Executives stress the urgency of delivering secure, compliant AI solutions to drive broader enterprise adoption, even as upfront compute costs and losses persist.

OpenAI’s new chief revenue officer emphasizes long-term profitability through an enterprise-focused strategy, prioritizing customer outcomes and a robust enterprise platform.

The company is reframing its focus from model prowess to building an enterprise platform that delivers tangible customer outcomes and scalable business models.

Industry dynamics show a shift toward becoming a platform company—integrated, secure AI ecosystems—rather than just delivering high-quality models.

A major hurdle remains: none of the players have achieved the security and compliance level many businesses require for widespread AI agent deployment.

Experts stress that scaling and differentiation, rather than immediate profits, are critical for sustaining growth in a crowded AI market.

Despite billions in revenue signals from subscriptions, both firms face enormous infrastructure costs and ongoing losses, with OpenAI citing substantial financial obligations backed by partners like Microsoft and Nvidia.

Google with Gemini and cloud giants like Microsoft, Google, and Amazon are central players, where incumbents often win initial cloud/AI deals, leaving AI model providers to compete for later-stage wins.

The AI landscape is locked in a high-stakes race between Anthropic and OpenAI to monetize AI through broader business adoption and consumer access, including new advertising models and enterprise platforms.

OpenAI publicly pushed back, with its CEO calling advertising models dishonest and noting that ChatGPT has a larger U.S. free user base than Claude overall.

Investors remain attracted to frontier-model potential despite heavy losses and the enormous compute needs, signaling belief in scalable differentiation.

Denise Dresser highlights OpenAI’s emphasis on enterprise platform building and customer outcomes over immediate revenue as the central strategic driver.