Venture capitalists (VCs) find themselves in a complex paradox: they are heavily investing in artificial intelligence (AI) startups, even though AI technologies have the potential to disrupt and reduce the need for traditional VC roles. This situation highlights both AI's transformative power and the evolving nature of the venture capital industry. Renowned investor Marc Andreessen has pointed out that venture capital may be among the last predominantly human professions, yet as AI automates more functions across sectors, even VC roles face uncertainty. His observations reflect a broader recognition that AI, while increasing efficiency and scalability, raises questions about the future of human involvement in fields that initially benefit from AI. VC firms now employ AI to streamline and automate administrative tasks that previously required significant human effort. AI tools are increasingly used in due diligence—evaluating the viability and risks of potential investments—by analyzing extensive data, market trends, competitors, and founders’ backgrounds faster and more comprehensively than humans. This allows VCs to make more informed, efficient decisions, potentially improving their success in backing startups. The core duties of venture capital involve identifying promising startups and supporting them post-investment through guidance, resources, and networks to aid growth. Ironically, many AI startups being funded develop platforms that automate these very functions: identifying opportunities, conducting complex evaluations, and assisting portfolio companies operationally, thereby reducing human intermediaries' roles. If these AI platforms mature successfully, traditional VC firms could face profound changes. Institutional investors—who allocate considerable capital to VC funds—may question the justification for the high fees charged by traditional venture capitalists, such as management fees and carried interest, which compensate for expertise and value-added services.

If AI efficiently performs many value-adding tasks, the case for premium fees may weaken. Despite this potential shift toward AI-driven venture capital, it remains largely speculative and developmental. Fully automating venture capital faces challenges in replicating nuanced judgment, emotional intelligence, and relationship-building—key to understanding founders’ visions and market dynamics. Human insight has traditionally been difficult to replace. Nonetheless, AI’s trajectory suggests significant industry restructuring could be imminent. In summary, the convergence of venture capital and AI presents a paradox: VCs invest in technologies that might eventually diminish their own profession’s role. As AI increasingly impacts all stages of investing—from deal sourcing and evaluation to portfolio management—the venture capital landscape may fundamentally transform. This evolution challenges established norms about startup funding, the value proposition of VCs, and the global startup ecosystem’s structure. Although the pace and scale of these changes are uncertain, this dialogue critically reflects on how technological innovation can reshape both targeted industries and the investment mechanisms themselves.