Scroll Product Hunt on any random Tuesday and you\u2019ll see that sentence \u2014 give or take a buzzword or three \u2014 pasted onto dozens of glossy landing pages. And investors are taking the bait. Venture capitalists injected $100 billion<\/a> into AI-related startups in 2024 alone, and generative AI specialists nabbed $56 billion of that across just 885 deals<\/a>.<\/p>\n\n\n\n If you\u2019ve actually test-driven many of these tools, you know the dirty secret behind the polished elevator pitches: most are just shiny wrappers around the same public API, offering indistinguishable features at inflated subscription prices.<\/p>\n\n\n\n Instead of a productivity boom<\/a>, we\u2019re getting AI bloat:<\/strong> a swelling stack of “smart” apps that promise gold but deliver pyrite, the “fool’s gold” that tricked many a prospector looking for fortune.<\/p>\n\n\n\n So, as we all navigate the claim-staked valley of AI, we need to recognize many tools for what they are: copy-paste products. We also need to better understand how the race to mediocrity hurts real businesses, and, most importantly, how to pan for the few nuggets that are worth our time (and budget).<\/p>\n\n\n\n Ready to separate fool\u2019s gold from the real deal? Whether you manage a five-product Shopify store or wrangle 500 seats of enterprise CRM, the sifting process is the same. Saddle up and let\u2019s navigate this Wild West together.<\/p>\n\n\n\n It\u2019s tempting to think the app store is full of near-identical AI products<\/a> because founders misread the market. The truth is simpler: the system incentivizes sameness.<\/p>\n\n\n\n Just about anyone can spin up an AI resume writer in a weekend. Here’s all they have to do:<\/p>\n\n\n\n When the raw ingredients are that <\/em>cheap and the recipe that <\/em>repeatable, the number of look-alike dishes on the buffet is bound to explode. Plus, all the existing apps and tools that are adding AI features (whether necessary or not).<\/p>\n\n\n\n Investors see the low cost of entry and sprint in. Global venture funding for AI-related startups broke $100 billion in 2024, which was an 80% jump over 2023<\/a>. Nearly a third of those dollars went to foundation-model companies, the same engines that weekend warriors stitch into their side projects. The result is a layered pyramid of money: big rounds for model builders at the base and thousands of point apps perched precariously on top.<\/p>\n\n\n\n Now, on top of that, add buyers who are afraid of getting left behind. A December 2024 survey<\/a> of 800 C-suite leaders found that 94% of them were dissatisfied with their current AI stack, but 59% admitted to “actively looking” for jobs with companies they considered “more innovative with generative AI.”<\/p>\n\n\n\n One possible way to interpret these survey results: executives know their AI tools<\/a> are broadly disappointing, but they’re still willing to throw time, effort, and budget at them to avoid looking stuck in 2023.<\/p>\n\n\n\n At the other end of the spectrum, AI adoption among U.S. small businesses has jumped 41% in 2025, according to a new survey<\/a>. The results also showed that small businesses often adopt AI tools without a formal vetting process at all, showing that SMBs are also feeling the AI hype, but with even fewer guardrails.<\/p>\n\n\n\nWhy We\u2019re Drowning in AI Tools<\/h2>\n\n\n\n
Low Barriers, Cheap Building Blocks<\/h3>\n\n\n\n
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<\/figure>\n\n\n\nCapital Floodgates Are Wide Open<\/h3>\n\n\n\n
The Corporate FOMO Flywheel<\/h3>\n\n\n\n
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