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IBM and ServiceNow expand AI deal to modernize legacy apps and data

The multi-year collaboration targets two persistent enterprise AI blockers — aging applications and ungoverned data — with joint solutions due in the second half of 2026.

Dmytro Spodarets
Jun 11, 2026 · 1 min read

IBM (NYSE: IBM) and ServiceNow (NYSE: NOW) on June 11, 2026 announced a multi-year expanded collaboration aimed at the obstacles that keep enterprises from putting AI into production: legacy applications and data that is not ready to use, IBM said. The two companies plan to deliver joint solutions in the second half of 2026.

The work spans three areas. The first targets application modernization, pairing IBM's Bob coding assistant, its Enterprise Application Runtime for Java and IBM watsonx.data to refactor aging systems. The second extends data governance, connecting ServiceNow Workflow Data Fabric to IBM watsonx.data along with IBM's Data Quality, Observability and Master Data Management tools and the ServiceNow Data Catalog, the companies said.

The third area covers autonomous infrastructure operations, folding Red Hat Ansible, IBM Bob, Instana monitoring, and HashiCorp's Terraform and Vault into ServiceNow IT workflows so routine operations can run with less manual intervention.

The pitch rests on scale on both sides. ServiceNow says more than 100 billion workflows run on its platform each year, while IBM operates in more than 175 countries — reach the two companies argue makes their combined data and automation tooling relevant to large enterprises. Those framings are the partners' own, and the solutions are not yet generally available.

The announcement does not include a contract value, customer commitments or a fixed launch date beyond the second-half window, so the deal is a product and engineering roadmap rather than a booked sale. Its impact will depend on whether the promised solutions ship on schedule and whether customers adopt the combined stack over the point tools they already run. For now, two of the larger enterprise-software vendors are betting that the bottleneck to enterprise AI is less the models than the unglamorous work of fixing data and old applications.


Dmytro Spodarets
Dmytro Spodarets
Founder & Editor-in-Chief

Founder and Chief Editor of Data Phoenix — a San Francisco Bay Area media and education platform focused on AI and Data.

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