Analyst(s): Keith Kirkpatrick
Publication Date: June 22, 2026
IBM and ServiceNow have expanded their collaboration to help enterprises address legacy systems and data challenges that limit AI adoption at scale. The partnership combines modernization, data governance, and autonomous IT operations capabilities to help organizations unlock enterprise data and support agentic AI initiatives.
What Is Covered in This Article:
- IBM and ServiceNow expanded their collaboration to address legacy systems and AI-ready data challenges that limit enterprise AI adoption.
- The partnership focuses on three areas: application modernization, enterprise data governance, and autonomous infrastructure operations.
- IBM will integrate technologies, including watsonx.data, Red Hat Ansible, Instana, HashiCorp Terraform, HashiCorp Vault, Enterprise Application Runtime, and IBM Bob with the ServiceNow AI Platform.
- The companies aim to help organizations modernize existing systems rather than replace them while enabling AI across core business operations.
- Joint solutions are expected to become available during the second half of 2026.
The News: IBM and ServiceNow announced an expanded multi-year collaboration designed to address two major barriers to enterprise AI adoption: AI-ready data and legacy application environments. The companies will combine IBM’s AI, data, automation, observability, infrastructure, and application modernization capabilities with the ServiceNow AI Platform to help enterprises modernize aging systems, unlock enterprise data, and support autonomous operations.
The collaboration will focus on application modernization, enterprise data governance, and autonomous infrastructure operations. Planned capabilities include legacy application scanning and refactoring, expanded data governance through ServiceNow Workflow Data Fabric and IBM watsonx.data, and automated infrastructure operations using technologies such as Red Hat Ansible, Instana, HashiCorp Terraform, HashiCorp Vault, and IBM Bob. The companies expect the joint solutions to become available during the second half of 2026.
Can IBM and ServiceNow Finally Make Legacy Systems AI-Ready?
Analyst Take: IBM and ServiceNow are positioning this expanded collaboration around a problem that repeatedly appears across enterprise AI initiatives: organizations want to deploy agentic AI, but decades of interconnected legacy systems and fragmented data limit their ability to do so at scale. Rather than advocating wholesale replacement of existing environments, the partnership focuses on modernizing applications, improving data governance, and automating operational processes. IBM contributes modernization, data, observability, automation, and infrastructure capabilities, while ServiceNow provides the workflow and orchestration platform designed to connect enterprise systems and data. The collaboration reflects a growing emphasis on making existing enterprise environments usable for AI rather than rebuilding them from the ground up.
Application Modernization Without Full Replacement
One of the most notable aspects of the announcement is the decision to focus on evolving existing systems instead of replacing them. IBM and ServiceNow specifically state that enterprises can modernize aging applications through technologies such as IBM Bob, