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Time charter

* [job market](/partner-content/charter/tag/job-market/)  
## job market  


# How Hiring is Changing as AI Expectations Adjust

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![Michelle Peng](https://static.time.com/v3/assets/bltea6093859af6183b/blt9d68e3e5a01ecd19/6998c9ecd32e93492ecd7596/IMG_1157.png?branch=production&width=1200&quality=75&auto=webp&crop=1:1)

by 

[Michelle Peng](https://time.com/author/michelle-peng/)

Aug 2, 2026 10:30 AM UTC

![](https://static.time.com/v3/assets/bltea6093859af6183b/blt3d87b2f62dca5a67/6a6d2ee2f1b1caada1678e74/charter-simon.jpg?branch=production&width=1200&quality=75&auto=webp&crop=3:2)

Art: Charter

![Michelle Peng](https://static.time.com/v3/assets/bltea6093859af6183b/blt9d68e3e5a01ecd19/6998c9ecd32e93492ecd7596/IMG_1157.png?branch=production&width=1200&quality=75&auto=webp&crop=1:1)

by 

[Michelle Peng](https://time.com/author/michelle-peng/)

Aug 2, 2026 10:30 AM UTC

New reports suggest companies are now [accelerating hiring](https://www.wsj.com/business/big-companies-are-starting-to-hire-again-defying-predictions-of-ai-wipeout-f4974e99?mod=author%5Fcontent%5Fpage%5F1%5Fpos%5F2) again, and industry CEOs are [backing away](https://www.businessinsider.com/ai-job-impact-losses-shifting-sam-altman-mustafa-suleyman-comments-2026-6) from predictions of an AI job apocalypse. But do the data support this broadly being the case?

A new [AI Labor Market Tracker](https://www.reveliolabs.com/ai-labor-market-tracker/us/july-2026) that launched earlier this week from workforce research company Revelio Labs suggests the answer is yes, at least among the companies embracing AI adoption. The tracker includes data related to labor demand, labor supply, headcount, wages, recruitment trends, and how job responsibilities are shifting, with monthly updates based on the latest Revelio data.


“It shows that \[AI\] adoption and growth and employment can coexist, which does away with these doomsday scenarios” about AI wiping out jobs, argues [Lisa Simon](https://www.linkedin.com/in/lisaksimon/?skipRedirect=true), chief economist at Revelio Labs. We reached out to Simon to learn more about the new tracker’s first release, what it says about the current state of the job market, and what it reveals about AI adoption and headcount. 

Here are excerpts from our conversation, edited for length and clarity: 

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**Why is it so hard to tell how AI is affecting the job market right now?**

There are just so many different aspects to it. What do you mean by the job market? Do you mean hiring? Do you mean hiring in a certain sector for a certain subgroup? Do you mean hiring demand? Do you mean supply? A lot of the effects that we uncover are hidden in the aggregate statistics. 

To give you an example, we have two sets of results on the impact of employment on the labor market from AI. One is what we call the ‘anticipatory effect’ from AI exposure, which looks at highly affected occupations, or occupations with a high share of activities that could be done by AI. We're seeing a pretty stark decline in demand for those jobs, especially for junior-level people. But then when you flip it to adoption, you actually see the opposite. When you look at companies that are already adopting AI, their headcounts are actually growing faster \[than non-adopting companies\]. 


Both can be true: The general demand for highly exposed occupations is going down, even as companies that are successfully adopting some of these tools are growing in headcount.

**Were there any results that surprised you?** 

We track how work is changing at the activity level, based on how employees write about their own jobs or employers write job descriptions. We've seen the rate of churn in work activities double over the past three to six months. Usually we have a four percentage point churn of activities, meaning that when you look at all the activities done in the economy today, and you compare them to this time last year, you'd have to reshuffle 4% of activities to get back to last year's distribution. That number has ticked up to 8%. 

At least some of that seems to be coming from exposed tasks going away, meaning that employers might already be automating some of the work. But the even more surprising bit is that essentially all of that churn—94%—happens within occupations. When you just look at how many people work in which job, you completely miss this transformation that's actually happening within occupations.


**Does that mean jobs are evolving rather than disappearing?**

Exactly, yes. 

**How should employers be responding to the data?** 

AI-adopting companies are growing faster. They were also growing faster pre-adoption, but the most innovative companies in our day and age are still relying on people and are spending a lot on their human capital. That might not have to be true for all companies, but it shows that adoption and growth and employment can coexist.

There’s this whole narrative \[that\] productivity-enhancing technology means less employment. That's only true if you are only producing a finite amount of goods, and that's actually not true for most of the knowledge economy this country operates in. It doesn't mean that the mix of occupations won't eventually change or that some of the very highly exposed occupations will see lower employment, but it does do away—a little bit—with the narrative that everybody will be out of a job.

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