IBM and Microsoft Launch Imagine Enterprise AI Agent Platform

By Amara Osei

IBM Consulting and Microsoft put more than 6,000 pre-built AI agents and assets behind a jointly developed platform, Imagine Enterprise, announced on November 10, 2026. The platform creates, runs and oversees AI agents tailored to industry processes, and it pairs IBM's industry and delivery expertise with Microsoft's AI, data, cloud, identity and security technologies.

The companies jointly invested in and co-developed the platform, according to IBM's launch overview. Imagine Enterprise connects to an enterprise's existing data, processes and systems. The design goal: organizations can adapt pre-built capabilities without replacing their current technology environment or assembling each component themselves.

How does the deployment model work?

Clients have three options. They can engage IBM Consulting to deploy and operate the platform, collaborate with IBM on enterprise-scale implementations, or choose self-management. Forward-deployed engineers from both IBM and Microsoft can work directly with customer teams on qualifying engagements to move projects from experimentation into production.

Initial industry frameworks cover financial services, insurance and retail. Manufacturing, energy, the public sector and mobility appear only as possible future additions — a signal of where the partners see near-term demand versus long-horizon bets.

What sits inside the stack?

The architecture splits responsibilities between the two vendors. IBM Consulting Advantage's Process Studio and Context Studio connect agents to an organization's own data and processes. Microsoft Foundry, GitHub Copilot and Copilot Studio coordinate agents with enterprise systems. Microsoft Fabric, Microsoft 365, Entra, Purview, Defender and Azure provide the surrounding data, identity, governance, security and cloud foundation.

That division places governance inside the deployment stack rather than leaving it to a separate oversight exercise. For regulated industries, the platform includes controls, observability and AI-compliance support intended to govern agents connected to enterprise knowledge and daily work.

IBM says every agent action, decision and escalation is logged, with real-time data on latency, cost, token usage and run history. Governance controls set which actions an agent may take autonomously, which require human approval and when escalation becomes mandatory. Agents cannot bypass their defined authority limits.

An operational intelligence layer monitors performance and recommends improvements, with approved changes redeployed automatically. Microsoft Defender, Purview, Entra and Sentinel add real-time visibility over agents running in production. The operating model leaves defined approval decisions with people while automating performance monitoring and redeployment of approved changes.

What does the insurance claims example show?

IBM's worked example applies the model to insurance claims — a document-intensive process that runs from first notification of loss through settlement. Based on client interviews, standard operating procedures and industry benchmarks, the process divides among digital workers with defined responsibilities, controls and escalation paths.

A Digital Steward orchestrates the work. It assesses claim complexity, flags possible fraud signals, checks policy coverage and routes cases according to their characteristics and an adjuster's authority:

• Simple claims go to junior adjusters.
• Coverage ambiguity goes to senior adjusters.
• Complex cases with multiple anomaly flags go to principal adjusters or specialist investigation units.

The employee receives a prioritized queue explaining why work was routed, what has already been investigated and the recommended next action. The example leaves the claim decision with the human. Digital workers handle preparation, triage and follow-through.

Who is testing it?

SEI, a provider of financial technology, operations and asset-management services, is exploring emerging and agentic technologies with IBM Consulting and Microsoft support. It also uses other technologies from both companies to improve operations and the experiences it delivers to employees and clients. SEI's role in the announcement is exploratory, with no quantified production results for Imagine Enterprise.

Sneha Shah, SEI's Chief AI Strategist and Head of SEI Next, said: "Our work with IBM Consulting and Microsoft is helping us explore how emerging capabilities could support critical processes and be responsibly scaled over time, with the goal to create better experiences for our employees and clients."

What's the execution test?

The launch connects a large consulting asset base to an extensive enterprise technology stack. But the adoption model depends on more than supplying agents. The initial industry frameworks, approval boundaries and deployment options define a specific execution test: turning pre-built components into governed operations that fit the way individual enterprises already work. The 6,000-agent inventory gives IBM and Microsoft scale on paper; production deployments in financial services, insurance and retail will show whether governed autonomy sells.