Tech • IA • Crypto
OpenAI's CFO Presents the Future of Finance with University of California’s Chief Investment Officer
7/10TL;DR
Artificial intelligence is rapidly reshaping finance by automating routine work, enhancing decision-making, and shifting skill demands toward curiosity, adaptability, and human judgment.
KEY POINTS
AI transforms core finance operations
Finance teams are increasingly embedding AI across foundational processes such as quote-to-cash, order-to-payment, tax, and treasury. Tasks once constrained by time and staffing limits are now automated, enabling faster execution and deeper analysis. This shift allows finance functions to operate with smaller teams while expanding their strategic impact.
From sampling to full verification
Traditional accounting practices like audit sampling are being replaced by comprehensive AI-driven checks. Instead of reviewing a small subset of transactions, AI systems can analyze 100% of invoices or records, improving accuracy and strengthening financial controls. This marks a transition from scarcity-based workflows to data abundance.
Custom AI tools reshape investor relations
Finance teams are deploying tailored AI systems trained on internal data such as investor presentations and diligence materials. These tools can generate consistent, factual responses to investor inquiries, assist in multilingual communication, and streamline fundraising interactions. The approach reduces manual preparation while maintaining high standards of accuracy and tone.
Automation of complex global compliance
AI is simplifying labor-intensive compliance tasks, including the completion of international tax forms. Systems can retrieve forms, interpret their structure, and automatically populate them with relevant data. This reduces administrative burden and allows tax professionals to focus on strategy and oversight rather than manual data entry.
Lean teams with expanded capabilities
AI adoption enables relatively small finance teams—around 200 personnel in large global operations—to manage vast, complex organizations. At the same time, new specialized functions such as economic research and pricing analytics are emerging within finance, reflecting a shift toward insight generation rather than pure reporting.
Human relationships remain central
Despite automation, fundraising and investment decisions continue to rely heavily on trust, credibility, and interpersonal connection. Investors prioritize leadership quality and long-term relationships, underscoring that AI augments but does not replace human judgment in high-stakes financial decisions.
Changing nature of finance work
Many routine and repetitive roles are expected to diminish, while others will evolve significantly. Entirely new job categories are also emerging as AI capabilities expand. Rather than eliminating work wholesale, AI is redistributing effort toward higher-value activities.
Key skills: curiosity, adaptability, kindness
The most critical skills in an AI-driven finance landscape are identified as curiosity, to explore new tools; adaptability, to navigate rapid change; and kindness, which strengthens collaboration and long-term professional relationships. Technical proficiency alone is no longer sufficient.
AI literacy becomes essential in education
Universities are being encouraged to integrate AI directly into coursework and learning methods. Instead of restricting AI use, institutions are shifting toward teaching students how to use it effectively while still demonstrating independent understanding and mastery.
AI lowers barriers to technical work
Tools now enable professionals without deep programming backgrounds to engage in tasks like coding and data analysis. This democratization is expanding participation in technical domains, with fields such as software engineering continuing to grow despite automation concerns.
CONCLUSION
AI is redefining finance by automating routine work and amplifying strategic insight, while placing greater emphasis on human skills that technology cannot replicate.