The Future of AI Is About What You Do With It

If you’ve been keeping an eye on AI, you’ve probably seen OpenAI rocket past a $150B valuation, with Anthropic, Google DeepMind, and others in hot pursuit. Right now, model-building is big business—but for how long?

DeepSeek AI’s R1 reasoning model proves that elite AI labs won’t be exclusive for long. As it gets easier and cheaper for companies to spin up custom LLMs, the real question shifts: Who’s turning AI into must-have applications that users can’t live without?

Specialized AI apps alone will grow from $39B (2023) to $512B (2030). That’s a 13x jump—and right now, the biggest winners are still up for grabs.

As Wired noted in its 2025 “Year of the AI App” feature, the real battle isn’t about who trains the biggest model—it’s about making AI indispensable. While AWS, Microsoft, and Google are pouring billions into infrastructure, they’re leaving a massive gap in solving real-world, industry-specific problems.

Big Tech Builds the Platform, Startups Build the Value

Cloud giants like Amazon Web Services (AWS) and Microsoft Azure have bet on a platform-first strategy. They provide the models, the GPUs, and the APIs, but they’re not getting their hands dirty with industry-specific AI solutions.

In fact, AWS recently announced a new “agentic AI automation” division, reinforcing its commitment to next-gen infrastructure for multi-agent workflows. But this follows the same pattern we’ve seen before: cloud providers build the underlying tech, while startups build the solutions that actually drive adoption.

And that’s where the magic happens. Specialized, user-friendly tools always outcompete raw infrastructure. It happened with Salesforce vs. AWS/Oracle. It happened with Figma vs. Adobe. And it’s happening now in AI.

Where AI Apps Are Already Winning

Some companies are already proving that domain-specific AI is the real play:

• Legal Tech: Harvey and Casetext, Part of Thomson Reuters (acquired for $650M) show that AI copilots tailored to legal workflows are a bigger deal than just dumping contracts into ChatGPT.

• AI Translation: DeepL competes with Google Translate by offering enterprise-grade precision—enough to land them on Forbes’ Cloud 100 and win millions of users.

• Commerce AI: Solutions like Icon and getitAI are reimagining the entire shopping experience, from AI ad creation to AI-guided video live shopping, by merging AI avatars, video generation, and LLM-driven storytelling.

• Healthcare: Abridge, which seamlessly slots into EHR systems, is solving a specific, high-value problem—one that generic LLMs alone can’t tackle.

• Cross-Industry Disruptors: Jasper (marketing), MagicSchool AI (education), and Trunk Tools (construction) prove that AI designed for actual workflows beats one-size-fits-all solutions.

The key theme? The fastest-growing AI startups aren’t just using AI—they’re embedding it into business-critical processes.

The AI App Boom Is Already Here

Look around—industries that were once slow to adopt tech are jumping on AI at record speed. Law firms, banks, and healthcare providers—some of the most conservative industries—are now adopting AI faster than SaaS did in the 2010s.

Why Now? The Window Won’t Stay Open Forever

• Confidence: OpenAI’s eye-watering valuation shows that model providers have value—for now. But as the infrastructure moat erodes, the companies that own data, workflows, and user experience will be the ones that stick around.

• Urgency: The next 6–12 months are pivotal. AI adoption is accelerating, but once industries standardize around specific AI solutions, switching costs will rise. If you’re building at the application layer, now is the time to capture market share before competitors flood in.

Yes, model providers are making headlines, but the real AI gold rush is happening elsewhere. The companies that own the user experience—not just the raw intelligence—will be the ones that create lasting value.

The AI arms race isn’t about who builds the biggest model anymore—it’s about who builds the most indispensable app.

That’s where the users are.

That’s where the revenue is &

That’s where the most valuable AI companies are being built—right now.