A new wave of analysis from the World Economic Forum casts AI as a major driver of change in the global job market, presenting a nuanced view that contrasts with early fears of sweeping job losses. The Future of Jobs Report 2025 presents a picture in which AI and related technologies could create a substantial number of new roles while also rendering others obsolete. In net terms, the report projects a positive balance: about 170 million new jobs worldwide by 2030 against roughly 92 million positions that could disappear, yielding a net gain of around 78 million roles. The findings come as businesses grapple with automation incentives, skill demands, and the need to prepare workforces for a transformed operating environment. This release arrives at a time when discussions about artificial general intelligence and broader automation are prominent in policy and corporate circles. The WEF frame emphasizes strategy, retraining, and talent pipelines as central levers for navigating this transition.
What the Future of Jobs Report 2025 Reveals
The report synthesizes data from a representative cross-section of the global economy, drawing on input from 1,000 companies that collectively employ about 14 million workers. It marks the WEF’s biennial effort to map hiring trends, skill needs, and the evolving structure of work so that policymakers, business leaders, and workers can align planning with anticipated shifts. The headline statistics highlight a dual reality: while a significant share of firms anticipate adjustments that include reductions in labor due to automation, a larger portion also foresees net growth in employment and opportunity driven by AI technologies. The report’s broader analysis moves beyond the immediate fear of layoffs and delves into how organizations plan to realign operations, retool their talent pools, and embrace new capabilities. It emphasizes that AI is not simply a threat to existing jobs but a driver of demand for new kinds of expertise and collaboration between humans and machines. This framing aligns with the WEF’s mission to facilitate informed, proactive decision-making among global economic actors. The document also stresses that AI’s impact will vary by industry, region, and firm size, underscoring the importance of targeted skills development and sector-specific strategies. In addition to workforce projections, the report identifies skill priorities that are expected to dominate recruitment through 2030 and beyond. It paints a picture of a labor market characterized by shifting roles, new pathways for career progression, and an intensified focus on continuous learning and professional development.
Net Job Growth and the Structure of Change
A central takeaway of the report is the net positive job trajectory projected through 2030, even as some roles contract or fade away. Specifically, the analysis estimates that AI and related technologies could generate 170 million new positions globally by 2030, while 92 million roles may be eliminated as automation expands. The resulting net increase of 78 million jobs signals a substantial expansion of employment opportunities, albeit with a redistribution of tasks and responsibilities across the economy. This outlook suggests that the employment landscape will be reshaped rather than simply contracted, with many sectors evolving to rely more heavily on digital capabilities and automated processes. The data imply a pivot toward roles that leverage AI to augment human performance, rather than replace human labor wholesale. As firms navigate this transition, they are expected to reorient business models, product lines, and service offerings to capitalize on AI-enabled efficiencies and new capabilities. The findings are framed as indicative of a broader shift toward knowledge-intensive work, where technology serves as a catalyst for productivity gains and economic growth. The report notes that approximately half of employers anticipate reorienting their business strategies in response to AI advancements, highlighting the strategic nature of these changes. In parallel, around two-thirds of firms plan to hire talent with specialized AI skills, signaling a concerted push to build in-house capability in data analysis, machine learning, and related disciplines. At the same time, roughly 40 percent of organizations expect to reduce headcount where AI can automate tasks, illustrating the tension between opportunity and displacement in different operational contexts. This combination points to a complex labor market dynamic characterized by skill upgrading, redeployment, and selective downsizing where automation yields clear efficiency gains. The survey-based evidence underpinning these conclusions reflects the diverse experiences of firms of varying sizes and across multiple sectors, underscoring the need for adaptable workforce strategies that can scale with technological progress.
The Talent Transformation Narrative
Beyond the headline numbers, the WEF report emphasizes a clear transformation in the talent landscape. It highlights that AI, big data, networks, cybersecurity, and general technological literacy are projected to be the most in-demand skill sets by 2030. This ranking signals a shift toward competencies that enable organizations to collect, interpret, and protect data; build and secure digital networks; and operate advanced analytic and automation tools. The verdict positions AI proficiency as the single most influential driver of hiring decisions, with 86 percent of surveyed companies expecting AI to reshape their operations by 2030. In practical terms, this means that job descriptions across industries are likely to evolve to require a blend of technical know-how, analytical thinking, and the ability to work with automated systems. The emphasis on these capabilities reflects a broader understanding that AI integration is not merely about replacing tasks but about enabling workers to tackle more complex, strategic, and creative assignments. The report suggests that organizations that prioritize upskilling in AI and related disciplines will be better positioned to capture the value offered by emerging technologies and to sustain competitive advantage in a rapidly changing market.
