Key Takeaways
- • Venture capital firms are increasingly shifting capital allocation toward deep tech startups as AI commoditizes traditional software development, requiring investors to reassess portfolio construction and due diligence processes.
- • Strong technological barriers to entry have become the primary selection criterion for VC investors, as AI-generated code commoditizes business model replication and reduces competitive moats in conventional tech startups.
- • SGInnovate's executive director for investments emphasizes that deep tech investment success requires both specialized technical expertise and early-stage conviction, fundamentally changing how VCs evaluate risk and timing in their investment theses.
- • Deep tech startups require sustained R&D investment, substantial capital reserves, and specialized investor knowledge—creating structural advantages for firms with proprietary technical due diligence capabilities and longer investment horizons.
Summary
Venture capital deployment is undergoing a strategic reorientation as artificial intelligence reshapes the competitive landscape of early-stage technology companies. More VC firms are expanding into deep tech investments, driven by the recognition that AI-powered code generation has substantially lowered barriers to entry in traditional software development. This shift reflects a broader market reassessment: as business models become easier to replicate through AI tools, investors are increasingly prioritizing startups with defensible technological moats and genuine innovation barriers.
According to Tong Hsien-Hui, executive director for investments at SGInnovate—Singapore's deep-tech ecosystem builder—the investment thesis has fundamentally shifted. "You need to have great barriers to entry so that it's not so easy for someone to replicate so quickly," Tong stated, highlighting the core rationale behind the VC migration toward deep tech. As AI makes technology more commoditized with businesses being built on AI-generated code, VCs are seeking companies with authentic global scalability and proprietary technological advantages that cannot be quickly duplicated by well-capitalized competitors.
The implications for institutional investors and fund managers are material. Deep tech investment requires both technical expertise and conviction to place capital early in development cycles—characteristics that distinguish this allocation from conventional venture strategies. These startups typically demand prolonged research and development phases, substantial financial commitments, and investors with specialized sector knowledge capable of evaluating complex technological feasibility and competitive positioning. This structural shift is likely to concentrate capital among larger VC firms with in-house technical resources, or alternatively, create opportunities for specialized deep tech-focused vehicles with differentiated due diligence capabilities.
The macro trend reflects a broader market inflection point: as AI reduces the cost of building software and replicating business models, differentiation increasingly flows from genuine scientific or engineering breakthroughs rather than software execution or market timing. For hedge funds, family offices, and institutional investors evaluating VC exposure or co-investment opportunities, this rebalancing signals a potential compression of returns in "spray and pray" venture portfolios while rewarding conviction-based deep tech strategies with defensible competitive positions.
According to Tong Hsien-Hui, executive director for investments at SGInnovate—Singapore's deep-tech ecosystem builder—the investment thesis has fundamentally shifted. "You need to have great barriers to entry so that it's not so easy for someone to replicate so quickly," Tong stated, highlighting the core rationale behind the VC migration toward deep tech. As AI makes technology more commoditized with businesses being built on AI-generated code, VCs are seeking companies with authentic global scalability and proprietary technological advantages that cannot be quickly duplicated by well-capitalized competitors.
The implications for institutional investors and fund managers are material. Deep tech investment requires both technical expertise and conviction to place capital early in development cycles—characteristics that distinguish this allocation from conventional venture strategies. These startups typically demand prolonged research and development phases, substantial financial commitments, and investors with specialized sector knowledge capable of evaluating complex technological feasibility and competitive positioning. This structural shift is likely to concentrate capital among larger VC firms with in-house technical resources, or alternatively, create opportunities for specialized deep tech-focused vehicles with differentiated due diligence capabilities.
The macro trend reflects a broader market inflection point: as AI reduces the cost of building software and replicating business models, differentiation increasingly flows from genuine scientific or engineering breakthroughs rather than software execution or market timing. For hedge funds, family offices, and institutional investors evaluating VC exposure or co-investment opportunities, this rebalancing signals a potential compression of returns in "spray and pray" venture portfolios while rewarding conviction-based deep tech strategies with defensible competitive positions.
Go deeper than the headline
Research every firm in this story, track the ones that matter and get the daily briefing — free for 7 days.