A few days ago, while browsing the news – as I usually do – one headline caught my attention: Moderna, the pharmaceutical company, announced it was merging its Human Resources and Technology departments into a single entity to be led by a Chief People and Digital Technology Officer.
In collaboration with OpenAI, Moderna developed around 3,000 personalized GPTs to automate tasks ranging from supporting clinical trials to drafting regulatory responses. This effort has significantly increased agility in workforce planning.
Curious about this development, I looked for more examples and found several – from IBM to Unilever, and from Accenture to Amazon and SAP. Many companies are increasingly linking their HR and IT functions to modernize and optimize workforce management.
AI has long been used as a virtual assistant to support routine tasks such as summarizing content and preparing basic analyses. But as AI capabilities continue to grow, the line between “assisting” and “replacing” white-collar work is becoming increasingly blurred.
IBM, for example, has implemented AI-powered virtual assistants to handle certain HR inquiries. Tools like Watsonx Orchestrate automate repetitive tasks, while platforms such as YourLearning offer personalized, AI-based employee training. These innovations have reduced operational costs and enabled faster, more customized employee support.
Unilever has adopted AI tools such as Pymetrics for cognitive assessments via gamified exercises, and HireVue for AI-driven interview analysis. These tools streamline resume screening, assess behavior, enhance workforce diversity, and reduce recruitment time by up to 75%.
Accenture’s approach centers on optimizing workforce allocation to align with business outcomes. They employ digital twins for predictive modeling and use AI simulations to test HR strategies before implementation.
Amazon’s focus has been on increasing efficiency in hiring and retention, while also emphasizing ethical AI use. Their systems monitor employee productivity and behavior and are continually refined to minimize bias.
SAP, meanwhile, has introduced over 25 generative AI features, including tools for summarizing content, mapping skills, and assisting with writing. They’ve paired this with a strong focus on data ethics and governance. As a result, they’ve achieved up to 45% faster service delivery and greater accuracy in HR assessments.
These success stories suggest that AI’s evolution will continue to reshape work. Strategic AI adoption — aimed at improving performance, reducing costs, and enhancing the employee experience — will likely accelerate in the near term.
Yet significant and unresolved challenges remain. Ethical deployment, transparency, and workforce reskilling are essential to ensure a sustainable transition.
But perhaps most troubling is the emerging practice of defining “who does what”: the clear-cut assignment of tasks either to humans or AI systems, often driven solely by operational efficiency.
Concerns are mounting over how quickly this shift will unfold and whether the current workforce will have time to adapt. It raises profound questions about the future of labor, dignity in work, and the balance of power in organizations.
Historically, technological revolutions have disrupted both production processes and workforce structures. But the speed and scale of disruption caused by artificial intelligence could eclipse past experiences, fueling alarming predictions.
In a recent interview with CNN (where he echoed comments made to Axios), Dario Amodei, CEO of Anthropic—one of the world’s leading AI companies—offered a warning to governments and the public.
According to Amodei, AI could eliminate up to half of all entry-level white-collar jobs, pushing unemployment to 10 – 20% within the next one to five years (in USA). He urged companies and governments to stop “sugar-coating” the potential consequences: widespread job loss in fields such as tech, finance, law, and consulting – particularly in junior roles.
Is this already happening?
Meta’s Mark Zuckerberg has suggested that midlevel coding jobs could soon disappear – potentially this year. Elon Musk has posted on X predicting that AI agents, including models like ChatGPT and DeepSeek, will outperform and replace doctors and lawyers, triggering mass global unemployment by delivering more precise medical and legal analysis.
Recent headlines support these concerns. Axios reported that Microsoft recently laid off 6,000 workers – around 3% of its workforce – including many engineers. Walmart is cutting 1,500 corporate jobs to streamline operations. CrowdStrike, a Texas-based cybersecurity firm, eliminated 500 positions (5% of its staff), citing an inflection point where AI is reshaping every industry.
Aneesh Raman, Chief Economic Opportunity Officer at LinkedIn, noted in a New York Times op-ed that the “bottom rungs” of many careers—junior developers, paralegals, first-year associates, and entry-level retail workers—are already being displaced by chatbots and other automation tools.
Whether this scenario unfolds at the predicted pace or not, and even if its exaggerated, urgent policy responses are needed. The tax system, for one, may need a rethink.
Amodei has proposed a “token tax”: a small percentage (e.g., 3%) of revenue earned each time an AI model is used and make profit, which would be collected by governments and redistributed. These funds could help slow job displacement by supporting retraining and skill development, giving workers a fair chance to adapt – and encouraging executives to do the same.
Leadership will be critical. Companies and governments must face the reality head-on, prepare people and organizations, and guide the transition with clarity and purpose. That’s the only way to ensure that this transformation is managed as smoothly – and as humanely – as possible.