Declining Roles and the Shifting Creative and Administrative Landscape
The WEF report also identifies specific job categories that are projected to decline as automation and AI-enabled workflows become more prevalent. Notably, postal service clerks, executive secretaries, and payroll staff appear on the list of roles shrinking fastest, with declines driven by a combination of automation, digital workflow systems, and process optimization. The drivers of these changes extend beyond AI alone and reflect broader technological adoption, organizational restructuring, and efficiency initiatives that reduce the need for routine, manual administrative tasks. For the first time in the report’s scope, graphic designers and legal secretaries are noted among faster-declining positions, with the WEF tentatively linking these developments to the expanding capabilities of generative AI in both creative and administrative workstreams. This inclusion underscores how AI’s capabilities are translating into tangible shifts in the demand for certain specialized skill sets within the creative sector and legal administration. The net effect of these declines is contextualized within a larger framework of job reallocation, as workers in affected fields are encouraged to pivot toward roles that maximize the strengths of human judgment, creativity, and interpersonal engagement in areas where AI augmentation remains imperfect or more challenging.
Why These Declines Matter
The projected declines illustrate a broader pattern of job market evolution under the influence of AI-enabled productivity gains. They underscore the importance of proactive career planning and support for workers in roles susceptible to automation. The WEF notes that even as certain positions wane, the overall employment picture remains positive if organizations invest in retraining and redeployment strategies. The emergence of new roles and the expansion of AI-enabled responsibilities imply a dynamic labor market where skills evolve rapidly and where workers may need to transition across occupations rather than simply advance within a single track. The analysis encourages policymakers and business leaders to consider how to smooth these transitions, ensure access to training, and provide pathways for workers to upgrade their qualifications as automation technologies permeate more aspects of the economy. In practical terms, this means designing vocational programs, apprenticeships, and continuous education opportunities that align with the new demand for AI literacy, data fluency, and system design capabilities, among other competencies.
Human–Machine Collaboration as the Dominant Workplace Mode
A central theme of the report is that the future of work is likely to be defined by deep human–machine collaboration rather than wholesale worker replacement. The data suggest that a substantial majority of firms—about 77 percent—intend to launch retraining programs aimed at enabling current workers to collaborate effectively with AI systems during the period from 2025 to 2030. This emphasis on retraining reflects a belief that the most effective productivity gains will come from humans working alongside intelligent tools, rather than from abrupt job displacement. The strategy focuses on creating complementary workflows where automation handles routine or high-volume tasks, while human workers contribute strategic thinking, supervision, quality control, and nuanced decision-making. In addition to retraining, the report indicates that roughly 70 percent of organizations plan to hire specialists capable of designing AI tools, signaling a growing demand for roles such as AI architects, tool designers, and system integrators who can tailor AI solutions to specific business needs. Another 62 percent seek employees adept at working with these AI systems, highlighting the need for operational fluency with automation technologies in the daily work environment. This constellation of workforce plans points to a transformation of job roles, with a premium placed on interoperability between human expertise and machine intelligence. The emphasis on retraining and AI-tool design underscores the recognition that adopting AI is not a one-off technology purchase but a long-term, strategic process that requires ongoing learning, governance, and adaptation. The collective implications for employers include building robust learning ecosystems, creating clear career pathways within AI-enabled roles, and ensuring equitable access to upskilling opportunities across the workforce.
Practical Pathways for Firms and Workers
To translate these intentions into tangible outcomes, organizations will need structured training programs, clear competency frameworks, and measurable upskilling objectives. Employers may implement modular learning sequences that cover foundational AI literacy, data interpretation, ethical and governance considerations, and hands-on practice with AI toolsets. For workers, the path involves gradual progression—from basic data and digital literacy to advanced skills in AI tool usage, workflow design, and cross-functional collaboration with automated systems. The implications extend to performance management, with new metrics that capture contributions to AI-enabled processes, the quality of human–machine collaboration, and the ability to troubleshoot or augment automated decisions. Beyond individual development, teams will benefit from collaborative frameworks that define responsibilities, delineate the boundaries of automation, and establish protocols for ongoing evaluation of AI systems’ impact on productivity and safety. The WEF underscores that investment in retraining during this transitional period will be a key determinant of how successfully the job market absorbs automation, highlighting the practical necessity for policy alignment, corporate provide-upskilling, and accessible learning opportunities for workers at all levels of experience.
Davos, Policy Dialogues, and the Global Implications
The timing of the report’s release places it in the context of the World Economic Forum’s annual Davos gathering, where leaders from governments, business, and civil society convene to discuss the future of work, technology governance, and economic policy. In Davos and beyond, AI’s impact on the global workforce is expected to be a central topic of conversation, with emphasis on how to translate the report’s insights into coherent policy and practical business strategies. The discussions focus on balancing innovation with social protection, ensuring that workers have access to retraining, and designing safety nets and opportunity pathways that reflect the realities of an AI-enabled economy. The Davos discourse is expected to emphasize collaboration among public institutions, private firms, and educational systems to align curricula with the needs of a changing labor market. This alignment includes improving data literacy at scale, fostering public-private partnerships for workforce development, and exploring policy mechanisms to support continuous learning in the face of rapid technological progress. The report thereby contributes to a broader conversation about how societies can reap the benefits of AI-driven productivity while mitigating disruptions that affect workers’ livelihoods and long-term career prospects.
