Major Companies Deploy AI Agents in Business Operations: Intuit, Uber, State Farm Lead the Way

The way large companies use artificial intelligence is changing dramatically. 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 simple tools to AI agents that can actually perform practical work within 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 programs to real operational roles.

From Tools to Agents

The new platform, called Frontier, is designed 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, enabling them to 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 organization's systems, providing access to shared business context, onboarding, feedback mechanisms, and appropriate permissions and boundaries.

Frontier also includes tools for security, auditing, and evaluation, so companies can monitor how agents perform and ensure they follow established rules and compliance requirements.

Early Adopters Leading the Way

According to OpenAI's announcements, early adopters include:

• Intuit
• Uber
• State Farm Insurance
• Thermo Fisher Scientific
• HP
• Oracle

Larger pilot programs are also reportedly underway at Cisco, T-Mobile, and Banco Bilbao Vizcaya Argentaria.

Having companies across different sectors test or adopt a new platform this early demonstrates a significant move toward real-world application, not just internal experimentation. These are firms with complex operations, heavy regulatory requirements, and large customer bases — environments where AI tools must work reliably and safely to be adopted beyond experimental phases.

What Executives Are Saying

"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."
— Senior Executive from Intuit

OpenAI's message to business customers emphasizes that the company believes agents need more than raw model power; they require governance, context, and ways to operate inside business environments. The challenge isn't the capability of AI models anymore — it's the ability to integrate and manage them at scale.

Why This Matters for Enterprises

For companies considering or already investing in AI, this represents a fundamental shift in how they might leverage the technology. In recent years, most enterprise AI work has focused on tasks like:

• Auto-tagging support tickets
• Summarizing documents
• Generating content

While these applications were useful, they were limited in scope and not connected to the workflows and systems that run core business processes.

AI agents are designed to close that gap. In principle, an agent can pull together data from multiple systems, reason about it, and take action — whether that means updating records, running analyses, or triggering actions in various tools.

This represents a different kind of value proposition: not just saving time on a task, but letting software take on complete portions of the work.

Real Adoption Has Practical Requirements

The companies testing Frontier are not approaching this lightly — they're organizations with stringent compliance needs, data controls, and complex technology stacks. For an AI agent to function effectively in these environments, it must be integrated with internal systems in a way that:

• Respects access rules and permissions
• Keeps human teams in the oversight loop
• Maintains audit trails and compliance standards
• Integrates seamlessly with existing infrastructure

Connecting CRM, ERP, data warehouses, and ticketing systems has been 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 indicate that enterprises see enough potential to begin serious trials. For AI deployments to move beyond isolated pilots and become part of broader operations, this represents a visible and significant step forward.

What Comes Next

If early experiments succeed and spread, enterprise AI could look dramatically 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 and governance frameworks.

This evolution will create new organizational roles. In addition to data scientists and AI engineers, companies will need:

• AI Governance Specialists
• Agent Performance Managers
• Workflow Integration Architects
• Compliance and Audit Leads for AI Operations

There may be a future where AI agents become integral parts of everyday workflow for large organizations, fundamentally transforming how work gets done at enterprise scale.

(Photo by Growtika)