OpenAI has unveiled Frontier, a platform designed to help enterprises deploy AI agents at scale. According to recent data, 75% of enterprise workers report AI has enabled them to complete tasks previously out of reach. Companies across industries, from manufacturing to finance, are seeing measurable benefits. At a major manufacturer, production optimization tasks dropped from six weeks to one day. A global investment firm used agents to free 90% more salesperson time for client interaction, while a large energy company increased output by up to 5%, generating over a billion in additional revenue.
Despite these gains, many organisations face an “opportunity gap” between what AI models can do and what is actually deployed in business workflows. Challenges stem not from model capabilities but from fragmented systems, governance, and the difficulty of moving agents past pilot stages. Frontier aims to bridge this gap with an end-to-end platform that helps build, deploy, and manage AI agents capable of real work.
How Frontier Works
Frontier equips AI agents with the skills necessary for enterprise work. Agents gain shared business context, onboarding, experience-based learning, and defined permissions and boundaries. They can access multiple systems and applications without requiring organizations to replatform. Companies can integrate existing AI, data, and third-party applications, ensuring agents operate efficiently across cloud and local environments.
AI agents on Frontier can plan, act, and solve problems by reasoning over data, executing tasks, and using tools in a reliable execution environment. They build memory over time, improving performance and adapting to evolving workflows. Performance is monitored and optimized through built-in evaluation tools, helping agents learn what constitutes quality outcomes.
Security and governance are core components of the platform. Each agent operates with a distinct identity, clear permissions, and guardrails suitable for sensitive or regulated environments. This allows enterprises to scale AI adoption while maintaining control and compliance.
Frontier’s approach combines technology with operational expertise. OpenAI teams work directly with enterprises to develop best practices for deploying agents in production. Feedback loops between deployment and research help refine both the platform and the AI models themselves, accelerating adoption and impact.
Early Adoption
Frontier is already in use at HP, Intuit, Oracle, State Farm, Thermo Fisher, and Uber, with pilots conducted at BBVA, Cisco, and T-Mobile. The platform aims to move AI agents from isolated demonstrations to dependable enterprise coworkers capable of improving productivity across functions. In a related move, OpenAI also introduced the Codex app for macOS, a desktop interface designed to help developers manage multiple AI agents in parallel and supervise long-running software projects more effectively, extending the Frontier vision to software development teams.