The AI industry has received over $100 billion in venture funding since 2022. That money has produced more than 10,000 AI startups globally. And if you ask a normal person, not a tech worker, not a VC, just a regular person, to name AI products they use regularly? You'll get maybe three answers. ChatGPT. Maybe Copilot if they're a developer. And then a long pause. That's the uncomfortable truth nobody in Silicon Valley wants to confront. The AI revolution has produced remarkably few products that people actually use. Not "downloaded once," not "tried during the free trial," not "signed up for because their boss told them to." Actually use. Weekly. Because it makes their life better. I've been tracking this for six months. Analyzing usage data, churn rates, public metrics, and app store rankings. Here are the five AI products that have genuinely broken through, what makes them different, and the painful lessons from the 50+ that haven't. ## The Five That Won **ChatGPT** is the obvious one. OpenAI reported over 400 million weekly active users as of early 2025, making it the fastest-growing consumer application in history (a record it already held, hitting 100 million monthly users in January 2023, just two months after launch). Revenue crossed $5 billion in annualized run rate by the end of 2025. What makes ChatGPT work isn't the model quality, though that matters. It's the interface simplicity. Open a browser, type a question, get an answer. No setup. No configuration. No "prompt engineering" required. Your grandmother can use it. And increasingly, she does. The product succeeded by feeling like a conversation, not like software. ChatGPT also benefits from what I call the "default effect." It was first. It became the generic term for AI chatbots, the way "Googling" became the generic term for searching. When someone says "ask AI," they mean ChatGPT. That brand position is nearly impossible to dislodge. **GitHub Copilot** is the second clear winner. Microsoft reported over 15 million users by late 2025, with paid subscribers growing every quarter. At $19/month for individuals and $39/month for business, it generates meaningful revenue, well over $1 billion ARR by most estimates. Copilot works because it's embedded in the workflow. You're already in VS Code. You're already typing code. Copilot just... helps. There's no context switch, no separate app to open, no prompt to craft. It watches what you're doing and suggests the next few lines. Accept with a tab key. Reject by ignoring it. The interaction model is so frictionless that developers forget it's there, until they try coding without it. The retention data tells the story. Developers who use Copilot for a week rarely stop. It's not because the suggestions are always right. Maybe 30-40% of suggestions get accepted verbatim. But the ones that stick save enough time that going back feels like giving up spell-check. **Midjourney** defied every prediction. A small, independent team with no venture funding and no API, running entirely through Discord of all places, built the dominant AI image generation tool. Estimated revenue crossed $300 million annually, with a team of roughly 40 people. That's $7.5 million in revenue per employee. Most SaaS companies would kill for those numbers. Midjourney won on quality and community. The images look better than DALL-E's or Stable Diffusion's, at least for the aesthetic styles that most people want: photorealistic scenes, fantasy art, design concepts. The Discord-first approach built a community of creators who share techniques, critique each other's work, and push the product forward. Midjourney's users are more like fans than customers. The business model is also brilliantly simple. $10-$60/month depending on the tier. No free tier. No ad-supported option. If you want Midjourney, you pay for it. And people do, because the output is good enough to be worth money. **Perplexity** cracked something nobody thought was possible: competing with Google on search. The AI-powered answer engine hit $100 million in annualized revenue by early 2025, a figure that would have seemed laughable for a search startup two years earlier. Their Pro plan at $20/month has strong retention, and they're growing usage by roughly 20-30% quarter over quarter. Perplexity works because it answers questions instead of listing links. For specific, fact-based queries, "What's the population of Osaka?" "When did Apple release the M4 chip?" "What's the current Fed funds rate?" Perplexity gives you the answer with sources. No clicking through ten blue links. No scrolling past ads. Just the answer. The "with sources" part is critical. It's what separates Perplexity from asking ChatGPT the same question. ChatGPT can hallucinate. You know this. Perplexity shows you exactly where each claim came from, so you can verify. For research, journalism, and knowledge work, that traceability is the product. **Claude** is the fifth. Anthropic's chatbot has found a distinct audience: professionals who need long, nuanced, careful work. Programmers. Writers. Researchers. Analysts. People who don't just want an answer, they want the answer to be right, well-structured, and detailed. Anthropic reported $14 billion in annual revenue run rate in early 2026, with Claude as the primary product. That's roughly 10x growth year-over-year. The Pro plan at $20/month and the Teams plan at $30/month per seat are driving strong subscription revenue, and the API business serves developers who want Claude's models in their own products. Claude won by being different, not by being first. Where ChatGPT optimizes for breadth (it'll try anything), Claude optimizes for depth (it'll be genuinely helpful on hard problems). Where