction in theory. They will be the ones who picked a plot, built early, and let the future grow outward from that first foundation.
Building AI agents, workflows, bots, or actions today is like building a rustic log cabin on a 100-acre plot of untouched land. There are no roads. No zoning laws. No neighbors telling you what should exist next door. It is a blank canvas.
That freedom is intoxicating. It is also risky.
If you are a business leader, you need to recognize something important: most of your customers do not want to live in that cabin yet. They are not looking to rough it. They want predictability. Comfort. Reliability.
They want to stay in Marriott or Hilton.
They expect amenities and luxuries. Heated pools, room service, and a continental breakfast. Early-stage AI does not always deliver that experience today.
And that is okay.
Here is the trap many teams fall into: they assume that because AI is early, imperfect, and sometimes unpredictable, they should wait. Sit on the sidelines. Let others experiment. Let the dust settle.
That is a mistake.
If you are running a business, you should not force all your customers to move into the cabin tomorrow. Most of them will not. Some never will. But you absolutely want to own the land.
Owning the land means building now, even if adoption is limited at first. It means giving your most forward-thinking customers the option to rent the cabin. These are the customers who want to experiment, push boundaries, and help shape what comes next.
They will tolerate rough edges. They will forgive hallucinations, data inconsistencies, and the initial limitations that come with the latest and greatest innovations. They will work within data and modeling limits, and ideally they will partner with you to help focus your efforts on where renovations and upgrades make the most sense.
Those early customers will teach you faster than any internal roadmap ever could.
It is important to recognize in your AI strategy that AI technology today hallucinates. It struggles with context. It bumps into data constraints. That is not a flaw. That is a phase. And this phase will pass, quickly.
This technology is self-learning and self-modeling. Every interaction makes it better. Every workflow refines its intuition. Every failure becomes training data.
The log cabin will not stay a cabin forever.
Over time, roads will be paved. Infrastructure will show up. Standards will emerge. What started as raw land will become a neighborhood. Then a suburb showing up with schools, grocery stores, and community norms.
The companies that win the AI era will not be the ones who waited for perfection. They will be the ones who accept imperfection in exchange for learning, leverage, and long-term advantage.
Applying an AI strategy into your product or business today is not about serving everyone immediately. It is about planting a flag. Claiming the acreage. Understanding the terrain before it becomes crowded.
You do not need every customer to move in today.
You just need to make sure that when they are ready, you own the neighborhood.
