How AI is forcing VCs to rethink their timelines
[SINGAPORE] There’s a lot of talk about how much generative AI has changed the startup game, but what’s less discussed is the extent of the sector’s impact on venture capital itself.
The speed with which AI-driven companies can create value is forcing VC fund managers to rethink long-standing frameworks for early-stage investment. But genAI is also capable of rapidly destroying value, and this is driving VCs to experiment with new fund structures and strategies.
This breakneck pace is revising VC playbooks. Here’s why rigid timelines no longer work and what flexible alternatives are emerging.
On the clock
Historically, VC funds have operated on a 10-year term model. The first three to five years are spent deploying capital, while the next ones are focused on scaling a firm’s portfolio companies before seeking exits in the second half of the fund’s life.
However, AI is compressing this timeline.
While an ecommerce business or software-as-a-service company may need years to reach immense scale, an AI-native firm can do this in a matter of months.
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This is partly due to the hype behind the AI gold rush, which has been pumping investment into firms. But there’s another factor at work: AI products can be deployed globally at near-zero marginal cost, improve with data, and spread virally through developer and user networks.
For example, Mistral AI reached a valuation of US$2 billion just seven months after it was founded in April 2023. Thinking Machines Lab, meanwhile, secured a monster seed round of US$2 billion this July at a US$10 billion valuation.
While a huge valuation may seem like a positive for an investor, the speed at which AI firms reach these dizzying heights puts intense pressure on the 10-year fund cycle.
These sizable valuations can delay IPOs as they set such high expectations for public market performance. After all, why would a founder or investor risk going public at an inflated valuation and see the value of the company drop?
This dynamic is forcing VCs to seek liquidity through other channels like mergers and acquisitions or secondary sales to lock in returns.
That’s the value creation side of the coin, but the value destruction AI causes is equally swift as the tech is evolving at breathtaking speed.
For instance, if a new, highly efficient open-source AI model is released in a specific sector, incumbents that have proprietary models could see their competitive moats destroyed overnight.
A good example is the rise of DeepSeek Coder V2, an open-source model that has outperformed several proprietary models on coding benchmarks. This kind of disruption forces VCs to constantly reconsider the long-term viability of their portfolio companies.
Flexibility at a premium
This shift towards quick cycles has led some VC firms to change how they operate. Rather than sticking to strict, multiyear plans and being purely early-stage backers, they have become portfolio strategists who proactively manage their holdings.
VCs taking this approach, however, need flexibility, mainly to buy and sell stakes on the secondary markets. By reselling their shares in private companies to other investors in this market, VCs can gain liquidity instead of waiting for an IPO or new funding round for an exit.
In contrast, there is a mismatch between the rigidity of a 10-year lifecycle fund and how swiftly AI firms scale. The explosive early growth of AI companies is often followed by longer periods of business model validation and delayed exit events.
This means a 10-year fund’s fixed timeline can expire just as an AI firm is entering its most value-creating phase. This forces investors to exit prematurely and miss out on long-term upside.
The solution for some fund managers is permanent capital vehicles (PCVs). These offer open-ended investment horizons, allowing managers to hold onto generational winners for longer to maximize returns.
This structure also provides more flexibility so investors can enter or exit at different times instead of being locked into a single cycle.
While PCVs are not yet the norm, leading firms are moving in this direction. For instance, Sequoia Capital transformed its fund structure into the evergreen Sequoia Fund, a more flexible model well-suited for the AI era.
This structure allows the firm to hold public and private assets in a single vehicle, eliminating the artificial timeline pressures of a 10-year fund.
What this means for VCs and founders
DeepSeek’s impact on Nvidia, where a single innovation triggered a valuation drop of some US$600 billion, is a stark reminder of how market dynamics can shift so suddenly. This evolving landscape presents new challenges and opportunities for both investors and founders.
VCs have rethink their fund structure, as the traditional 10-year model may be too rigid for the fast-paced AI industry. PCVs or funds with explicit authorization for secondary market activity may be the way to go.
VCs must also have a strong technical edge to understand the AI companies they invest in as surface-level due diligence won’t cut it. VCs need in-house technical expertise to evaluate an AI startup’s technology, data sources, and go-to-market strategy so they can see how sturdy its moat is.
Finally, active portfolio management is crucial and trumps the “invest and wait” approach. VCs must become hands-on and be prepared to help their portfolio companies navigate rapid competitive shifts and be ready to exit positions quickly to de-risk investments.
Founders, meanwhile, should seek investors who understand the nimble pace of AI development and can give them structural flexibility. This support could involve participating in a secondary sale to get early liquidity or committing for over a decade to help build a generational company.
Open-source innovation in AI is moving fast, and that means a powerful business model isn’t enough. Founders must focus on not just building a defensible moat, but also creating a durable competitive advantage through proprietary data, a strong user community, network effects, or a unique distribution channel.
Founders should look beyond public listings to exit. Being open to strategic acquisitions and secondary sales can provide returns for their team and investors while continuing to scale the business.
The jury is still out on which new models will prevail, but one thing is clear: GenAI is rewriting the VC playbook. Adaptability, strategic liquidity, and long-term vision are now the essential tools for creating and preserving value in this new market reality. TECH IN ASIA
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