The discussion around ChatGPT and generative AI has been plagued by the conflation of "usage" with "users".

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The launch of ChatGPT has sparked a wave of excitement around AI’s potential. In just two months, it has grown to 100M users globally, making it the fastest growing consumer product in history. It’s captured the imagination of everyday consumers and businesses alike on creative ways to leverage LLMs.

(quote & image source: https://lnkd.in/g2y77SCf)
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While it is undoubtedly true that ChatGPT has garnered over 100 million uses globally, this does not necessarily mean that the technology has been adopted by those users.

Adoption of technology requires evidence that the technology has been actively integrated into the routines, habits, and processes of individuals or businesses, and that it is consistently applied over time.

It is simply too early to tell what percentage of the 100M+ individuals who have used ChatGPT directly will continue to use it in their day-to-day activities.

It is likely that the majority of people who "use" ChatGPT (or other LLMs) in the future will do so without specific intent, as the technology will be baked into other tools they habitually use. As an analogy, predictive text was not intentionally adopted by most people, but simply appeared in tools they were already using, like email and messaging.

As major companies like Microsoft and Google integrate LLM output into their search engines, it will soon become commonplace for billions of people to "use" ChatGPT-like technologies without even realising it. Therefore, it is important to distinguish between usage and adoption when discussing the impact of ChatGPT and generative AI.

This distinction has significant implications for the market of generative AI applications and services. It indicates that this market will likely be divided into two groups: individuals or businesses who intentionally adopt generative AI tools to enhance their workflows, and those who passively adopt new features and functionality incorporated into their existing preferred tools and services.

The former group is likely to engage in custom training activities and deliberately design workflows around the generative AI tools they adopt, while the latter will accept generative AI as an added feature to their existing tools without necessarily undergoing custom training activities or intentionally reconfiguring their workflows.

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