#future of work

#future of work

If you sell the tool, you're in a race against the model. But if you sell the work, every improvement in the model makes your service faster, cheaper, and harder to compete with. A company might spend $10K a year for QuickBooks and $120K on an accountant to close the books. The next legendary company will just close the books.

Companies aren't rewarded for making decisions that support people or social goods. Companies are rewarded for profit. They're rewarded for being first to market. When robotics cuts labor costs or increases output, deployment becomes a business decision. Whether displaced workers are retrained or supported elsewhere depends on public policy.

The linear career path changed somewhere between the rise of the gig economy and the rise of artificial intelligence. Companies are restructuring. Some industries may collapse entirely in the next five years. I've gone from studying law to studying software entrepreneurship to being a self-improvement essayist. My career is still an "experiment in progress." The world of work is changing. And I'm changing with it.

We talk constantly about age-in politics, in leadership, in debates about retirement and the future of work. Yet we rarely stop to ask a simple question: What is age, exactly? Most of us rely on a single number, as if people were stamped with a vintage year like bottles of wine. But age is far from a fixed or universal metric. It is multidimensional, deeply unequal, and increasingly misleading when used as a shortcut for ability, potential, or readiness.

In September, the consulting firm Accenture made headlines when it acknowledged it had "exited" 11,000 employees who couldn't be retrained to adapt to AI. On a recent earnings call, CEO Julie Sweet explained the decision bluntly, saying that "the workforce needs new skills to use AI, and new talent strategies and related competencies must be developed." It's a tough-but-true reality that thanks to AI, tomorrow's jobs will look radically different than they do today.

Aki Ito is our chief correspondent on careers, a huge topic for Davos - and for us. She asked people across business tough questions about the future of work (believe me, I was in the room) to help bring insights for your success. She also moderated a conversation with chief people officers from companies across the business world. You'll see her takeaways from that soon.

Business Insider is on the ground at the World Economic Forum in Davos, Switzerland, this week, and we want to take you along with us.

As work, technology, and learning change quickly, gaining the right skills has become essential. So, instead of just wanting "a better job," people now aim to build the skills employers will need in 2026. This focus makes more sense because skills are trackable, actionable, and linked directly to job growth. Plus, skill-based goals fit better into busy lives. You can study in short sessions, see your progress, and use what you learn right away.

AI is changing how companies hire, train, and lead, and in the process, the chief human resources officer's role is expanding. Today's top HR leaders are becoming AI strategists, helping their organizations navigate the next wave of workplace transformation. "The old model of HR was employees over here, technology over there," says Thomas Hutzschenreuter, a university professor at the Technical University of Munich (TUM). "But the new model of work is human-AI collaboration." AI is a coworker now, he says, and that means that "HR has a bigger mandate. They need to understand not just people and culture, but go deeper into the strategy, the business, and the technology itself."

A leader at the Big Four firm EY recently told me that the firm has introduced an AI tool to help their employees navigate the uncertainty around jobs that the new technology is creating. It's part of an internal training program known as AI Now 2.0, which prompts EY employees to answer a series of questions about their job, day-to-day responsibilities, and overall deliverables.

AI has rapidly become a reliable coding assistant for many developers -- so much so that many are wondering about the future of the entire profession. Entry-level coding jobs are dwindling for recent grads as teams offload junior tasks to AI assistants; at the same time, experts cite the real limitations of these tools as proof that engineers will never actually become obsolete.

Cyberpsychology investigates the psychological processes related to technologically interconnected human behavior, informing disciplines such as human-computer interaction (HCI), computer science, engineering, psychology, and media and communications studies.5 The field explores how digital technologies influence and transform human cognition, emotion, and social interaction, as well as the reciprocal impact these human elements have on technologies. At its core, cyberpsychology seeks to understand the dynamic interplay between humans and technology.

The speed of that displacement could require government intervention to help support the workforce, executives said. What they're saying: "As with most things, when an exponential is moving very quickly, you can't be sure," Amodei said. "I think it is likely enough to happen that we felt there was a need to warn the world about it and to speak honestly." Amodei said the government may need to step in and support people as AI quickly displaces human work.

The short answer: AI isn't replacing developers-it's changing what developers do. While AI is undoubtedly transforming the programming landscape, we're witnessing an evolution in how software is built, with AI serving as a powerful collaborator rather than a replacement. Understanding this shift is crucial for anyone concerned about the future of programming jobs. The Current State of AI in Development Today's AI coding tools are impressively capable.

Atlassian made a one-way door decision in 2020 to permanently embrace distributed work, creating a framework for flexibility and collaboration that may inspire other companies.

In short, they want generalists. Just be enough. You don't need to be everything. You just need to be enough of many things.

Cowen argues that educational institutions should focus on teaching how to effectively use AI tools instead of avoiding them, preparing students for an AI-driven job market.