OpenAI has launched Frontier, a new platform designed to help enterprises build, deploy, and manage AI agents that can do real work across the business.
The announcement comes as companies struggle to move AI agents beyond isolated pilots and into production environments where they can meaningfully impact customer experience and operational efficiency.
According to OpenAI's own data, 75% of enterprise workers say AI helped them do tasks they couldn't do before. The technology is clearly capable. The problem is getting it into the hands of teams who need it most.
In the official OpenAI blog, the company claimed that “AI has let teams take on things they used to talk about but never execute.
“What's slowing them down isn't model intelligence, it's how agents are built and run in their organizations.”
That's the gap Frontier is trying to close.
HP, Intuit, Oracle, State Farm, Thermo Fisher, and Uber are among the first to adopt the platform. Existing customers like BBVA, Cisco, and T-Mobile have already piloted Frontier's approach.
Joe Park, Executive Vice President and Chief Digital Information Officer at State Farm, explained the appeal:
“Partnering with OpenAI helps us give thousands of State Farm agents and employees better tools to serve our customers.
“By pairing OpenAI's Frontier platform and deployment expertise with our people, we're accelerating our AI capabilities and finding new ways to help millions plan ahead, protect what matters most, and recover faster when the unexpected happens.”
Building AI Coworkers, Not Just Chatbots
Frontier's approach treats AI agents like new employees rather than standalone tools. That means giving them shared context, onboarding processes, hands-on learning with feedback, and clear permissions and boundaries.
The platform connects siloed data warehouses, CRM systems, ticketing tools, and internal applications to create what OpenAI calls a “semantic layer for the enterprise.”
This shared business context helps agents understand how information flows, where decisions happen, and what outcomes matter.
From there, agents can reason over data, complete complex tasks, work with files, run code, and use tools. As they operate, agents build memories that turn past interactions into useful context for future work.
Built-in evaluation and optimization features also help human managers and AI coworkers understand what's working and what isn't.
Each agent has its own identity, with explicit permissions and guardrails designed to make them usable in sensitive and regulated environments.
Where the Impact Shows Up
OpenAI pointed to several early use cases that highlight Frontier's potential in customer-facing and operational roles.
At a major manufacturer, agents reduced production optimization work from six weeks to one day.
Elsewhere, a global investment company deployed agents end-to-end across the sales process, opening up over 90% more time for salespeople to spend with customers.
In one hardware troubleshooting example, millions of test failures previously required engineers to spend thousands of hours each year manually hunting down root causes.
Frontier-powered agents reduced root-cause identification from roughly four hours per failure to a few minutes by pulling together simulation logs, internal documents, workflows, and code to run end-to-end investigations.
In a customer experience context, that level of acceleration can directly impact satisfaction and retention.