This perspective reflects the thinking and firsthand insights of Nidhi Gupta, CEO and Founder of SheTO.
2025 showed just how fast the tech industry can change. Last year alone, roughly 120,000 tech workers were laid off, according to Layoffs.fyi. Behind that number were real people with careers disrupted, livelihoods lost, and a sense of stability gone overnight. Looking ahead, thousands more could face the same reality in 2026. Companies are pouring massive amounts of money into AI, and the tools are growing more advanced every day. As AI takes on tasks once performed by humans, smaller teams are becoming the new norm for companies looking to cut costs. The uncomfortable truth is that massive investment in AI is making headcount the easiest place to cut, and people pay the price.
For the workforce, this shift is unsettling, as employees quietly wonder if they’ll be next.
Layoffs are a signal that the old ways of building and scaling tech companies are retiring. For decades, tech leadership success was measured by headcount numbers and how quickly teams could grow. Bigger was believed to be better. And with bigger teams, came promotions. That logic is breaking down now that AI is embedded in everyday work. When tools can automate and streamline large parts of operations, growth for its own sake no longer makes sense. Organizations are shrinking, and leaders are being forced to rethink what real productivity and impact look like.
In 2026, business impact will be front and center. To grow, individuals and leaders will need to focus on the impact they deliver to the customer and the business. Impact will become an important measure of growth especially for leaders. For decades, the tech industry has talked about “T-shaped” leaders. In the AI era, these T-shaped leaders will be noticed and rewarded. What matters is not a title, but whether someone knows the ins and outs of the business and can make the right decisions. The people who thrive in this new era are the T-shaped leaders, those who have expertise in their own area while also understanding the broader business and strategy. They step outside narrow job descriptions to focus on the bigger picture. Success will be defined less by your title and more by whether you can move the business forward.
With increased cross functional collaboration and focus on business impact, the lines between various functions such as engineers, product managers, and data scientists will continue to blur, and eventually disappear altogether. The traditional rules for success no longer apply. AI can already be used as an aid generate requirements, product demos and code. With AI tools improving, and becoming sounding boards for technologists, it will be easier for various functions to cross traditional role boundaries. For example, product managers could easily vibe code a product feature, and at the same time, an engineer will be able to easily come up with impactful product requirements. This is not bad news. All of this, provides greater business visibility to all functions, and frees then up to make an impact regardless of the functional role that they might be boxed into today. AI is also changing what leadership looks like. With smarter tools at their disposal, teams no longer need to be large to get things done, which is flattening organizations across the industry. In this environment, the leaders who stand out are not just strong people managers. They are the ones who can strategically stay ahead of the curve, work cross-functionally, understand the business impact of their work, and deliver results.
There is no doubt that AI will continue to evolve in 2026. As tools improve, they will reshape how work gets done, how teams are structured, and how leadership is defined. For those willing to adapt and think beyond the traditional boundaries, the year offers real opportunities for career growth. Those who cling to old ways will remain stuck in 2025. In the next era, the people and companies that embrace this new reality will be the ones defining the future of tech, and delivering results that actually matter.
