The generative AI landscape has been evolving rapidly, with foundational model companies leading the charge. However, recently investor interest is shifting away from the firms developing these foundational models to those making applications atop them, thereby expanding the startup landscape and opportunities.
According to S&P Global, the nine top pure-play foundation model companies, including Anthropic, Cohere AI, and OpenAI, have collectively secured $28.67 billion in disclosed funding rounds. While these companies are still poised for growth, investor interest in them has started to wane since late 2023.
One primary factor contributing to this trend is the dominance of certain players in the market, namely OpenAI, Google, Microsoft, and Anthropic, which appear firmly entrenched and difficult to challenge. Moreover, the development of foundational models requires substantial capital investment. Although the cost per token is projected to decrease gradually, the anticipated surge in demand might not be substantial enough to offset the decline in access costs on a company level. Additionally, the presence of viable open-source models as alternatives is expected to exert pressure on profit margins. Furthermore, consumer expectations have evolved beyond generic models; they now demand models tailored to their specific business requirements, as well as applications that offer direct business advantages.
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Recognizing this shift in the market, investors have redirected their attention toward application-layer startups. According to S&P Global, eight out of the ten largest generative AI deals in the 1Q24 were to companies specializing in developing applications utilizing third-party foundation models. These companies garnered twice the amount of investment in 1Q24 compared to the same period in 2023.
In April, Perplexity AI, a San Francisco-based startup specializing in search engine technology, secured $63 million, pushing the company's valuation past $1 billion. In February, Magic AI, another San Francisco-based startup dedicated to automating software development processes, raised a $117 million Series B funding round. Additionally, Glean Technologies, a startup focused on AI-powered work assistance and enterprise search solutions, raised around $200 million in a Series D funding round at a valuation of $2.2 billion. All these companies leverage third-party foundation models from the likes of OpenAI, Mistral, Meta Platforms, and Anthropic, among others.
Figure: VC Investors Increase Focus on Generative AI Applications
Source: S&P Global
Customer acquisition for application-layer startups is typically easier due to their tailored products for specific market segments. Coupled with lower expenses and their profit potential, the companies have become attractive investments. However, specialization also means a smaller total addressable market, resulting in fewer potential customers. Consequently, application-layer companies are less likely to achieve the outsized valuations observed with foundational models.
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This trend indicates that the AI market is maturing, with investors becoming more discerning about their investments. While AI has experienced significant growth in recent years, the need to keep pace with its rapid evolution has been a priority for every organization, which has also yielded tangible results in the past. According to Accenture, executives from the world's largest 2,000 companies, as measured by market capitalization, who discussed AI during earnings calls were 40% more likely to witness an increase in their share prices in 2021. However, the study also highlighted that only 12% of these companies were operating at an AI maturity level, conferring a strong competitive advantage. Consequently, there has been a surge in the phenomenon of "AI washing," leading the SEC to propose a rule in July 2023 aimed at financial firms to mitigate conflicts of interest in their use of AI tools.
General integration of AI is no longer sufficient. Both consumers and organizations are demanding substantial change through adoption, necessitating the emergence of enterprise-level application startups. Major players have also begun to acknowledge this shift. For instance, IBM and Salesforce announced their enterprise-grade model last year, aimed at aiding businesses across various industries worldwide in accelerating their adoption of AI for CRM purposes. However, the majority of prominent players in the landscape are still focused on the arms race, leaving ample opportunities for startups to exploit.
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In conclusion, the generative AI landscape is experiencing a significant shift as investor interest pivots towards application-layer startups. While foundational model companies have secured substantial funding, their dominance and the hefty investment required in foundational models have led investors to explore opportunities elsewhere. The rise of application-layer startups signals a maturing market where tailored solutions meet specific market demands. This shift not only reflects market dynamics but also the growing demand for impactful AI solutions across industries, paving the way for further innovation and growth in the coming years.
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