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While AI feels disruptive, incumbent tech giants possess all the key ingredients to win: massive datasets, huge capital for compute, and vast distribution networks. This suggests AI could reinforce their market power, making it a 'sustaining' innovation rather than one that unseats them.
The biggest winners from AI will be entities with massive distribution and significant cost inefficiencies. Legacy banks and large brands are prime candidates, as AI can drastically cut their operational costs while they retain their powerful brand and distribution moats.
VC Carter Reum argues the AI cycle is different from past disruptions like mobile. Previously, it was 'innovators competing with innovators.' Today, incumbents like Google and Microsoft have the advantage because they possess the unique combination of tech, talent, data, capital, and technical expertise required to win in AI.
The AI revolution may favor incumbents, not just startups. Large companies possess vast, proprietary datasets. If they quickly fine-tune custom LLMs with this data, they can build a formidable competitive moat that an AI startup, starting from scratch, cannot easily replicate.
Unlike mobile or internet shifts that created openings for startups, AI is an "accelerating technology." Large companies can integrate it quickly, closing the competitive window for new entrants much faster than in previous platform shifts. The moat is no longer product execution but customer insight.
Contrary to the narrative of AI startups destroying incumbents, established enterprise software companies will likely absorb and 'domesticate' AI. They will integrate AI capabilities into their existing platforms, leveraging deep customer relationships and distribution advantages to maintain their market position.
Contrary to popular narrative, established companies hold a significant advantage over AI-native startups. Their vast proprietary data and deep, opinionated understanding of customer problems form a powerful moat. The key is successfully leveraging these assets to build unique, data-driven AI solutions, which can create a bigger advantage than a pure tech-first approach.
AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.
Oren Zeev argues against the narrative that AI will kill all incumbents. He believes businesses with operational complexity, deep data moats, and strong distribution are not easily disrupted. These companies are more likely to leverage AI to their advantage, while simpler software companies are at greater risk.
Unlike previous tech waves, AI's core requirements—massive datasets, capital for compute, and vast distribution—are already controlled by today's largest tech companies. This gives incumbents a powerful advantage, making AI a technology that could sustain their dominance rather than disrupt them.
With AI lowering the barrier to building software, getting user attention is harder than ever. This shifts the competitive advantage to distribution. Incumbents can spray a 'good enough' AI model across billions of users, establishing a default that's difficult for a superior startup product to displace.