The way large companies use artificial intelligence is changing. For years, AI in business meant experimenting with tools that could answer questions or help with small tasks. Now, some big enterprises are moving beyond tools to AI agents that can actually do practical work in systems and workflows.
This week, OpenAI introduced a new platform designed to help companies build and manage those kinds of AI agents at scale. A handful of large corporations in finance, insurance, mobility, and life sciences are among the first to start using it. That may signal that AI is ready to move from pilot to real operational role.
From tools to agents
The new platform, called Frontier, is meant to help companies deploy what are described as AI coworkers. These are software agents that connect to corporate systems and carry out tasks inside them. The idea is to give the AI agents a shared understanding of how work happens in a company, so they can perform meaningful work reliably.
Rather than treating every task as a separate instance, Frontier is built so that AI agents function in the context of an organisation’s systems. OpenAI says its platform provides the same kinds of basics that people need at work: access to shared business context, onboarding, ways to learn from feedback, and permissions and boundaries.
Frontier also includes tools for security, auditing, and evaluation, so companies can monitor how agents perform and ensure they follow rules.
Who’s using this now
According to OpenAI’s posts, early adopters include Intuit, Uber, State Farm Insurance, Thermo Fisher Scientific, HP, and Oracle. Larger pilot programmes are also said to be under way at Cisco, T-Mobile, and Banco Bilbao Vizcaya Argentaria.
Having companies in different sectors test or adopt a new platform this early shows a move toward real-world application, not internal experimentation. These are firms have complex operations, heavy regulatory needs, and large customer bases, environments where AI tools must work reliably and safely if they are to be adopted beyond experiment.
What executives are saying
Direct quotes from executives and leaders involved in these moves give a sense of how companies view the change. On LinkedIn, a senior executive from Intuit commented on the company’s early adoption: “AI is moving from ‘tools that help’ to ‘agents that do.’ Proud Intuit is an early adopter of OpenAI Frontier as we build intelligent systems that remove friction, expand what people and small businesses can accomplish, and unlock new opportunities.”
OpenAI’s message to business customers emphasises that the company believes agents need more than raw model power; they need governance, context, and ways to operate inside business environments. As one comment on social media put it, the challenge isn’t the ability of the AI models anymore: it is the ability to integrate and manage them at scale.
Why this matters for enterprises
For end-user companies considering or already investing in AI, this points to a change in how they might use the technology. In the past few years, most enterprise AI work has focused on tasks like auto-tagging tickets, summarising documents, or generating content. Such applications were useful, but limited in scope, not connecting to the workflows and systems that run business processes.
AI agents are meant to close that gap. In principle, an agent can pull together data from multiple systems, reason about it, and act; whether that means updating records, running analyses, or triggering actions in tools.
This means AI could start to touch real workflow work not provide assistance. For example, instead of an AI drafting a reply to a customer complaint, it could open the ticket, gather relevant account data, propose a resolution, and update the customer record. This is a different kind of value proposition: Not saving time on a task, but letting software take on parts of the work.
Real adoption has practical requirements
The companies testing Frontier are not using it lightly as they’re organisations with compliance needs, data controls, and complex technology stacks. For an AI agent to function there, it has to be integrated with internal systems in a way that respects access rules and keeps human teams in the loop.
Connecting CRM, ERP, data warehouses, and ticketing systems is a long-standing challenge in enterprise IT. The promise of AI agents is that they can bridge these systems with a shared understanding of process and context. Whether that works in practice will depend on how well companies can govern and monitor these systems over time.
The early signs are that enterprises see enough potential to begin serious trials. For AI deployments to move beyond isolated pilots and become part of broader operations, this is a visible step.
What comes next
If early experiments succeed and spread, enterprise AI could look very different from earlier periods of AI tooling and automation. Instead of using AI to generate outputs for people to act on, companies could start relying on AI to carry out work directly under defined rules.
This will create new roles in addition to data scientists and AI engineers; governance specialists and execution leads will be needed who take responsibility for agents’ performance. There may be a future where AI agents become part of the everyday workflow for large organisations.
(Photo by Growtika)
See also: OpenAI’s enterprise push: The hidden story behind AI’s sales race
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