ChatGPT feels like talking to a fast friend, Claude feels like talking to a patient expert. Different products for different needs. And both are thriving. ## The Pattern: What Winners Share These five products share three things that the losers don't. First: zero-friction entry. You can start using any of them in under 60 seconds. No sales call. No onboarding sequence. No "book a demo." ChatGPT is a text box. Copilot is an extension install. Midjourney is a Discord bot. Perplexity is a URL. Claude is a text box. The time between "I want to try this" and "I'm using this" is measured in seconds. Second: immediate, obvious value. The first interaction delivers something useful. Not "you'll see ROI in six months." Not "it gets better as you customize it." Right now. First query. The product either impresses you or it doesn't, and these five impress consistently. Third: habit formation through repetition. Each of these products plugs into a workflow that happens daily. You code every day (Copilot). You ask questions every day (ChatGPT, Claude, Perplexity). You create visual content regularly (Midjourney). The products become habits because the underlying activities are habits. ## The Graveyard Now let me tell you about the products that raised millions, sometimes hundreds of millions, and have either died, pivoted, or are circling the drain. I won't name every failure. That would be cruel and also take too long. But the patterns are clear. **AI writing tools** that tried to replace human writing are struggling badly. Jasper, once valued at $1.5 billion, went through layoffs and a strategic pivot. Copy.ai has struggled with retention. Writer, Rytr, Writesonic, and dozens of others are fighting over a shrinking market. The problem? ChatGPT and Claude do the same thing for free (or $20/month), and they do it better. A standalone AI writing tool is a feature, not a product, and the platform companies ate the feature. **AI search startups** that aren't Perplexity are in trouble. You.com pivoted. Andi Search hasn't broken through. Kagi has a loyal niche following but hasn't crossed into mainstream adoption. The search market has room for one AI-native challenger. Perplexity got there first. **AI avatar and video tools** have high trial rates and terrible retention. Synthesia, HeyGen, and others see massive signups around product launches and marketing campaigns, then watch usage crater. The problem: most people don't need AI-generated videos regularly. It's a novelty, not a workflow. The ones surviving are targeting enterprise use cases (training videos, localization) where there's recurring need. **Autonomous agent startups** are the biggest category of unfulfilled promises. Companies that raised on the vision of "an AI that works for you" have consistently underdelivered. The technology isn't ready for fully autonomous operation. Users don't trust agents with consequential tasks. And the failure modes are too unpredictable for enterprise deployment. Some of these companies will eventually be right, but being early is the same as being wrong. **Vertical AI tools** are the most heartbreaking category. Companies that built AI for specific industries, legal, medical, financial, education, often have genuinely good products. The problem is distribution. A startup selling an AI contract review tool to law firms needs an enterprise sales team, regulatory compliance, liability insurance, and years of relationship-building. The technology is the easy part. Selling into a conservative industry is the hard part. ## Why $100 Billion Produced Five Products The venture capital industry funded AI companies the way it funds every hype cycle: fast, indiscriminately, and with very little product judgment. If your pitch deck mentioned "AI" or "LLM" or "generative," you could raise. The funding wasn't based on product-market fit. It was based on fear of missing out. The result is predictable. Most AI startups are building features, not products. They're taking a capability that OpenAI or Anthropic or Google offers through an API and wrapping a thin UI around it. That works for a demo. It doesn't work for a business, because the moment the underlying platform adds the same feature, the wrapper company dies. OpenAI adding search to ChatGPT was an extinction event for a dozen startups. Claude adding file analysis killed a dozen more. The five winners avoided this trap. Each one either controls its own model (OpenAI, Anthropic, Midjourney) or has built enough product differentiation that a model change wouldn't kill them (Copilot's IDE integration, Perplexity's citation system). The lesson for the industry is uncomfortable: most AI startups aren't building anything defensible. The model providers are eating the market from below. The platform companies (Microsoft, Google, Apple) are eating it from above. The space in between, the "AI wrapper" zone, is getting crushed from both directions. ## What Comes Next The next wave of AI products that break through won't look like chatbots. They'll be embedded in existing workflows so deeply that users don't think of them as "AI products." They'll be Canva's AI features, not a standalone "AI design tool." They'll be Notion's AI, not a separate "AI note-taking app." They'll be the AI in your email client, your calendar, your spreadsheet. The era of the standalone AI product, the "ChatGPT for X" pitch, is ending. The products that win from here will be the ones that disappear into the tools people already use. Five out of ten thousand. That's the hit rate. And honestly? Five products that genuinely improve millions of people's daily lives is a pretty good return on $100 billion. It's just not the return the VCs were expecting.