As artificial intelligence reshapes industries worldwide, the debate about its impact on employment has reached a critical juncture. While headlines often focus on job losses, a more nuanced reality is emerging – one where AI simultaneously eliminates some roles while creating entirely new categories of work. This dual dynamic presents both opportunities and challenges for businesses and workers navigating the technological transition.
The Historical Pattern Repeats
Economist Bouke Klein Teeselink from King’s College London reminds us that technological anxiety isn’t new. “Every time jobs automate or we get mechanization or computerization, jobs disappear [and] people freak out and think there are not going to be any jobs,” he notes in a Financial Times interview. “And every time so far, that was false.” Research by Daron Acemoglu and Pascual Restrepo found that half of employment growth between 1980 and 2007 occurred in occupations with entirely new job titles – roles unimaginable just decades earlier.
Complementary Jobs Emerge
AI isn’t just replacing workers – it’s creating new types of employment. Teeselink points to “vibe coding” as an example, where AI generates code based on natural language descriptions. This creates opportunities for complementary roles like code verification specialists. More fundamentally, large language models require massive amounts of new training data, potentially creating what Teeselink calls “a massive industry” in data construction and curation.
The Jevons Paradox in Action
When AI automates parts of production, prices typically fall. Lower prices often increase demand, which in turn requires more human workers for non-automated tasks. This economic principle, known as the Jevons paradox, suggests that automation can actually increase employment in certain sectors. Teeselink uses interior architects as an example: “I’ve never hired an interior architect because it’s out of my budget zone. If it would cost �50… brilliant.” As AI reduces costs for professional services, latent demand could create new opportunities.
Quality Versus Quantity
The crucial distinction lies in which tasks get automated. Teeselink’s research reveals that automating easy tasks makes jobs harder, while automating expert tasks erodes wages but might increase employment. This explains why software developers using AI tools often earn more – AI handles routine coding, freeing them for higher-value work. Conversely, some writing roles incorporating AI pay less because producing words was the core skill being automated.
Industry Leaders Weigh In
K Krithivasan, CEO of Tata Consultancy Services, India’s largest IT services company, dismisses fears of mass layoffs despite recent workforce reductions. “AI is not going to create lay-offs by itself,” he asserts, noting that TCS’s AI revenue grew 17.3% annually to $1.8 billion. Meanwhile, Infosys increased its headcount by 5,000 employees to 337,000, with 90% of its largest clients integrating AI technology.
Policy Responses Take Shape
As the transformation accelerates, governments are considering intervention strategies. UK Investment Minister Lord Jason Stockwood reveals discussions about universal basic income to support displaced workers, suggesting tech companies could fund such programs through windfall levies. “We’re going to have to think really carefully about how we soft-land those industries that go away,” he states. Technology Secretary Liz Kendall acknowledges that “some jobs will go” but believes more will be created, promising government support for adaptation.
The Data Labeling Boom
One concrete example of AI-driven job creation comes from the data labeling sector. Handshake, originally a college hiring platform, launched a human data labeling business serving AI model companies and recently acquired Cleanlab in an acqui-hire deal. Cleanlab’s co-founders – all MIT computer science PhDs – joined Handshake’s research organization, highlighting how AI creates demand for specialized human expertise even as it automates other functions.
A Balanced Perspective
Anthropic CEO Dario Amodei warns of “unusually painful” job market disruption, noting that “humanity is about to be handed almost unimaginable power.” Yet industry data shows a more complex picture. Analysis of millions of job postings reveals that software and quantitative roles requiring AI skills pay more than those without, while some writing roles incorporating AI pay less. The key differentiator appears to be whether AI automates routine tasks (enhancing high-value work) or core competencies (reducing skill requirements).
Looking Forward
The AI employment landscape defies simple categorization. As Teeselink observes, “If we only look at the displacement side, we’re going to miss a lot of what’s going on.” The transformation involves not just job losses but job evolution – new roles emerging, existing roles adapting, and economic principles like the Jevons paradox creating unexpected opportunities. For businesses and workers, success will depend on understanding these dynamics and preparing for a future where human-AI collaboration becomes the norm rather than the exception.