AI: The Job Creator?

The rapid rise of artificial intelligence is often framed as a threat to jobs.  As an efficiency machine poised to automate work faster than labor markets can adapt. But the empirical record emerging from recent research tells a more nuanced story. While disruption is real, so are productivity gains, business expansion and new forms of employment. Before forecasting the end of the work force, it’s worth examining what the data actually shows.

AI Is Being Adopted Rapidly, But Unevenly

AI uptake has accelerated dramatically over the past two years. In 2024, 78% of organizations worldwide reported using AI, up from 55% in 2023. At the worker level, adoption has also been swift: by late 2024, roughly 23% of employed U.S. workers were using generative AI for work at least once per week.

Yet beneath these headline numbers lies a significant gap between experimentation and full integration. As of mid-2025, only about 9–10% of U.S. firms reported using generative AI in regular production workflows. In effect, AI is widespread but still far from fully embedded in most organizations.

This uneven adoption matters, because many of the economic and labor effects associated with AI depend on sustained, scaled use rather than pilots or AI being leveraged into isolated tools.

Productivity Gains Are Material and Measurable

Across studies, AI’s most consistent near-term effect is productivity improvement. Economists estimate that generative AI could raise labor productivity by around 15% in the U.S. and other developed markets once fully integrated into business operations.

At the macro level, these gains compound. One projection suggests AI adoption could lift GDP levels by approximately 1.5% by 2035 and nearly 3% by 2055 relative to a no-AI scenario, implying a permanent increase in economic output.

Firm-level data reinforces this picture. Companies that significantly increased AI usage experienced 9.5% higher sales growth over five years compared to peers with lower AI adoption. In a controlled field experiment at a Fortune 500 company, customer service agents equipped with an AI assistant increased productivity by about 14%, measured by issues resolved per hour.  Interestingly, the largest gains were seen among less-experienced workers.

The productivity effect is already showing up in real business performance.

What Has Happened to Jobs So Far?

Despite widespread concern, there is little evidence of broad, economy-wide job losses attributable to AI to date. As of the end of 2023, overall employment levels had not experienced significant net declines due to AI, with job reductions in highly automatable roles being largely offset by gains elsewhere, particularly in firms that became more productive through AI adoption.

By 2024–2025, this pattern largely persisted. While AI adoption accelerated sharply across sectors, labor market impacts remained incremental rather than systemic. Looking forward, Goldman Sachs estimates only about a 0.5 percentage point uptick in the jobless rate during the AI transition, with new tech-enabled roles and productivity gains eventually offsetting many displaced jobs.

Overall, employment growth in AI-using firms through 2025 remained positive, reinforcing the view that—at least in this phase—AI has functioned more as an amplifier of organizational capacity than as a broad labor-substituting force.

In fact, firms that adopt AI extensively tend to grow faster. A longitudinal study of U.S. companies from 2010 to 2023 found that large increases in AI use were associated with roughly 6% higher employment growth over five years compared to non-adopters. Revenue growth at these firms appears to enable, rather than suppress, hiring.

Notably, even jobs with high exposure to AI have sometimes expanded. In companies implementing AI, highly AI-exposed, high-wage roles grew by approximately 3% as a share of employment over five years, reflecting how productivity gains can allow firms to scale output and headcount simultaneously.

As MIT Sloan professor Lawrence Schmidt summarized: firms adopting AI “don’t necessarily need to shed workers; they can grow and make more stuff and use workers more efficiently than other firms”.

New Roles, New Hiring and Selective Displacement

AI adoption is also creating demand for new skills. In a mid-2025 survey, 11% of service-sector firms and 7% of manufacturers reported hiring additional workers specifically because of AI, often looking for employees proficient in AI or data-analytics tools. Around 10–15% of firms expected to create new AI-related positions within six months.

At the same time, displacement is not absent, rather it is selective. Research shows AI tends to automate tasks rather than entire occupations. When AI can perform nearly all tasks of a job (such as in some business and finance roles) employment in that role may decline sharply—by roughly 14%. Conversely, when AI automates only a subset of tasks, employment in those roles can increase as workers shift to higher-value activities.

Some early warning signs are emerging, however. Occupations with higher AI exposure saw larger increases in unemployment rates between 2022 and 2025, particularly in certain tech and administrative roles. And while layoffs directly attributed to AI remain rare (around 1% of service firms reported cuts), about 13% anticipate future staff reductions as AI capabilities advance.

A Longer Historical Lens

History provides useful context. Labor-saving technologies have repeatedly caused short-term disruption followed by longer-term adjustment and job creation. Past data suggests that a 1% productivity gain from technology can raise unemployment by about 0.3 percentage points in the short run, but these effects typically dissipate within roughly two years as new roles and industries emerge.

Long-run employment data underscores this pattern. Roughly 60% of workers in 2023 were employed in occupations that did not exist in 1940, and over 85% of U.S. employment growth since 1940 has come from newly created roles and industries driven by technological change.

Forward-looking forecasts vary, but recent projections are increasingly optimistic. The World Economic Forum’s 2025 Future of Jobs update estimates that by 2030, AI and related technologies could create 170 million jobs globally while displacing about 92 million, implying a substantial net increase in employment.

What This Means for Sustainability Professionals

Taken together, the data suggests that AI is less a blunt job-destroying force and more a productivity amplifier.  One that reshapes work, redistributes tasks and rewards those who can use it effectively. For sustainability professionals, this has direct implications.

The scale and complexity of sustainability challenges (climate risk, supply-chain analysis, regulatory reporting, transition planning and the ever-present need for innovation) are expanding faster than human-only approaches can manage. As AI becomes embedded across business functions, professionals who can work alongside these tools will be better positioned to preserve, expand their value and share of voice.

The evidence from the broader world of industry is stark.  Firms and workers that adopt AI tend to grow faster than those that do not. The same dynamic is likely to hold in the world of sustainability. AI-enabled practitioners can analyze larger datasets, test scenarios more quickly and translate sustainability challenges into business-relevant insights with greater speed and precision.

Ultimately, the question is less whether AI will eliminate sustainability jobs and more whether sustainability professionals will be equipped to operate in AI-augmented organizations. History suggests that those who adapt early tend to shape the next generation of roles, rather than be displaced by it.

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