The way large companies use artificial intelligence is changing. For many years, AI in business has meant experimenting with tools that can answer questions and assist with small tasks. Some large companies are now moving beyond tools to AI agents that can perform actual work on their systems and workflows.
This week, OpenAI introduced a new platform designed to help enterprises build and manage these types of AI agents at scale. A few large companies in finance, insurance, mobility, and life sciences are the first to use the service. This could indicate that AI is ready to move from pilot to actual operational role.
From tools to agents
The new platform, called Frontier, aims to help companies deploy what are called AI co-workers. These are software agents that connect to corporate systems and perform tasks within them. The goal is to give AI agents a common understanding of how work works within a company, ensuring they can perform meaningful work.
Frontier is built so that its AI agents work in the context of your organization’s systems, rather than treating every task as a separate instance. OpenAI says its platform provides the same kinds of basics people need at work, including access to a shared business context, onboarding, ways to learn from feedback, and permissions and boundaries.
Frontier also includes security, audit, and assessment tools so businesses can monitor agent performance and ensure they’re following rules.
Who is using this now?
According to OpenAI’s post, early adopters include Intuit, Uber, State Farm Insurance, Thermo Fisher Scientific, HP, and Oracle. Cisco, T-Mobile and Banco Bilbao Vizcaya Argentaria are also said to have larger pilot programs underway.
Testing or adopting new platforms at this early stage by companies in a variety of sectors signals a move toward real-world applications rather than in-house experiments. These companies have complex operations, stringent regulatory needs, large customer bases, and are in environments where AI tools need to operate reliably and securely if they are to adopt them beyond experimentation.
Management’s statement
The first-hand accounts of executives and leaders involved in these movements provide insight into how companies view this shift. A senior Intuit executive commented on the company’s early adoption on LinkedIn: “AI is moving from being a ‘tool to help’ to being an agent to help. Proud Intuit is an early adopter of OpenAI Frontier, building intelligent systems that remove friction, expand what people and small businesses can accomplish, and open up new opportunities.”
OpenAI’s message to enterprise customers emphasizes that the company believes agents need more than raw modeling capabilities. It requires governance, context, and a way to operate within a business environment. As one social media comment stated, the challenge is no longer the ability of AI models, but the ability to integrate and manage AI models at scale.
Why this matters to businesses
For end-user companies considering or already investing in AI, this signals a shift in the way the technology is used. Over the past few years, most of the enterprise AI work has focused on tasks such as automatic ticket tagging, document summarization, and content generation. While useful, these applications were limited in scope and not connected to the workflows and systems that run business processes.
AI agents aim to fill that gap. In principle, agents can collect data from multiple systems, reason about it, and act on it. Whether that means updating a record, performing an analysis, or triggering an action in a tool.
This means that AI may start to influence the actual workflow work rather than providing assistance. For example, instead of drafting a response to a customer complaint, AI can open a ticket, collect relevant account data, suggest a solution, and update the customer record. This is a different kind of value proposition. Instead of saving time on a task, let the software do some of the work for you.
Actual implementation has realistic requirements
The companies testing Frontier are organizations with compliance needs, data management, and complex technology stacks, so they don’t use Frontier lightly. For AI agents to work there, they must 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 perennial challenge in enterprise IT. The hope for AI agents is that they can bridge these systems with a common understanding of process and context. Whether it actually works depends on how well companies manage and monitor these systems over time.
Early signs are that companies see a good chance of starting full-scale trials. This is a tangible step toward moving AI beyond isolated pilots and becoming part of a broader operation.
what happens next
If early experiments are successful and widespread, enterprise AI could be very different from early AI tools and automation. Instead of using AI to generate output for people to act on, companies may start relying on AI to perform tasks directly based on defined rules.
This will create new roles in addition to data scientists and AI engineers. It requires governance experts and execution leaders who are responsible for agent performance. There may be a future where AI agents become part of the daily workflow of large organizations.
(Photo provided by Groutica)
See also: Pushing OpenAI to the enterprise: The hidden story behind the AI sales race
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