AI is everywhere. You can’t escape it.
As someone who builds smart bots for a living, I’ve got my hands in the code, the architecture, and the actual implementation. I see what AI can do, and I see where it’s still… well, not quite there. Lately, it feels like a lot of companies are caught in an AI fever dream, throwing resources at anything with “AI” in the title without a clear understanding of what they’re truly trying to accomplish.
In 2026, the sheer volume of companies using AI is staggering. The U.S. alone shows incredible entrepreneurial energy, with over 1,900 newly funded AI firms. That’s a lot of new players, all hoping to strike gold in the AI space. But are they all making sound decisions? Are they all building something truly useful, or are some just chasing the hype?
The AI Gold Rush
It’s easy to get swept up. Every major player is pushing AI further. Google’s Gemini now helps with shopping. NVIDIA released an advanced AI computing platform. Samsung expanded AI capabilities to millions of devices. These are real advancements from companies with deep pockets and serious research departments.
Yet, PwC’s 2026 business predictions note that only a few companies are actually realizing extraordinary value from AI. We’re talking about surging top-line growth and significant valuation premiums. This suggests a significant gap between the widespread adoption of AI and the actual business benefits many companies are seeing. For every success story, there are likely many more pouring money into projects that aren’t yielding the expected returns.
“Death by AI” Claims
The dark side of this enthusiasm is also starting to emerge. Gartner predicts that by the end of 2026, there will be more than 2,000 “death by AI” legal claims. This isn’t just about technical glitches; it speaks to a broader issue of responsibility and oversight. If a company’s AI system causes harm or makes a critical error, who is accountable? This growing number of claims indicates a rush to deploy without fully understanding the ethical, legal, and operational risks involved.
From my perspective, building a smart bot means understanding its limitations just as much as its strengths. It means anticipating potential failures and building in safeguards. Are all these newly funded AI firms doing the same? Are the established companies moving fast enough to address these concerns?
Beyond the Hype Cycle
For those of us building the actual tools, the focus remains on practical application. We’re looking at how AI can genuinely improve processes, automate tasks, and create new experiences. My work at ai7bot.com focuses on tutorials, code, and architecture for smart bots. We care about the “how” and the “why.”
AI can assist with business and management tasks including marketing, sales, finding capital, and managing people. There’s real value there. But achieving that value requires more than just slapping “AI-powered” on a product description. It demands a solid understanding of the underlying technology, careful implementation, and a clear strategy for how AI will solve a specific problem.
The sheer number of newly funded AI companies, especially in the U.S., is a testament to the belief in AI’s potential. But the “death by AI” claims and the limited number of companies seeing extraordinary value tell another story. It’s a story of companies perhaps getting caught up in the fervor, rather than approaching AI with a clear, measured strategy.
As builders, we have a role to play in educating and guiding. The goal isn’t just to build AI; it’s to build smart AI, applied thoughtfully, with an eye toward real value and accountability.
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