Artificial intelligence is now being treated as core economic infrastructure, and OpenAI CFO Sarah Friar states that most organizations are only beginning to tap into its potential.
Friar shared her reflections in a post on Monday following her attendance at the World Economic Forum (WEF) annual meeting in Davos last week. She noted that this year felt different, with AI no longer being a peripheral discussion or a future investment. Instead, AI is now being assessed as fundamental economic and strategic infrastructure, comparable to geopolitics, energy, and security.
Friar, who has served as OpenAI’s finance chief since June 2024, pointed to “capability overhang” as a recurring theme at Davos. This concept describes the disparity between AI’s current capabilities and the actual value that organizations are able to realize. According to Friar, there is a disconnect between the advanced AI capabilities available today and the limited ways in which most individuals and companies are utilizing them, with sophisticated tools still only minimally integrated into daily workflows and decision-making processes.
She emphasized that “Experience and execution are closing that gap faster than any amount of rhetoric.” Friar added, “At OpenAI, we see that frontier users use seven times the amount of intelligence than the average user—they’re going deep on coding, deep research, and pushing the models to really be thought partners.”
In line with this, OpenAI recently published new research documenting this phenomenon. The researchers observed a distinct country-level disparity that is not solely attributable to income. Across more than 70 countries where ChatGPT is widely adopted, some nations utilize advanced AI features three times more per person than others.
Interestingly, while major economies like the U.S. and India have the highest total number of users, and smaller affluent nations such as Singapore and the Netherlands lead in per capita AI usage, advanced AI adoption is becoming widespread globally. Meanwhile, countries like Pakistan and Vietnam are among the leading global users of agentic tools, employing them more than twice as frequently as the average.
Essentially, certain countries are already leveraging AI to address more complex challenges and accelerate progress, irrespective of their resource levels. These early adopters are experiencing tangible productivity improvements: their workforces can concentrate on more intricate tasks, develop new products and services, and expedite innovation in ways that foster economic growth and enhance living standards, according to OpenAI’s findings.
Another observation that resonated with Friar in Davos was the WEF CFO gathering, which “reinforced how pragmatic finance leaders are.” She added that there is a “broad conviction that AI is inevitable, but deployment hinges on ROI, clean data, and simpler systems; this is a change-management challenge, not a belief gap.”
This focus on concrete outcomes is mirrored in OpenAI’s recent performance. In an interview with Fox’s Maria Bartiromo last week, Friar stated, “An IPO isn’t off the table; it’s a question of when.”
OpenAI was valued at approximately $500 billion in its most recent completed share sale. In 2023, revenue reached $2 billion in annual recurring revenue; this figure rose to $6 billion in 2024 and surged to over $20 billion in 2025, according to Friar’s January 18 statement.
This revenue growth closely paralleled an increase in computing capacity. OpenAI’s computing capacity expanded from 0.2 gigawatts (GW) in 2023 to 0.6GW in 2024 and approximately 1.9GW in 2025.
Beyond infrastructure investments, OpenAI is also venturing into new consumer-focused areas. The company announced earlier this month the launch of ChatGPT Health—a specialized experience within ChatGPT where users can securely link medical records and wellness apps such as Apple Health, Fitbit, and MyFitnessPal to further personalize their interactions. The company affirmed that it would not use personal medical data for training its models.
The company’s strategy of combining infrastructure expansion with practical, domain-specific applications aligns with the pragmatic approach to AI deployment that Friar observed among finance leaders in Davos.