IBM and Microsoft launched Imagine Enterprise on Tuesday, November 10, 2026. It is a new agentic platform that helps large enterprises build, run and govern AI agents. The agents are designed to help people carry out industry specific work, not to replace the judgment that regulated work still needs. The announcement came from Armonk, New York, and Redmond, Washington. IBM Consulting brings more than 6,000 prebuilt AI agents and assets. Microsoft provides the AI, data, cloud and security foundation. The first industry frameworks cover financial services, insurance and retail.
Quick Facts
| Item | Detail |
|---|---|
| Platform name | Imagine Enterprise |
| Announced by | IBM and Microsoft |
| Announcement date | Tuesday, November 10, 2026 |
| Announcement places | Armonk, New York, and Redmond, Washington |
| What it is | An agentic platform to build, run and govern AI agents |
| Prebuilt agents and assets | More than 6,000 from IBM Consulting |
| IBM Consulting platform | IBM Consulting Advantage, its AI powered delivery platform |
| Microsoft foundation | Microsoft Foundry, GitHub Copilot and Microsoft Copilot Studio |
| First industries | Financial services, insurance and retail |
| Possible later industries | Manufacturing, energy, public sector and mobility |
| How clients can use it | IBM managed, jointly developed or self managed deployments |
| Support available | Forward deployed engineering support for qualifying engagements |
| Pricing in the announcement | No pricing given |
| General availability date | No general availability date given |
What Imagine Enterprise Is
Imagine Enterprise is a working platform for AI agents inside large companies. An AI agent, in this setting, is software that can take on a defined task, use enterprise data, follow rules, and help a person complete a process. The platform covers the full life of that agent, from building it and putting it into daily use to watching how it performs and governing how it behaves. An agent that works well in a demo but cannot be controlled, checked or explained is not ready for real work.
The announcement places the human worker at the center. The agents help people execute industry specific processes, so people stay in charge of decisions while agents handle steps, gather information, prepare drafts and check details. In financial services, insurance and retail, many processes involve rules, records and checks. An agent that follows those rules in a steady way can save time, while a person who reviews the result keeps the process sound.
Why IBM and Microsoft Built It Together
Large enterprises often face the same problem with AI. A pilot works in one team, a second team builds something similar, and soon the company has many small experiments and no clear way to run them safely at scale. Imagine Enterprise is aimed at that gap, giving companies a repeatable way to build agents, connect them to enterprise data and daily processes, and govern them in one place.
The partnership matters because neither side alone covers the whole need. IBM Consulting brings more than 6,000 prebuilt AI agents and assets, built on IBM Consulting Advantage, its AI powered delivery platform. Those agents and assets come with experience from building and running them in real client settings, covering how agents are designed, tested, put into service, and kept working over time.
Microsoft provides the AI, data, cloud and security foundation, including Microsoft Foundry, GitHub Copilot and Microsoft Copilot Studio. That covers the tools used to create agents, the cloud services that run them, the data connections that feed them, and the security controls that protect them. A company can then build an agent without rebuilding the basic platform each time, and apply the same security and governance rules across many agents.
The Focus on Regulated Industries
Imagine Enterprise aims especially at regulated industries. Banks, insurers and other regulated firms work under strict rules. They must keep clear records, protect customer data, explain decisions, and show that their processes follow the law and their own policies. An AI agent in such a setting must meet the same standards, and it must be possible to see what it did, why it did it, and who was responsible.
The platform helps organizations combine human expertise with AI agents and connect them to enterprise data and daily processes. Human expertise brings judgment, context and accountability. AI agents bring speed, consistency and the ability to work through large amounts of information. Combined well, a process can become faster without becoming less careful, and the governance part of the platform is meant to reduce the risk that speed hides mistakes.
Financial services, insurance and retail are the first industries covered. The frameworks are designed as a repeatable blueprint for potential later industries such as manufacturing, energy, public sector and mobility, though no timing is given. The announcement does not list specific processes, so no particular use case should be assumed.
