IBM and ServiceNow Expand Their Alliance to Run Agentic AI on Enterprises' Legacy Systems

IBM and ServiceNow Expand Their Alliance to Run Agentic AI on Enterprises' Legacy Systems

For the world's largest enterprises, the biggest obstacle to deploying AI at scale is not a shortage of models — it is four decades of interconnected legacy infrastructure sitting underneath every workflow. On June 11, 2026, IBM and ServiceNow moved to address that problem directly, announcing an expanded multi-year collaboration designed to let companies run agentic AI on top of aging systems without tearing them out first.

The deal pairs IBM's AI, data, and automation software stack with the ServiceNow AI Platform, creating a set of joint solutions targeting three distinct choke points that stop enterprise AI programs from graduating out of the pilot stage: modernizing old applications, making enterprise data actually AI-ready, and automating the infrastructure operations that keep it all running.

What the Deal Actually Includes

The technical scope is specific enough to matter. On the application side, IBM is bringing IBM Bob — its AI-powered coding agent launched in April 2026 — along with Enterprise Application Runtime (targeted at Java-based applications) and IBM watsonx.data into the ServiceNow environment. The aim is to let organizations refactor aging codebases and migrate workloads into an AI-compatible architecture incrementally, rather than through wholesale replacement.

On data governance, the collaboration extends ServiceNow's Workflow Data Fabric with IBM watsonx.data, adding capabilities around Data Quality, Observability, and Master Data Management, all surfaced through ServiceNow's Data Catalog. The practical effect is that mutual customers can keep data continuously AI-ready rather than treating it as a periodic cleanup project.

The third pillar, autonomous infrastructure operations, integrates Red Hat Ansible, Instana (IBM's observability platform), HashiCorp Terraform, and HashiCorp Vault directly into ServiceNow IT workflows. The goal is self-healing infrastructure: systems that detect, remediate, and resolve incidents before they surface as business disruptions.

Joint solutions across all three areas are expected to reach customers in the second half of 2026.

What Executives Are Saying

"Most enterprises have the ambition to deploy agentic AI, but lack the foundation to run it at scale," said John Aisien, SVP and general manager of central product management at ServiceNow. "IBM brings the tooling to modernize the systems and extend ServiceNow's data capabilities; ServiceNow provides the platform to put that data to work across every workflow in the business. Together, we're helping enterprises move from AI ambition to real, scalable outcomes."

IBM's Raj Datta, VP of ISV and AI partnerships, reinforced the same thesis from a different angle: "AI adoption at scale requires more than access to models. It requires rethinking the systems, data and workflows that support them. We're building an open, flexible foundation for AI that can scale across operations and deliver real business value."

Both statements are notable for what they avoid — neither executive reached for TAM figures or vague transformation language. The framing is deliberately operational, which reflects a shift in how enterprise AI partnerships are being positioned in mid-2026, when CIOs are less interested in strategy decks and more focused on what can actually be deployed.

The "Evolve, Don't Replace" Thesis

The structural logic behind this deal speaks to a broader pattern in enterprise AI adoption. Large organizations in financial services, telecommunications, healthcare, and government — sectors where both IBM and ServiceNow have deep customer penetration — are not in a position to rip out core systems that have been running for decades. ERP platforms, mainframe workloads, and Java-based applications carry too much institutional logic and regulatory history to be discarded on an AI timeline.

The answer IBM and ServiceNow are proposing is a wrapper strategy: bring the modernization tooling and data plumbing to where the systems already live, then use ServiceNow's platform as the orchestration and workflow layer on top. ServiceNow reported more than 85 billion workflows running on its platform annually, giving the integration a substantial surface area to operate across.

This is also not the first time the two companies have combined their stacks. A May 2024 partnership first connected ServiceNow workflows with IBM's watsonx.ai platform and introduced IBM's Granite language models into the Now Assist ecosystem — expanding multilingual capabilities and improving summarization and virtual agent responses. The June 2026 expansion goes considerably deeper, moving from model access into the underlying systems, data, and infrastructure layers.

Competitive Context

IBM and ServiceNow are not the only vendors pursuing this angle. ServiceNow earlier in 2026 deepened ties with OpenAI to bring frontier model capabilities to its platform, and the company has been building out its AI Control Tower as a governance and orchestration layer for agents deployed across disparate enterprise systems. IBM, meanwhile, has continued to expand its consulting and software presence around the watsonx platform following its HashiCorp acquisition, which now feeds directly into this partnership's infrastructure operations pillar.

The competitive pressure is real. Oracle, AWS, Salesforce, and Microsoft are all positioning their respective platforms as the connective tissue for enterprise AI. The IBM-ServiceNow combination is betting that the answer to legacy complexity is not a single-vendor cloud migration story, but an open, model-agnostic integration layer that meets large enterprises where their data and applications already sit.

ServiceNow CEO Bill McDermott articulated the platform's competitive claim during the company's Q1 2026 earnings call: "AI, data, security and governance are now built into every product and package, not a separate purchase." The IBM partnership is, in part, a vehicle to make that statement credible across the infrastructure and data layers as well, not just at the workflow surface.

What to Watch

The first indicator of whether this deal has teeth will be the pace of customer announcements in the second half of 2026. Both IBM and ServiceNow serve overlapping enterprise accounts in industries where AI modernization pressure is highest — financial services, telco, and government — so joint case studies should not be hard to produce if the integrations deliver.

The second thing to track is the role of IBM Consulting in the rollout. IBM's services arm has historically been the go-to-market engine for complex enterprise deployments, and the consulting layer around application modernization and data governance is where deals like this actually get implemented. If IBM Consulting starts booking significant engagements anchored to this partnership, that is a more durable signal than press releases.

Finally, watch for whether the "model-agnostic" positioning holds. Both companies have emphasized that customers can run AI on any model they choose. How that plays out when customers want to use Anthropic, Google, or Meta models alongside IBM Granite on the ServiceNow platform will be a practical test of the open foundation both executives described.

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Sources: [IBM Newsroom](https://newsroom.ibm.com/2026-06-11-ibm-and-servicenow-expand-collaboration-to-unlock-enterprise-data-for-ai-at-scale), [ServiceNow Newsroom via BusinessWire](https://www.businesswire.com/news/home/20260611423102/en/ServiceNow-and-IBM-Expand-Collaboration-to-Unlock-Enterprise-Data-for-AI-at-Scale), [CIO Dive](https://www.ciodive.com/news/servicenow-IBM-modernize-data-enterprises/822718/), [CoinCentral](https://coincentral.com/ibm-stock-what-the-servicenow-partnership-means-for-enterprise-ai/)