The Top 100 Gen AI Consumer Apps

TECH & AI

a16z just published the 7th edition of its Top 100 AI Consumer Apps leaderboard, where they rank the top web and mobile AI products by monthly traffic. Worth having a close look to better understand AI consumer behavior.

Is AI truly threatening the majority of our jobs?

No. Today, AI seems more like a pretext to justify layoffs or boost stock prices than a reality. Many announcements have touted AI-driven productivity gains allowing for headcount reductions and cost cuts. From Klarna's over-promises to the PR stunts of American tech giants, we need to take a step back.

Yes, on paper, it is easy to assume that task automation (call centers, accounting, HR, data entry, data analysis and synthesis, graphic design, translation, etc.) risks eliminating many jobs. The more manual and simple a task is, and the simpler its underlying process, the higher the risk.

Some speak of 50% of jobs being threatened. A recent Boston Consulting Group (BCG) study mentions 15% of US jobs within 5 years. In France, a study by the Treasury Department of the Ministry of the Economy, published in the summer of 2026, indicates that "3.8% of work content is currently at risk of automation by generative AI, rising to up to 16.3% within two to five years."

However, I believe the actual short-term impact of AI on work is overestimated, while its long-term impact is underestimated. Amara's Law (named after the former president of the Institute for the Future) applies to AI as well. Most current layoffs are not due to AI, but rather to the economic context, poor corporate management, or the pursuit of excess profits. Projections regarding AI's impact are overstated: automating a task does not necessarily mean eliminating a job.

In the long term, modeling the impact of productivity gains is highly complex, and these gains typically unfold over cycles much longer than a few years. The reality is that we do not yet know how to model Schumpeter's famous "creative destruction" in the age of AI.

What if, conversely, AI created jobs?

In early September, The Economist ran the headline: "The jobs apocalypse is postponed. The boom is here."

In the United States, AI has reportedly created one million jobs, compared to 200,000 job losses attributed to AI since mid-2023. A portion of these creations consists of infrastructure jobs resulting from the data center construction boom: electricians, cooling technicians, engineers... Given the climate impact and the low ratio between jobs and invested capital, one can legitimately question the societal value created.

That being said, what is most interesting is that, contrary to what is sometimes reported, it appears many knowledge-worker roles are growing: analysts who master these tools to better question generated insights, corporate AI managers, etc. LinkedIn reports 640,000 jobs specifically related to AI created between 2023 and 2025.

What are the real questions AI poses to business leaders?

Beyond the net balance of job creation versus destruction, the essential issue is understanding that AI will change how most employees work. There will be major impacts at both the microeconomic and macroeconomic levels.

The microeconomic challenge for companies is a cultural and organizational transformation in which middle management will play a vital role.

It requires a CEO who is both visionary and embodies change through a "top-down" approach, alongside employees driving innovative projects with a "bottom-up" approach. As is often the case with multi-year transformations, the key to success will rely on HR and middle managers.

The macroeconomic challenge is indeed the overhaul of the social contract and the modernization of capitalism.

The analysis I find most relevant is that of Yann Ferguson, Scientific Director of LaborIA at Inria.

In an interview with Stratégies a few months ago, he explained simply that the societal role of work was being impacted by AI. To quote him: "The phenomenon of 'shadow AI' raises the fundamental problem of the invisible transformation of the collective workforce." Furthermore: "Studies show that using a technological tool during the learning phase crushes the trial-and-error process that allows one to improve. There is also the risk that the apprentice will call upon their mentor less, thereby missing out on the learnings tied to their experience."

This is a highly complex subject that requires nuance and humility, promising fascinating debates and reflections in the years to come.

By Thomas Husson, independent analyst.

I believe in quality over quantity so don’t expect daily or even weekly updates, but rather bi-monthly or monthly news – assuming I’ll only write when I have something meaningful to share.