Software Dev Efficiency Gains Aren’t Driving Layoffs

With AI-related layoffs drawing plenty of attention as companies continue to boast about heavy increases in efficiency, two leaders in the nearshoring space are showing hesitance to embrace what is quickly becoming the new expectation — using those efficiency gains to justify job cuts.

But in today’s market, which Applaudo CEO and Co-Founder Jose Giammattei says is “always wanting more,” the time savings are instead being used to create better products.

Instead of wiping out roles, AI is reshaping them — driving deeper specialization, expanding project capacity and ultimately improving the products delivered to clients.

Giammattei said with the ever-increasing focus on leveraging AI, Applaudo has recognized the need for education among C-suite executives on the capabilities of these platforms. While old school business acumen is still very much in demand, the need for leaders who truly understand how AI can be leveraged is at an all time high.

‘Now it’s Not the Number of People … It’s the Capacity and Services’

Vladimir Mendoza, vice president and country manager in Mexico for SoftServe, said the company has been rolling out generative AI both in internal operations and in client delivery work. In some cases, the results have been dramatic.

One internal efficiency gain came from Microsoft Copilot.

“I think that we have gained between 20 to 30% efficiency where most of those efficiencies is writing emails, you can double the efficiency, but in other areas, you may not have that much optimization,” Mendoza said.

But the most transformative use cases are on the delivery side.

“One of the cases that we have applied with … a company reduces manual design to code efforts by 85%. So in one internal project, we reduced UI development time frame from 36 hours to just five hours using a multi agent system,” he said. “These can translate faster time to market and consistent design implementation across the product.”

While AI is sometimes said to slow down senior developers — due to extra review or refactoring steps — Mendoza says SoftServe’s approach avoids bottlenecks by integrating AI across the entire software lifecycle.

“Instead of applying just this solution in one of the stages, you will be able to materialize more of the optimizations. Because for example, if we just focus on coding, then it gets stuck at unit testing.”

The efficiencies aren’t leading to layoffs; they’re allowing SoftServe to redeploy talent toward higher-value work.

“That will allow us to have more capacity and to give more value to services to our customers. … Now, it’s not the number of people that you have working. Now it’s more about the capacity, the services, that you can provide, with maybe a short base of employees, but that will drive higher impact in value to the customers.”

‘The Market Always Wants More’

Giammattei has built a company-wide initiative, Newton, that embeds AI tools into every business unit — from HR to finance to operations. But the focus starts at the top. “We make sure we have our C-suite executives fully trained and capable in using and understanding AI technologies. If we want to lead into this area, we must have leaders that are proficient in the use of the technology and understanding of it.”

He sees AI not as a replacement, but as an amplifier.

“AI won’t replace the human, we believe … it will definitely automate and make things easier for us, but at the end, the human input is still necessary to validate,” he said.

Like SoftServe, Giammattei stresses that efficiency gains are largely passed on to clients in the form of richer products or faster delivery. “We believe we’re getting between 20 to 30%. There’s some positions that you get even more than 30% of efficiency. But all of that goes directly to the customer.”

Giammattei said there is software now being developed in days compared to what would have taken years decades ago, and he said the market is ripe with clients wanting to use that increase in computing power to produce higher quality outcomes.

“The market always wants more,” he said, and for proof of that Giammattei looked to none other than OpenAI, the company behind ChatGPT, which recently launched GPT-5.

“Do you see their costs going down?” he asked. “No way. They are doing crazy big investments into the technology.”

In other words, the newfound efficiency doesn’t shrink the work — it expands the scope of what can be delivered within the same budget.

“Every product has an infinite vision, and what’s limiting that vision is budget. When you have a higher output, you won’t probably expect to pay more. Basically, the product and the quality is just getting a lot better.”

From Labor Arbitrage to Deep Specialization

Both Mendoza and Giammattei agree that AI is accelerating the shift away from the old nearshore model of pure labor arbitrage and toward industry-specific, value-driven services.

Mendoza says SoftServe is pairing AI with domain expertise in sectors like retail, healthcare, BFSI and manufacturing. Giammattei says Applaudo is leaning into sports, entertainment, hospitality, airlines and banking. In both cases, AI is used to deliver specialized solutions faster, with less human time spent on repetitive work.

Specialization also strengthens client trust.

“If you are a company that is taking advantage of this higher root output … it’s because you’re becoming a preferred vendor. And the race is in that … whoever is dominating and using this is at an advantage,” he said.

Efficiency Without the ‘Slash and Burn’

This strategic use of AI stands in stark contrast to the narrative of AI-driven mass layoffs. In fact, both leaders caution against drawing a straight line between efficiency gains and headcount cuts.

Giammattei has healthy skepticism regarding AI-related job loss announcements, especially from public companies, saying, “(A lot of times) they don’t really explain that while jobs may be getting cut, they’re getting replaced somewhere else. They didn’t actually reduce headcount.”

He said he feels this dynamic often plays out due to the high expectations placed on public companies.

Mendoza sees the risk in framing AI purely as a cost-cutting tool. The real opportunity, he argues, is in redefining what teams can deliver. “The value driven is about the solutions, the experience, the frameworks that we utilize to fasten the time to market … by leveraging these specializations … to be ready to be taken as part of the integral solutions for the customers.”