The Future of Work

We’re grateful to those of you who took part in our first-in-a-series event to help build understanding of how artificial intelligence is an inherently productivity-driving innovation that can drive significant economic growth, and what policies we should put in place to help the country realize that growth and ensure that all Americans have the freedom and opportunity to benefit from this prosperity. As promised, we’re sharing insights and takeaways from the discussions – including sample output from our technical demonstration of how our new Deep Research tool helped a Wisconsin small business owner quickly plan to expand to other states.

The Blueprint outlines policy proposals for how the US can maximize AI’s benefits, bolster national security, and drive economic growth.

The evolving landscape of AI is marked by increasing generality, scalability, and advanced reasoning capabilities—trends exemplified by OpenAI’s "O series" models, which demonstrate the potential for AI to "think" before responding. In remarks by Noam Brown, Researcher at OpenAI, the discussion highlighted two key AI paradigms—pre-training and reasoning—and how models improve as they process more data and compute. These technical advances are not only accelerating model performance but also reshaping the strategic and economic dynamics of AI infrastructure. Complementing this, discussions led by OpenAI’s Chief Economist Ronnie Chatterji and Forum members explored how AI intersects with geopolitics, national security, and economic policy. They examined the balance between democratic and autocratic approaches to AI development, the implications for global alliances, and how AI infrastructure investments influence both economic and military strategy. Together, these conversations underscore the dual trajectory of AI: accelerating technical progress and deepening its role in global policy, infrastructure, and institutional governance.

About the Talk: Much of the value of labor in industrialized economies derives from the scarcity of expertise rather than from the scarcity of labor per se. In economic parlance, expertise denotes a specific body of knowledge or competency required for accomplishing a particular objective. Human expertise commands a market premium to the degree that it is, first, necessary for accomplishing valuable objectives, and second, scarce, meaning not possessed by most people. Will  AI increase the value of expertise by broadening its relevance and applicability? Or will it instead commodify expertise and undermine pay, even if jobs are not lost in net. Autor will present a simple framework for interpreting the relationship between technological change and expertise across three different technological revolutions. He will argue that, due to AI’s malleability and broad applicability, its labor market consequences will depend fundamentally on how firms, governments, NGOs, and universities (among others) invest to develop its capabilities and shape its applications.  

Replay: Learn how AI is reshaping the economy—and why its true impact goes beyond traditional metrics. Earlier this year, the OpenAI Forum hosted a fireside chat featuring Kevin Weil, Chief Product Officer at OpenAI, and Erik Brynjolfsson, Stanford professor and digital economy expert. They explored how AI differs from past technological revolutions, why its benefits often escape traditional economic measurements, and how businesses can integrate AI to augment—not replace—human workers.

In this talk, Professor David Autor discusses the evolving value of expertise in the context of artificial intelligence (AI) and its potential impact on the labor market. He explores how AI could either commodify or complement human expertise, depending on how institutions, governments, and firms invest in its development. Autor also highlights that while AI poses challenges, it presents opportunities to elevate the scope and value of human work.

This discussion between OpenAI's Chief Economist Ronnie Chatterji and LinkedIn’s Chief Economist Karin Kimbrough explores the current and future impact of generative AI on the labor market, highlighting macroeconomic dynamics, evolving skill demands, and global disparities in AI adoption. Kimbrough offers labor market insights based on LinkedIn data, while Chatterji connects these to policy, infrastructure, and human-centered innovation themes promoted by OpenAI.

Joe Fuller, a professor at Harvard Business School, and Ronnie Chatterji, Chief Economist at OpenAI share insights on how AI is reshaping the workforce, emphasizing both the opportunities and challenges it presents. Fuller highlighted the profound impacts of AI adoption across industries, especially in white-collar roles, the shifting skills requirements emphasizing social and interpersonal skills, and the critical role of democratic AI and infrastructure investment for sustained competitiveness and innovation.

OpenAI CFO Sarah Friar joined UC Investments CIO Jagdeep Singh Bachher for an OpenAI Forum conversation on AI’s impact on finance and careers. Friar reflected on her nonlinear path from engineering to finance leadership, emphasizing curiosity, adaptability, and kindness as essential skills for students entering a changing workforce. She described how OpenAI’s finance team is using tools like custom GPTs for investor relations, audit support, and more. While AI is transforming finance tasks and expanding what lean teams can do, Friar stressed that human trust and relationships remain central, especially in fundraising and leadership.

This OpenAI Forum event explored how agentic AI is transforming work far beyond software development. OpenAI Chief Economist Ronnie Chatterji and researcher Drew Johnston shared findings on how Codex adoption is changing workflows, enabling people to delegate longer tasks, run multiple workstreams in parallel, and expand beyond traditional job boundaries. OpenAI teams then demonstrated how agents support real-world work across data science, product design, and sales—from automating KPI reports to building interactive prototypes and managing recurring go-to-market processes. The discussion emphasized that reusable skills, connected workplace tools, and clear organizational support can help teams turn repetitive workflows into scalable systems. Speakers encouraged attendees to begin with an ambitious or frustrating work problem, give the agent strong context, and experiment with what can be delegated or automated.

This conversation focused on how real-world OpenAI usage data can give a more grounded picture of AI’s labor-market impact than simple exposure measures alone. Ronnie Chatterji, Alex Martin Richmond, Daniel Rock, and Gregor Schubert argued that widespread AI adoption does not automatically translate into immediate job loss, and that economists need better ways to distinguish between automation-prone work, demand-expanding work, and roles where human judgment remains central. Across the discussion, the panel described how people are already using AI in practice for writing, technical help, planning, summarization, research, and other day-to-day knowledge work, while also noting that many of the broader productivity effects may take time to show up in traditional data. The conversation also emphasized training, access, and experimentation as key factors in helping workers and institutions benefit from these tools rather than be left behind by them. Audience questions reinforced those themes, especially around what students should study, how to interpret personal-account usage for work, how to measure quality and meaningful work, and what policymakers should watch as adoption accelerates.

