The artificial intelligence startup ecosystem is experiencing a significant valuation correction in 2024, with down rounds and flat rounds hitting all-time highs since 2014. This trend is affecting even the most prominent AI companies that were previously considered untouchable darlings of the venture capital world.
Inflection AI serves as a prime example of this shift. After raising $1.3 billion at a $4 billion valuation in 2023, the company saw its effective valuation slashed when Microsoft paid just $650 million to license its software and hire key personnel earlier this year. The UK’s competition regulator characterized this arrangement as a “relevant merger situation,” though it fell short of an official acquisition.
According to PitchBook data, the percentage of AI startups raising up rounds in the US dropped from 90.2% in 2022 to 81.1% in 2024, while down rounds increased from 6.5% to 11.4% during the same period. This represents a dramatic shift in investor sentiment following the initial ChatGPT-fueled euphoria that saw AI startups globally rake in nearly $50 billion from VCs in 2023.
Several high-profile AI companies have already faced valuation cuts or entered acquihire arrangements. Jasper AI slashed its internal valuation in 2023 as growth stalled, while the founding teams of Character.ai and Adept were absorbed by Google and Amazon respectively, in deals that significantly reduced their effective valuations.
The core issue plaguing many AI startups is the capital-intensive nature of building foundational models. Companies have spent heavily on expensive AI engineers and training datasets without achieving sufficient traction or revenue to justify their inflated valuations. As Francesco Ricciuti from Runa Capital notes, these startups operate like typical software companies but with significantly higher infrastructure costs and lower margins.
Investors are now taking a more cautious approach, with many startups turning to secondary share sales as an alternative funding mechanism. This allows companies to provide liquidity to employees and early investors without publicly announcing a down round, helping them retain talent in the competitive AI hiring market while avoiding the stigma of a reduced valuation.
Key Quotes
In light of the current hype surrounding the sector, we’ve observed early signs that the AI market may be overheating, with the increase in flat rounds, down rounds, and acquihires being indicative of the challenges ahead
Andreas Riegler, general partner at APEX Ventures, explains how the proliferation of down rounds and acquihires signals fundamental challenges in the AI startup ecosystem, suggesting the market has become overheated despite continued enthusiasm.
Investors went crazy for AI startups with zero revenue, at higher valuations, which will be an issue. Acquihires like Inflection.ai, Adept, and Character.AI will accelerate in the next 12 months, and these startups will have to face the music
Umesh Padval, managing director at Thomvest Ventures, warns that the irrational exuberance of 2023 created unsustainable valuations for revenue-less AI startups, predicting an acceleration of acquihires as companies struggle to justify their price tags.
Those that torch VC’s money to chase growth will crash mid-flight. They will die just like the quick commerce startups
Francesco Ricciuti, a deep tech VC at Runa Capital, draws a stark parallel between AI startups burning through capital and the failed quick commerce companies, emphasizing that unsustainable growth strategies will lead to company failures.
A lot of them hired really expensive engineers to try to solve this problem. They also spend a lot of money trying to train these datasets, and what they realized is that now they’re running out cash without any sort of traction to prove — so they’ve burnt a lot of money
A London-based investor describes the fundamental cash flow problem facing AI startups: the combination of expensive talent acquisition and costly model training has left many companies depleted without demonstrable market traction or revenue.
Our Take
This valuation correction was inevitable and arguably healthy for the long-term development of AI technology. The 2023 funding environment created perverse incentives where startups prioritized raising capital at astronomical valuations over building sustainable businesses with real revenue streams.
What’s particularly striking is how quickly the market shifted—from 90.2% up rounds in 2022 to just 81.1% in 2024. This suggests investors have rapidly sobered to the realities of AI economics: high infrastructure costs, expensive talent, and uncertain paths to profitability.
The rise of acquihires by Big Tech is concerning from a competition perspective. While these deals provide exits for struggling startups, they concentrate AI talent and technology within a handful of companies, potentially stifling innovation. The secondary market emergence as a funding alternative is creative but may simply delay the inevitable reckoning for companies without viable business models. Ultimately, this correction should separate genuinely innovative AI companies from those riding the hype cycle.
Why This Matters
This valuation reset represents a critical inflection point for the AI industry, signaling the end of the post-ChatGPT funding frenzy and the beginning of a more sustainable, metrics-driven investment environment. The trend has profound implications for the entire AI ecosystem, from startups to Big Tech companies.
For AI entrepreneurs and employees, the shift means increased pressure to demonstrate real revenue and product-market fit rather than relying on hype and potential. The rise of acquihires by tech giants like Microsoft, Google, and Amazon suggests that many well-funded AI startups may not survive as independent companies, potentially reducing innovation and competition in the sector.
For investors, this correction serves as a reminder that even transformative technologies are subject to market fundamentals. The capital-intensive nature of AI development, combined with lower margins than traditional software, creates unique challenges that require careful evaluation.
This trend also has broader implications for AI development and deployment. As funding becomes more selective, we may see a consolidation of AI capabilities within large tech companies, potentially limiting diverse approaches to AI safety, ethics, and applications. The market correction could ultimately lead to a healthier, more sustainable AI industry focused on real value creation rather than speculative valuations.
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Source: https://www.businessinsider.com/ai-down-rounds-rise-valuations-investors-2024-9