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Saved February 14, 2026
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This article examines the evolving landscape of large language model (LLM) adoption, highlighting changes in user demographics and usage patterns. While growth continues globally, particularly in countries like India, the focus is shifting from standalone LLMs to integrations in widely-used applications like Google Search and Meta’s platforms. The piece also notes that many users are leveraging AI for work without employer-provided access.
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LLM adoption is evolving, with shifts in who uses these technologies and how. While ChatGPT experienced rapid growth—growing from under 400 million to nearly 800 million weekly active users in just eight months—its growth rate has started to slow. In contrast, other LLMs like Gemini have seen faster increases in user numbers, particularly in markets outside the US. For example, daily ChatGPT users in India surged sevenfold over the past year, highlighting a growing global user base that could offset stagnation in more saturated markets like the US.
User engagement metrics reveal that even without a significant influx of new users, existing ones are using LLMs more intensively. The number of messages sent by ChatGPT users has increased faster than the user base itself. However, web traffic for ChatGPT has stagnated, suggesting a potential shift from web use to app usage. The ChatGPT app was the most downloaded app of the year, with 1.9 billion downloads from October 2024 to September 2025. Meanwhile, average time spent in the app has risen, with ChatGPT users averaging 17 minutes per day and Gemini users averaging 11 minutes—indicating a growing reliance on these tools.
Revenue from LLMs continues to grow rapidly, with OpenAI's annualized revenue hitting $13 billion as of August, expected to rise to around $21 billion by year-end. This revenue growth reflects both increased user numbers and deeper integration of AI into workplaces. A survey indicated that 36% of respondents used AI for work tasks, even if their employers didn’t provide access. This suggests that while enterprise deployments are significant, a substantial amount of AI usage occurs informally, underscoring its growing role in everyday tasks.
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