In this OpenAI Forum conversation, Artists and AI: Expanding the Creative Process, moderator Allie Sandza Wood speaks with researcher Eric Zhang about how generative AI is reshaping artistic practice, creative productivity, and the economics of creative work. Drawing on his research, Zhang explains that AI can lower technical barriers, help more people turn ideas into finished work, and give artists room to explore many more possibilities. At the same time, faster production can flood the market with generic content, making human taste, intention, curation, and refinement even more important sources of value. The discussion also considers how creative roles are shifting toward direction and orchestration, why provenance may become a premium in human-made art, and how artists and AI companies can build a healthier ecosystem together.

Ronnie Chatterji spoke with Arjun Dutt and Gene Rapoport from Bain about how companies can move from early AI experimentation to business-level impact. The group emphasized redesigning workflows around AI, rather than bolting tools onto existing processes, and using clear metrics like customer response time, win rate, employee experience, and profit impact. They also discussed the need for executive ownership, stronger AI literacy across teams, and practical governance so companies can move quickly without creating new risks. A recurring theme was that AI readiness comes from starting with focused, high-value use cases and learning through implementation.

AI is beginning to reshape how people work across industries. OpenAI's Vice President of Global Policy Ann O'Leary sat down for a conversation with Randi Weingarten, President of the American Federation of Teachers, and Sean McGarvey, President of North America's Building Trades Union (NABTU) about how workers and institutions are responding to that shift, and what it will take to prepare millions of Americans for an AI-driven economy. The conversation focused on the importance of moving from resistance to adoption, with both leaders emphasizing training, certification, and lifelong learning as critical tools for helping workers adapt. They highlighted the growing demand for accessible AI education and the role trusted institutions can play in guiding workers through this transition. At the same time, the discussion underscored the need for stronger coordination across the public and private sectors. As AI accelerates change, investments in reskilling, clear guardrails, and policies that address displacement will be essential to ensure workers can adapt and continue to thrive.

AI is already changing how people work. On March 18, 2026, OpenAI hosted the Participation Economy Forum to bring together labor, education, policy, and industry leaders to talk about how AI is beginning to shape the labor market and what that means for American workers. In this conversation, OpenAI Chief Economist Dr. Ronnie Chatterji and Deputy Secretary of Labor Keith Sonderling discuss the need for public-private coordination around AI literacy training, apprenticeships and rapid reskilling can help Americans build relevant skills and adapt to an AI-driven economy.

In this OpenAI Forum event, Chief Futurist Josh Achiam discussed how his role focuses on helping society prepare for the transformative global impacts of AI while ensuring AGI ultimately benefits all of humanity. Josh emphasized that AI safety is not only a technical challenge but a sociotechnical one that requires democratic input to define acceptable risk and guide how systems are deployed across society. He framed AI as a general-purpose technology comparable to the agricultural, industrial, and internet revolutions—but advancing at unprecedented speed—with the potential to automate economically valuable work and meet global material needs if governed responsibly. Josh highlighted how scaling compute and inference capabilities may reshape geopolitical competition, creating national incentives to build AI infrastructure in order to maintain economic and strategic advantage. This dynamic reinforces the importance of building resilient, democratic AI ecosystems and investing in compute capacity as a foundation of national power and global stability. He also underscored that broad access to AI tools and literacy is critical for economic resilience, enabling workers, firms, and communities to adapt to rapid technological change. Ultimately, Josh positioned the democratization of AI access as essential for ensuring productivity gains, scientific advancement, and social benefits are widely shared rather than concentrated.

The event was an OpenAI Forum conversation focused on how people can use ChatGPT to navigate job searches, interviews, and career transitions with more clarity and confidence. Hosted by Natalie Cone, the session featured Selena Ma, Head of Recruiting Programs at OpenAI, who shared a recruiter’s perspective on preparation, storytelling, and skill translation across industries. The discussion highlighted ChatGPT as a practical coach for interview prep, confidence-building, self-reflection, and translating experience into compelling resumes and narratives. Speakers emphasized career agency, encouraging participants to define their own non-negotiables, avoid unhealthy comparison, and pursue paths aligned with their strengths and motivations. The event addressed nontraditional and nontechnical candidates, underscoring that AI companies hire across many functions and value transferable skills, curiosity, and adaptability. Audience Q&A covered topics including authenticity when using AI, standing out in competitive markets, career pivots into AI, and the role of projects, portfolios, and networking. Overall, the session framed AI as an accessible, democratizing tool that supports learning, workforce mobility, and personal growth across career stages.

OpenAI’s Chief Economist Ronnie Chatterji sat down with Columbia University economist Daniel Björkegren for a conversation about what AI could change for low- and middle-income countries, and what still has to happen for those gains to reach people. Daniel’s research paper followed about 500 teachers in Sierra Leone and more than 40,000 messages, showing why cost can make the web a poor fit in bandwidth-constrained settings. His research found that the average page used about 2.5 megabytes while an AI answer used only a few kilobytes, and found AI was over 700 times more data-efficient than loading a web page. In the paper’s latest update, AI was 98% cheaper, opening a wider discussion about local usefulness, trust, education, health, and new paths to growth. The conversation also marked Daniel’s selection as one of the first recipients of the OpenAI Economic Research Exchange, special recognition from a field of nearly 500 applications.