The common analogy of AI being "like a website" that every company must adopt may be misleading. The real transformative power of AI could be in enabling entirely new, AI-native businesses that leapfrog incumbents, rather than simply being a feature tacked onto existing products.

Related Insights

The most successful AI applications like ChatGPT are built ground-up. Incumbents trying to retrofit AI into existing products (e.g., Alexa Plus) are handicapped by their legacy architecture and success, a classic innovator's dilemma. True disruption requires a native approach.

Don't just sprinkle AI features onto your existing product ('AI at the edge'). Transformative companies rethink workflows and shrink their old codebase, making the LLM a core part of the solution. This is about re-architecting the solution from the ground up, not just enhancing it.

Incumbent companies are slowed by the need to retrofit AI into existing processes and tribal knowledge. AI-native startups, however, can build their entire operational model around agent-based, prompt-driven workflows from day one, creating a structural advantage that is difficult for larger companies to copy.

Most companies use AI for optimization—making existing processes faster and cheaper. The greater opportunity is innovation: using AI to create entirely new forms of value. This "10x thinking" is critical for growth, especially as pure efficiency gains will ultimately lead to a reduced need for human workers.

The focus on AI automating existing human labor misses the larger opportunity. The most significant value will come from creating entirely new types of companies that are fully autonomous and operate in ways we can't currently conceive, moving beyond simple replacement of today's jobs.

The true economic revolution from AI won't come from legacy companies using it as an "add-on." Instead, it will emerge over the next 20 years from new startups whose entire organizational structure and business model are built from the ground up around AI.

Incumbents face the innovator's dilemma; they can't afford to scrap existing infrastructure for AI. Startups can build "AI-native" from a clean sheet, creating a fundamental advantage that legacy players can't replicate by just bolting on features.

The true advantage for new AI-native companies lies not in simply using AI tools, but in building entirely new business models around them. This mirrors how Direct-to-Consumer brands leveraged Shopify not just to sell online, but to fundamentally change distribution, marketing, and customer relationships, thereby outmaneuvering incumbents.

Most current AI tools are skeuomorphic—they just perform old tasks more efficiently. The real transformation will come from "AI-native" applications that create entirely new business models, just as Uber was an "iPhone-native" concept unimaginable before its time. The biggest winners will use AI to become the industry, not just sell to it.

The fundamental shift from AI isn't about replacing foundational model companies like OpenAI. Instead, AI creates a new technological substrate—productized intelligence—that will engender an entirely new breed of software companies, marking the end of the traditional SaaS playbook.