Is AI the New Spellcheck?

It’s 2025, and if your AI works, congratulations—you’ve met the bare minimum. The fact that your AI is functional, effective, and produces the expected results is no longer a differentiator. It’s table stakes.

We’ve seen this play out before. Think about spellcheck. In the early days, spellcheck was a game-changer, revolutionizing how we wrote and edited documents. But now? It’s just expected. Either it works, or it doesn’t. Is Google’s spellcheck slightly better than Microsoft’s? Maybe. I know from personal experience that Google often figures out what I’m trying to type even when Microsoft is completely lost. But at the end of the day, the difference between the two isn’t significant enough to change how I work. They both accomplish the fundamental goal of correcting spelling mistakes, and that’s all that really matters.

AI is heading in the same direction. A well-built AI will work—and it will work dramatically better than manual processes. The difference between AI models will, of course, exist, but most of those differences will be marginal. A chatbot that is 5% more accurate than another, an AI-powered sourcing tool that finds candidates 8% faster, or an automated interview solution that generates slightly better insights—these improvements aren’t enough to create meaningful market differentiation anymore.

So if AI alone isn’t enough to make a product stand out, what is? The answer lies in execution, implementation, and customer success.

• Elegance of the Product – The way the AI is integrated into a seamless, intuitive user experience matters more than the AI itself. A clunky, disjointed interface can kill adoption, no matter how good the underlying model is.
• Implementation & Support – The companies that win won’t just throw AI into the mix and hope for the best. They’ll ensure smooth implementation, make integration seamless, and provide hands-on support to drive adoption.
• Continued Improvement & Adoption – AI is not a one-and-done solution. Success will come from how well companies refine and optimize AI based on real-world usage. That means regular updates, adapting to customer needs, and ensuring that users actually get value from the tool long after the initial sale.
• Unified Platforms Over API Patching – Too many AI products today are just a patchwork of different tools connected by APIs. Companies that build true platforms—ones with a common middle tier, a unified messaging layer, and a seamless customer experience—will outlast those that are simply bundling various AI features together.  This is a hard argument to make with investors because it doesn’t bring returns tomorrow, it is the long game.
• Customer Success as a Core Strategy – The companies that prioritize customer success—those that actively measure adoption, track utilization, and ensure AI is driving real business value—will win. The best AI won’t save a product that customers don’t know how to use or don’t see value in.

While big AI companies battle for market share by layering on complexity, a new class of businesses is emerging: the profitable small AI business.

These will be  lean, 1-3 person companies that create AI-driven products, gain a solid customer base, and sustain a comfortable, profitable business—without raising millions in venture funding or chasing exponential growth.  I am hearing from two or three such companies each week.

Instead of navigating investor pressure and the relentless push for scale, these businesses will stay small, nimble, and laser-focused on solving one or two very specific use cases exceptionally well. With minimal overhead and simple, effective products, they’ll carve out a space in the market that large AI companies struggle to reach.

Meanwhile, bigger AI players, driven by investor expectations, will continue adding layers of features, complexity, and integrations in search of ever-higher returns. These small AI businesses, by contrast, will offer customers exactly what they need—without the bloated software, endless updates, and sky-high subscription fees.

In many ways, they will become a thorn in the side of larger companies that are weighed down by massive overhead, bureaucracy, and the need to chase ever-growing returns. Their ability to stay lean and focused will be their superpower.

Too many companies in the AI space think that having a working AI solution is enough. It’s not. AI is becoming a commodity, just like spellcheck. If you’re not thinking about user experience, implementation, support, and long-term adoption, you’re going to lose—no matter how good your AI is.

And for those who want to build something truly impactful, bigger isn’t always better. The AI revolution is creating space not just for giants, but for small, smart, and sustainable businesses that prioritize profitability over scale, simplicity over complexity, and value over hype.

The game has changed. The question is, has your company changed with it?