AI-driven efficiency: Are smaller teams the future—or just the latest productivity myth?

The corporate world is currently obsessed with AI-driven efficiency. While AI can’t yet replace most human employees, it can certainly accelerate various tasks and processes, thus boosting individual productivity and employee efficiency. 

One of the side effects of this has been a dip in hiring—managers seem to be increasingly choosing smaller teams and betting on AI to help pick up the slack. The Future of Jobs Report 2025 reveals that 40% of employers “anticipate reducing their workforce where AI can automate tasks”.

We can already observe this out in the wild where, for example, despite the continued rally of US tech companies, hiring for software developers has flatlined. At the same time, companies aren’t particularly happy with AI, with MIT reporting that 95% of generative AI pilots at companies are failing. 

It appears that companies are stuck—they’re trying to make smaller, AI-driven teams and failing. 

Are smaller teams the future? Or just the latest productivity myth? 

Let’s explore the PROs and CONs of AI-powered efficiency so you can judge for yourself. 

4 PROs of AI-powered efficiency

At the heart of it all lies a simple formula: if one person with AI can do the job of two or more people, and AI costs less than hiring someone, then AI can save a company significant resources.

But beyond the obvious “work is done faster by fewer people” argument, here are four more reasons why managers are tempted to integrate AI and downsize:

1. First-mover advantage

Integrating AI early on may prove invaluable. The tech is here to stay and, eventually, it may quite literally penetrate every workflow everywhere. Early adoption puts you ahead in experience and practical integration. You’re learning which prompts actually work, which APIs are stable, and how to structure a business that doesn’t rely on massive headcount. 

When the improved AI tools eventually arrive, your lean team will already have the muscle memory to use them, while your competitors will still be trying to figure out how to log in.

2. Less overhead & faster communication 

We’ve all been in those meetings—the ones that could have been an email, but involve twelve different people who all need to weigh in. Large teams suffer from a high communication tax. The more people you have, the more time is spent on Slack, in stand-ups, and managing personalities rather than doing work. 

A smaller, AI-driven team moves like a startup. Decisions are made over a quick coffee (or a single message), and because the AI handles the documentation and summaries, everyone stays on the same page without the bureaucratic bloat.

3. 24/7 availability 

AI doesn’t get burnt out, and it doesn’t need to sign off at 5 PM on a Friday. From providing instant customer support to working through the night on data-heavy tasks, AI agents don’t need to sleep. 

For a small team, this is the ultimate equalizer. You can maintain a global presence and handle some issues in real-time without needing to hire a night shift or a distributed team across four time zones. It allows a skeleton crew to punch way above its weight class.

4. The compound interest of AI progress 

AI will probably get better in the near future. The shortcomings we see now—the hallucinations, the clunky interfaces, the security gaps—are being worked on as we speak. If you build a smart, small team structure today, those productivity gains will likely double or triple when the technology matures. 

5 CONs of AI-driven efficiency

While the efficiency gains look great on a spreadsheet, the reality of managing a shrunken team is often far messier. If you cut the people before you’ve mastered the process, you’re being reckless.

1. Forcing broken work models 

Today’s AI is incredible in some ways, but absolutely atrocious in others. Forcing AI use in certain departments can be counter-effective, leading to an increased workload per person. 

Anecdotally, there are more and more stories when a manager demands to double the AI usage, but employees spend more time fighting with a chatbot to get a usable result than they would have spent just doing the work themselves. You lose human judgment, and you end up with a team that is busy but not actually productive.

2. Putting your faith in a black box with no accountability 

Unless you expect your employees to stringently verify every single AI output—which would eat away the majority of the productivity gains you were looking for—then you have to just trust that the results are accurate. 

But AI doesn’t care about your company’s reputation. If a hallucinated fact makes it into a client report or a buggy piece of AI-generated code crashes your app, who is responsible? When you shrink your team, you remove the human safety nets that catch these errors. You’re essentially staking your company’s future on a tool that holds zero accountability.

3. Fragility and single points of failure 

In a team of ten, one person getting sick is a hurdle. In a team of two, one person getting sick is a catastrophe. Smaller teams have zero redundancy. If your developer who understands the AI-integrated codebase decides to quit, or your marketing specialist who knows how to prompt the brand voice is out with the flu, your entire operation stalls. By cutting the numbers in your workforce, you’ve removed the resilience that allows a company to survive the unexpected.

4. Losing the next generation 

AI’s ability to complete basic tasks has been a major point of contention for entry-level hiring. After all, why hire a junior Gen Z to write basic copy or clean data when a bot can do it for $20 a month, right? But this creates a terrifying hollowed-out talent pool. 

If you don’t hire juniors today, you won’t have seniors in five years. You’re effectively destroying your own talent pipeline. Fresh professionals need those basic tasks to learn the nuances of the industry. Without them, the middle and upper management of the future will be nonexistent.

5. The echo chamber effect 

AI lacks common sense and cultural nuance. It can only regurgitate what it has already seen. Without a diverse group of human perspectives to challenge an AI-generated strategy, a small team is much more likely to release a product that is logically sound but culturally or ethically tone-deaf. 

Moreover, this leads to a weaker company culture and worse creative collaboration. When everyone is just managing their own bot, the spontaneous brainstorms and productive disagreements that lead to true innovation simply stop happening.

AI-driven efficiency—should you go all in?

So, is the “smaller team” a myth? Not entirely. But the version being sold by many tech evangelists—where you fire half your staff and let the AI take over—is probably a recipe for a corporate existential crisis.

The secret sauce shouldn’t be subtraction, but rather augmentation. The real winners won’t be the companies with the smallest headcounts, but the ones who find the middle ground.

This means combining AI power with a smart team structure that still values human judgment. It means creating clear workflows where AI handles the drudgery, but humans provide the soul and the oversight. Most importantly, it means shifting away from measuring how much AI your team uses and starting to measure meaningful outcomes and where your time goes. 

Whether you’re a lean startup or a legacy firm experimenting with AI, the goal shouldn’t be to see how much work you can squeeze out of a chatbot, but how much meaningful progress your team is making.

This is where DeskTime comes in. Instead of guessing whether your smaller team is actually more efficient or just drowning in “workslop”, DeskTime provides the ground truth through automatic time tracking. With real, hard data at hand, that’s when you can start making decisions that will actually move the needle, instead of just swaying with the hype. 

It’s free to try, so give it a shot. 

Article written by

Viesturs Abelis

A fan of crunching complex topics into digestible bites, Viesturs helps tech companies – and startups in particular – convey their unique stories to broader audiences. In addition to his work on DeskTime’s blog, you’ll come across his writing in Tech.eu, The Next Web, Crunchbase, and more.