Despite the generative AI boom of the past three years, most AI startups are still primarily generating revenue through business-to-business sales, rather than capturing the consumer market. While general-purpose large language models (LLMs) like ChatGPT saw rapid consumer adoption, specialized consumer GenAI applications have largely failed to achieve widespread resonance. VCs discuss why most consumer AI startups still lack staying power, pointing to factors ranging from the rapid commoditization of underlying technologies to the limitations of existing devices.
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Official guidance: IEEE — official guidance for VCs discuss why most consumer AI startups still lack staying
Key Developments
Chi-Hua Chien, co-founder and managing partner at Goodwater Capital, addressed the challenges facing consumer AI startups at TechCrunch’s StrictlyVC event. He noted the initial excitement surrounding AI applications in video, audio, and photo editing, but observed that these opportunities quickly diminished as more powerful and accessible models, like Sora and open-sourced Chinese video models, emerged. This rapid technological advancement effectively commoditized many of the early applications. VCs discuss why most consumer AI startups still lack staying power, emphasizing the importance of platform stabilization.
Chien drew a parallel to the early days of the iPhone, where simple applications like flashlight apps initially gained popularity before being integrated directly into the operating system. He argued that AI platforms require a similar period of stabilization before truly transformative consumer applications can emerge. He believes the industry is nearing a point comparable to the mobile landscape of 2009-2010, which saw the rise of mobile-first giants like Uber and Airbnb. The potential technological parity between Google’s Gemini and ChatGPT could be a sign of this stabilization. VCs discuss why most consumer AI startups still lack staying power, suggesting that the current environment is akin to the nascent stages of the mobile app revolution.
Device Limitations and the Search for a New Platform
Elizabeth Weil, founder and partner at Scribble Ventures, echoed Chien’s assessment, describing the current state of consumer AI applications as being in an “awkward teenage middle ground.” Both Weil and Chien suggest that the limitations of the smartphone may be hindering the development of truly breakthrough consumer AI products. Chien argues that a device used so frequently but which only captures a small fraction of a user’s experience is unlikely to fully harness the capabilities of AI. VCs discuss why most consumer AI startups still lack staying power, highlighting the limitations imposed by existing smartphone technology.
Weil agreed that the smartphone’s lack of ambient awareness limits the potential for reimagining consumer AI products. She indicated her iPhone, stating she doesn’t believe that the future of consumer AI will be built for that device. This has fueled a race among startups and established tech companies to develop new personal devices that can potentially supplant the smartphone. These efforts include OpenAI and Jony Ive’s rumored “screenless,” pocket-sized device, Meta’s Ray-Ban smart glasses controlled by wristbands, and various startups experimenting with AI-powered pins, pendants, and rings. VCs discuss why most consumer AI startups still lack staying power, as innovation in hardware is critical for unlocking AI’s full potential.
Beyond New Devices: Personalized AI Services
While a new device might unlock new possibilities, not all consumer AI products necessarily require one. Chien suggested that a personal AI financial advisor, tailored to a user’s specific needs, could be a successful offering. Similarly, Weil anticipates the widespread adoption of personalized, “always-on” tutors delivered directly through smartphones. These examples demonstrate that specialized AI services can thrive without relying on entirely new hardware platforms. VCs discuss why most consumer AI startups still lack staying power, but see promise in personalized AI services accessible via existing devices.
Despite their enthusiasm for AI’s potential, both Weil and Chien expressed reservations about the emergence of stealthy AI-powered social network startups. Chien voiced concerns about networks where thousands of AI bots interact with user content, arguing that this could transform social interaction into a solitary experience. He emphasized that the appeal of social networking lies in the connection with real human beings. VCs discuss why most consumer AI startups still lack staying power, particularly those attempting to replace human interaction in social networks with AI bots.
Conclusion
The challenges facing consumer AI startups stem from a combination of factors, including the rapid commoditization of underlying technologies, the limitations of existing devices, and the difficulty of replicating genuine human interaction. While the initial excitement surrounding generative AI led to a flurry of applications, many of these have struggled to achieve lasting success. VCs discuss why most consumer AI startups still lack staying power, suggesting that the industry is still in a nascent stage, requiring further platform stabilization and potentially new hardware innovations to unlock its full potential. However, personalized AI services that address specific user needs, regardless of the device, may offer a more immediate path to consumer adoption and long-term viability.
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