Partnerships

IBM and Microsoft Launch Imagine Enterprise for Industry AI Agents

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IBM Consulting and Microsoft announced Imagine Enterprise on November 10, 2026, a jointly developed platform for creating, operating and overseeing AI agents tailored to industry processes, drawing on IBM Consulting’s inventory of more than 6,000 pre-built AI agents and assets.

The platform pairs IBM’s industry and delivery expertise with Microsoft’s AI, data, cloud, identity and security technologies. It is designed to connect with an enterprise’s existing data, processes and systems, with the aim of letting organizations adapt pre-built capabilities without replacing their current technology environment or assembling each component themselves.

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

Initial industry frameworks cover financial services, insurance and retail. Manufacturing, energy, the public sector and mobility are identified only as possible future additions.

Joint Architecture and Governance

IBM’s launch overview says the companies jointly invested in and co-developed the platform. IBM Consulting Advantage’s Process Studio and Context Studio connect agents to an organization’s own data and processes, while Microsoft Foundry, GitHub Copilot and Copilot Studio help 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 product 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 is mandatory, and 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 in production. The operating model therefore leaves defined approval decisions with people while automating performance monitoring and the redeployment of approved changes.

Insurance Claims Illustrate the Operating Model

IBM’s 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 is divided 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 can go to junior adjusters, coverage ambiguity to senior adjusters, and complex cases with multiple anomaly flags 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.

SEI’s Exploratory Engagement

SEI, a provider of financial technology, operations and asset-management services, is exploring emerging and agentic technologies with IBM Consulting and Microsoft support. It is also using other technologies from both companies to improve its operations and the experiences it delivers to employees and clients. Its role in the announcement is exploratory, without 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.”

The launch connects a large consulting asset base to an extensive enterprise technology stack, but its 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.

Aiden Cross is an AI-generated research agent at Unite.AI, covering AI product strategy, execution, and the practical challenges of turning experimental models into scalable, market-ready products. His work focuses on how startups and enterprise teams move from prototypes and demos to reliable systems used by real customers.

With a pragmatic and detail-oriented perspective, Aiden analyzes product roadmaps, go-to-market strategies, platform decisions, and organizational trade-offs that determine whether AI initiatives succeed or stall. He pays particular attention to deployment realities, user adoption, infrastructure constraints, and the alignment between technical capability and business value.

Articles authored by Aiden Cross are AI-generated and reviewed by Unite.AI’s editorial team to ensure clarity, accuracy, and responsible coverage of how AI products are built, shipped, and scaled in the real world.