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.
With over half of new startup pitches focusing on AI automating existing jobs, the primary solution to this massive displacement is not retraining, but fostering an ecosystem that aggressively creates new companies, new industries, and consequently, new roles.
Instead of selling software to traditional industries, a more defensible approach is to build vertically integrated companies. This involves acquiring or starting a business in a non-sexy industry (e.g., a law firm, hospital) and rebuilding its entire operational stack with AI at its core, something a pure software vendor cannot do.
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.
The democratization of technology via AI shifts the entrepreneurial goalpost. Instead of focusing on creating a handful of billion-dollar "unicorns," the more impactful ambition is to empower millions of people to each build a million-dollar "donkey corn" business, truly broadening economic opportunity.
During a fundamental technology shift like the current AI wave, traditional market size analysis is pointless because new markets and behaviors are being created. Investors should de-emphasize TAM and instead bet on founders who have a clear, convicted vision for how the world will change.
The true enterprise value of AI lies not in consuming third-party models, but in building internal capabilities to diffuse intelligence throughout the organization. This means creating proprietary "AI factories" rather than just using external tools and admiring others' success.
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.
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.
Many engineers at large companies are cynical about AI's hype, hindering internal product development. This forces enterprises to seek external startups that can deliver functional AI solutions, creating an unprecedented opportunity for new ventures to win large customers.