It’s been three-and-a-half years since generative AI exploded onto the scene. In this past year, progress has continued its relentless pace: Vibe coding took off, companies embraced agentic workflows, regular users of ChatGPT hit 900 million and Google’s Gemini surpassed 750 million, and OpenAI posted an $852 billion valuation in its latest funding round.

Amid the hype and debate over AI’s future, one question continues to stand out: How are people actually using this technology now? This is the focus of AI in the Wild, a longitudinal study carried out by me and Sara Biuk that tracks how we humans are evolving alongside AI.

For the third installment (following 2024 and 2025) of this annual research, we analyzed 12,637 AI use cases. This dataset is an order of magnitude greater than those of the previous two years: We built a database of nearly 50,000 records that were collected between March ‘25 and Feb ‘26 from a wider pool of online sources, adding LinkedIn, TikTok, and YouTube to our previous sources of Reddit, Quora, and articles. (There are pros and cons to this “social listening” approach, which I’ve previously detailed.) We then used a hybrid human-AI system to identify use cases.

As an aside, it’s worth noting the enduring necessity of human judgement in this process. Despite hundreds of iterations of our scripts with frontier models, we found AI to still be far from perfect for the task of evaluating text as a bona fide, valuable, meaningful AI use case.

This year, we found that people are adopting generative AI for an ever-widening range of uses. There’s some nuance here. Trends from one year to the next should be understood as shifts in emphasis, rather than stark ruptures. While last year, emotional use cases topped technical ones, there were many emotional uses before and there remain many technical uses today. Remember, the pie of users is growing—just because more users are doing one thing this year doesn’t mean that others stopped doing another. Finally, the bulk of the dataset is from individuals utilizing AI to some end, both at home and at work.

So, what shifts have we seen? As the breadth and depth of usage grows, so has the anxiety that people are surrendering their cognitive responsibilities to AI. There’s also a parallel concern that they are relying too much on the technology for emotional support. In the business world, we’re seeing lots of activity producing marginal rather than game-changing benefits, so far.

Here’s how people have been using generative AI this past year.

“Thinkslop”

The new AI models have become adept at mimicking human thinking, which makes it tempting to let them do this for us. That can be a problem.

In at least a quarter of the top use cases this year (therapy/companionship [#1], relationship advice [#7], enhanced decision-making [#13], organizing my life [#14], drafting emails [#42], generating ideas [#47]), people are asking AI to do some portion of their thinking. There’s an argument that this kind of AI use is cause for concern. First, because these types of activities are precisely those for which human beings need to take responsibility. And second, because such activities are the kinds that we thrive at, as a species.

Jumping on the bandwagon of Merriam Webster’s 2025’s word of the year, “slop” (which includes “workslop,” from HBR’s most popular article last year), we’ll use the term “thinkslop” for the lazy, sloppy thinking that can be engendered by excessive use of AI.

AI usage can lead to people becoming vulnerable to thinkslop in a few ways.

We lose track of our intentions.

It is, of course, possible to think hard about our intentions, carefully turn them into a corresponding prompt, and only then pass the baton to AI. But the barrier to getting output is so low, it’s tempting turn to AI at the start of our brainstorming process. Whether it’s developing a thesis for a research paper, coming up with draft art, or articulating the strategy for a project, it’s easy to fire off a prompt before we’ve fully thought through what we’re really trying to do.

As one user said: “Relying on AI to fully generate images or texts risks removing intention, authorship and personal perspective—elements that still matter in creative and commercial work.”

We outsource our thinking.

When we go to AI first, we deny our brain the opportunity to solve the problem afresh and unfettered. Moreover, we may well miss out on valuable ideas that exist only in the deep recesses of our memories and imaginations. This issue has been called “cognitive debt” in other studies.

As one user in our database realized: “With excessive use of ChatGPT and all these AI tools, I realized I hadn’t been using my brain the same way. It’s so easy to let AI write for you, and I think that made me lazy with language. I was literally outsourcing my brain.”