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.

Geoffrey Mosoti Nyakiongora of the Gates Foundation joined the OpenAI Forum for a conversation on how AI could help public health teams prepare for future outbreaks. He discussed what COVID revealed about the speed of public health crises and the fragility of healthcare systems in resource-constrained settings. Geoffrey also explained how AI can help researchers work through large healthcare datasets, identify unusual patterns earlier, and test possible responses faster. The conversation explored how these tools could give public health leaders more time to allocate resources, prepare hospitals, and act before a crisis spreads.

The forum featured a conversation with Tibo Sottiaux, Head of Codex at OpenAI, about how Codex is evolving from a developer tool into a broader AI agent for knowledge work, personal productivity, and complex multi-step tasks. The discussion explored how people are using Codex to reduce friction, manage information overload, automate repetitive work, and coordinate projects across tools and sources. Tibo also shared thoughts on enterprise adoption, including trust and security, as well as where agents are headed next with more persistent, goal-oriented workflows.

This conversation framed ChatGPT as a tool that helped Liam Corrigan move from managing the noise of daily life to focusing more fully on the things that mattered most. Liam described using the models to reduce friction across training, work, and relationship logistics, from nutrition research and scheduling to travel planning and everyday decision-making. Natalie Staudacher added a product-side perspective, emphasizing how the breadth of use cases surprised her and how the models became useful in both professional and personal contexts. The discussion repeatedly returned to the idea that AI is most valuable when it helps people become more present, protect time, and stay connected to human judgment, discipline, and teamwork rather than replacing them.

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.

This OpenAI Forum conversation explored how NASCAR is using AI in practical, people-centered ways across analytics, racing operations, and workforce enablement. Derek Thomas shared how NASCAR combines race data with years of fan feedback to identify patterns, evaluate race quality, and make faster, more confident decisions that improve the sport for fans. Rich Bowman focused on what it takes to scale AI successfully inside a legacy organization, emphasizing that adoption depends on trust, clear governance, useful training, and repeatable workflows, not just access to powerful tools. Together, they framed AI not as a replacement for people, but as a “jet pack on your back” that reduces friction, speeds up work, and helps teams turn ideas into action more effectively.

The San Antonio Spurs Community Impact organization, OpenAI Academy and the Positive Coaching Alliance teamed up to bring together coaches, parents, and community leaders on Sunday to explore how AI can support learning, coaching, and youth engagement—on and off the court.