Long-Term Outlook, Open Questions, and Perspectives on Universal Solutions
Beyond the concrete projections, the Future of Jobs Report 2025 contributes to an ongoing debate about the net impact of AI on employment. While the near- to mid-term forecast signals a net positive trajectory in job quantity, the ultimate question remains whether the transition will be smooth and inclusive for workers across sectors and regions. Some observers suggest that the shift could be gradual, with knowledge workers adapting incrementally as automation takes on more routine tasks. Others contend that the changes could be more abrupt, requiring rapid upskilling and robust social support systems to prevent mismatches between skills and job opportunities. In this context, discussions around universal basic income (UBI) gain renewed attention as possible buffers in times of disruption. The report references public conversations around UBI as one approach to addressing potential income gaps, noting that experiments and trials have been funded by proponents who see basic income as a way to stabilize livelihoods during periods of retraining, career transitions, or economic restructuring. These considerations are framed as exploratory and hypothetical, rather than prescriptive, acknowledging that policy solutions will need to be tailored to local conditions and evolving economic dynamics. Open AI perspectives, including those from industry leaders, contribute to the broader discourse on whether or how general intelligence aims to transform the workplace, and the pace at which such capabilities will mature remains a focal point for ongoing reporting and analysis. While there is considerable interest in AGI and advanced forms of intelligence, the report emphasizes that current workflows and skill needs are already shifting in meaningful ways, with or without breakthroughs that redefine intelligence itself. The discussion around these longer-term horizons remains an important area for policymakers and industry to monitor, as they will shape education systems, labor market regulation, and investment priorities for years to come.
The Open Questions Ahead
- How will regional disparities in digital infrastructure and education influence the pace of AI-driven job growth and displacement?
- What policies are most effective in accelerating retraining while ensuring access for workers in precarious or underserved communities?
- How will organizations balance speed to adopt AI with the need for robust governance, ethics, and risk management?
- To what extent will universal basic income or other social protection mechanisms be adopted, and under what conditions?
- What are the long-term consequences for wage growth, career progression, and job satisfaction as human–machine collaboration becomes the default mode of operation?
Notable Context: The OpenAI Perspective and the AGI Horizon
In discussions surrounding the employment implications of AI, notable viewpoints have highlighted potential scenarios in which AI could replace large portions of the labor force for certain tasks. In 2023, prominent figures in the AI community discussed the possibility that automation might affect the “median human” worker, pointing to a future in which a significant share of routine tasks could be automated. While these projections are subject to debate and contingent on the pace of technological development, they contribute to ongoing concerns about job security and the need for adaptive skills. The broader ambition of many AI researchers and developers includes advancing artificial general intelligence (AGI) as a comprehensive, broadly capable system that can perform a wide range of tasks with human-like versatility. Alongside this ambition, there is sustained interest in exploring policies and programs, such as universal basic income trials, that examine how to provide a basic safety net in a society where automation performs an increasing share of work. These conversations underscore the importance of proactive planning, investment in education and training, and thoughtful design of social supports as technologies evolve.
What This Means for Workers, Firms, and Society
The Future of Jobs Report 2025 underscores that AI is a major disruptor and enabler in equal measure. For workers, the implications are clear: continuous learning and flexibility will become essential as job requirements evolve. For firms, the imperative is to align strategic planning with rapid reskilling, to create clear pathways for employees to transition into AI-enabled roles, and to invest in tools and teams capable of designing and operating AI systems. For policymakers and civil society, the findings highlight the need for robust educational pipelines, social protections, and collaborative governance to maximize benefits while reducing the pain of transitions. The data points to a world where AI-driven productivity can translate into real economic growth and expanded opportunities, provided that the human workforce is equipped with the skills and support to participate in this new economy. The Davos moment and related policy discussions are likely to accelerate concrete actions in workforce development, industry innovation, and international cooperation to ensure that the benefits of AI are broadly shared and sustainably managed.
Conclusion
The World Economic Forum’s Future of Jobs Report 2025 presents a nuanced, forward-looking view of AI’s impact on employment. While a sizable portion of firms anticipate reductions in headcount due to automation, the overall projection indicates net job growth driven by AI-enabled demand for new roles and capabilities. The emphasis on retraining, AI-skills development, and human–machine collaboration suggests that the work landscape will be reconfigured rather than simply reduced. The report highlights specific in-demand skills, including AI, big data, networks, cybersecurity, and general technological literacy, with a strong expectation that AI will transform operations across most sectors by 2030. It also identifies declines in certain job categories, notably in administrative and creative roles, as AI capabilities expand in generative and automation contexts. The Davos platform and broader policy conversations are poised to translate these insights into practical strategies for education, workforce development, and social protection. In the longer term, the sustainability of net positive employment will depend on effective retraining programs, equitable access to opportunity, and thoughtful governance of AI deployment that respects workers’ livelihoods and dignity. As organizations continue to experiment with AI-driven workflows, the careful orchestration of skills development, career pathways, and supportive safety nets will be essential to realizing the potential of AI to create meaningful, lasting gains in global employment.
