Firms built around AI are scaling knowledge work without the knowledge workers.
For several years now the idea that AI will transform organizations has been less a finding than a forecast repeated in keynotes, board decks, and earnings calls with a confidence that outpaced the evidence. The new working paper, “AI-Native Firms,” co-written by HBS AI Institute PI Rembrand Koning, offers one of the first empirical looks at what AI-enabled organizational transformation may look like in practice. Studying Y Combinator startups from 2020 to 2024, they ask straightforwardly whether organizations built around AI are actually organized differently. The answer turns out to be yes, but the why points somewhere most of the AI organizational transformation story has missed.
Why This Matters
In a world with more competitors, faster product cycles, and lower barriers to entry, this research highlights that business leaders and executives can begin redefining success-with-AI in relation to value per employee. That starts with learning to scale through compute by embedding AI into products and services so more customer value can be delivered without a proportional expansion of headcount. It also means moving toward a more expert-dense workforce, where smaller teams build, supervise, and improve systems that handle day-to-day operations and maintenance themselves. Finally, leaders should reassess their firm hierarchies: high functioning firms are flatter with fewer layers, suggesting some coordination and routine knowledge work can move into tools and products. The firms that win may be those that stop treating AI as a productivity add-on and start treating it as a core part of their product.
Link to the HBS AI Institute Insight Article
Link to the Research Paper
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