Jobs lost today belong to the skills of yesterday

This article is authored by Hari Krishnan Nair, co-founder, Great Learning.

Over the past two years, I have had hundreds of conversations, with fresh graduates trying to find their footing, mid-career professionals questioning their next move, and seasoned tech leaders navigating complex transitions. No matter where they are on their journey, the sentiment is the same: The ground beneath our careers is shifting faster than ever.

Employment

The recent wave of tech layoffs is not just another downcycle. It is not the dotcom bust, nor is it the 2008 financial crisis replayed. This time, the driver is not an economic collapse but a technological one. Artificial Intelligence (AI) has moved from being a silent partner to, in many cases, the lead executor. Companies are not simply cutting headcount; they are redesigning the very architecture of their workforces for an era where machines take on core responsibilities once entrusted to people.

Layoffs.fyi reports that 80,845 tech employees have already lost their jobs across 176 companies this year. In 2008, job losses were a reaction to collapsing markets. In 2025, they are the result of a fast-moving, irreversible wave of automation. For the first time in history, it is technology, not an economic downturn, that is displacing people on a scale.

AI is no longer an emerging trend to watch. It is here, embedded in the operating fabric of industries. Over just the past year, agentic AI systems have moved from pilots to production, running entire workflows, from generating and debugging code to delivering marketing campaigns, to handling multi-step business processes without human intervention.

Advances in multi-modal AI now allow systems to interpret text, images, audio, and video simultaneously, creating new efficiencies across healthcare, education, and manufacturing. Developers can describe a task in plain language, and AI can deliver production-ready code, a shift that is already making many traditional programming functions redundant.

This is not incremental change; it is structural. Roles in testing, maintenance, and routine IT / customer support are declining. The World Economic Forum’s Future of Jobs Report predicts that by 2030, the world will gain 78 million jobs but lose 92 million, many of them in technology. We are no longer preparing for the future of work. We’re living inside it.

Which raises the only question that matters: How do we stay indispensable?

In an AI-driven economy, the half-life of skills is shrinking dramatically. What gives you an edge today could be irrelevant in a year or two. Skills like machine learning, data science, and generative AI are no longer niche; they are the building blocks of the most competitive products and services in the market right now.

But upskilling is no longer a once-a-year checkbox. It is a continuous process. The winners in this new landscape will be those who treat learning like compounding interest, reinvesting regularly, layering new capabilities over old, and adapting as fast as technology changes.

And this is not limited to tech roles. In finance, AI is redefining how we detect fraud and assess risk. In healthcare, it’s driving breakthroughs in diagnosis and personalised treatment. In marketing, it produces entire campaigns in minutes. Across every sector, the professionals who can guide, challenge, and integrate AI into their work will be the ones who lead.

For individuals, AI skills are not just career insurance but a growth multiplier. For organisations, it is the difference between reacting to change and setting the pace.

In a market shaped by volatility and rapid innovation, the choice is clear: Keep pace with the machines or be replaced by them. Those who adapt relentlessly won’t just survive this shift but will define it.

This article is authored by Hari Krishnan Nair, co-founder, Great Learning.