How Enterprises Can Use the Platform
Imagine Enterprise is available to clients by engaging IBM Consulting to deploy and operate the platform on the client behalf, or by co-innovating with IBM Consulting on enterprise scale implementations. Businesses can use IBM managed, jointly developed or self managed deployments. That gives clients three broad paths: IBM runs day to day operation, the work is shared between the client and IBM, or the client keeps operation in house, using the platform and the prebuilt agents as a base.
Large companies differ in how much they want to run themselves. Some have large technology teams and want to keep control in house. Others want a partner to operate the platform while their own teams focus on the business process. The announcement offers all three options, rather than forcing one model on every client.
What the announcement does not give is also important. It gives no pricing, no general availability date, no customer count and no financial terms, so the commercial impact cannot be judged from the release alone. A reader cannot tell what the platform will cost, when a typical client could start, or how many clients are already using it.
The example named in the announcement is SEI, a global provider of financial technology, operations and asset management services in financial services. SEI is cited as an example of the enterprise transformation needs that agentic AI can address. The release does not say SEI is a customer or partner of the platform, so that claim should not be made. As of September 30, 2026, SEI manages, advises or administers approximately 2 trillion dollars in assets.
What This Launch Means for Enterprise AI
The launch fits a wider shift in enterprise AI. The first wave of interest focused on chat tools and single answers. The next wave focuses on agents that can carry out multi step work inside a business. That shift raises new questions. How does a company know an agent followed the rules? How does it fix an agent that makes a mistake? How does it update an agent when a process changes? A platform that answers those questions is more useful than a tool that only produces a fast draft.
The IBM and Microsoft approach tries to answer those questions with a mix of prebuilt assets, a shared foundation and governance. The prebuilt agents give clients a starting point, so they do not have to build every agent from zero. The Microsoft foundation gives them the AI, data, cloud and security pieces in one place. Forward deployed engineering support from both companies is available for qualifying engagements, though the announcement does not define which engagements qualify.
For readers in financial services, insurance and retail, the practical question is simple. Does this platform fit a real process in their company, and can it be run safely? The announcement gives a framework for that question, but it does not answer it for any single company. Each enterprise would need to look at its own processes, data, rules and teams. For readers outside those three industries, the launch is still worth watching. If the repeatable blueprint works in the first three, it may later be adapted for other industries. That is the plan described in the announcement. It is not a timetable.
Readers following the wider technology market can place this launch alongside other recent enterprise AI news. See the Nvidia slump story, the SoftBank second quarter results and the Google new AI chips for that wider picture.
FAQs
What is Imagine Enterprise?
Imagine Enterprise is an agentic platform from IBM and Microsoft. It helps enterprises build, run and govern AI agents that help people execute industry specific processes. It is designed first for regulated industries, with frameworks for financial services, insurance and retail.
Who built Imagine Enterprise?
IBM and Microsoft announced the platform together on Tuesday, November 10, 2026. IBM Consulting brings more than 6,000 prebuilt AI agents and assets, built on IBM Consulting Advantage. Microsoft provides the AI, data, cloud and security foundation, including Microsoft Foundry, GitHub Copilot and Microsoft Copilot Studio.
Which industries does Imagine Enterprise cover first?
The industry specific frameworks initially cover financial services, insurance and retail. The design is a repeatable blueprint for potential additional industries such as manufacturing, energy, public sector and mobility, but no timing is given in the announcement.
How can a business use Imagine Enterprise?
A business can engage IBM Consulting to deploy and operate the platform on its behalf, or co-innovate with IBM Consulting on enterprise scale implementations. Deployments can be IBM managed, jointly developed or self managed. Forward deployed engineering support from both companies is available for qualifying engagements.
SOURCES
Final Thoughts
Imagine Enterprise is a clear and focused launch. IBM and Microsoft have described what the platform is, who it is for, and how clients can use it. The focus on regulated industries, the prebuilt agents, the Microsoft foundation, and the three deployment options give enterprises a practical starting point. The limits are just as clear. There is no pricing, no general availability date, no customer count and no financial terms, so the commercial impact cannot be judged from the release alone. SEI is named only as an example of enterprise transformation needs, not as a customer or partner. The next step for any interested enterprise is a direct discussion with IBM Consulting, a careful look at a real process, and a pilot that tests whether the agents work safely at scale.
