General artificial intelligence (AI), a catalyst for mass AI adoption
We believe that generative AI, particularly large-language-models like GPT, could serve as the catalyst for widespread adoption of artificial intelligence. While AI has been utilized in enterprises for some time now, primarily for analytics and predictions (such as predictive maintenance on machinery, fraud detection in payments, ad targeting on the web/social media, and recommendation engines in e-commerce), the rapid rise in popularity of ChatGPT marks a significant milestone. For the first time, non-technical users could directly engage with artificial intelligence.
The response from users was overwhelmingly positive, with ChatGPT amassing 100 million monthly active users within just two months of its launch. This is a feat that even TikTok and Instagram were unable to achieve in such a short span of time.
We believe that the timing for adoption of AI should, by definition, be very fast given it is used as a software technology that is distributed through apps or web browsers on PCs and mobile phones. These devices, already owned and used daily by both enterprises and consumers. Consequently, we anticipate that the typical barriers to adoption (excluding potential regulatory issues) should be minimal compared to previous adoption cycles.
For context, achieving "mass adoption" took more than 20 years for technologies like electricity and the personal computer. However, the adoption rate has significantly accelerated for more recent technologies. For instance, the smartphone achieved a 50% adoption rate in less than five years following the launch of the iPhone, and a decade after the release of the Blackberry 5810. Similarly, the tablet market went from 0% to 50% market adoption within approximately five years of its launch. The chart below, from hbr.org, highlights the increasingly fast rate of technological adoption over time.
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