A year ago, I wrote a piece here about how people were really using gen AI. That article seemed to hit a note: It was popular, featured in viral posts, and the beautiful accompanying infographic has been shared far and wide. The use cases split almost equally between personal and business needs, with roughly half spanning both.

Since then, the hype around AI, gen AI, and large language models (LLMs) has only amplified. User interest has doubled, investment in AI is skyrocketing, governments are taking more emphatic and explicit positions, and the stakes are about as high as they get—the future of humanity, according to some.

The HBR editors and I felt a need to update the research. Much has happened over the past 12 months. We now have custom GPTs: AI tailored for narrower sets of requirements. New kids are on the block, such as DeepSeek and Grok, providing more competition and choice. Millions of ears pricked up as Google debuted their podcast generator, NotebookLM. OpenAI launched many new models (now along with the promise to consolidate them all into one unified interface). Chain-of-thought reasoning, whereby AI sacrifices speed for depth and better answers by sharing the intermediate reasoning steps with the user before arriving at a final answer, came into play. Voice commands now enable more and different interactions, such as allowing us to use gen AI while driving. And costs have substantially reduced with access broadened over the past 12 hectic months.

The aspiration for this rebooted piece is exactly as it was a year ago. When people see others making effective, productive, advantage-yielding uses of a technology, they follow suit. Real-world use cases change behavior in ways and to an extent that PR, thought leadership, and technological brilliance simply cannot. So, by surfacing use cases from the depths of hundreds of subreddits, we hope to increase awareness and accelerate the many positive and beneficial applications of gen AI.

For this piece, I adopted the same methodology as last year but scoured more data (there was much more to scour) and limited the results to the past 12 months. I looked at online forums (Reddit, Quora), as well as articles that included explicit, specific applications of the technology. Perhaps owing to its inherent pseudonymity, Reddit again yielded the richest insights. I read through them myself, and added each relevant post to the tally for that category. Several days later, I emerged with the count and the quotes for each of the new 100 use cases.

The 2025 Top-100 Gen AI Use Case Report lists the top 100 applications now, in 2025, rated according to perceived usefulness and scale of impact (assessed qualitatively by expert review), and includes a quote or several for each. As before, this is where the real gold lies (but note that it’s produced in its raw, unedited form, and therefore not for the faint-hearted!). This time, I’ve steered harder to include quotes that are more explicitly and immediately useful.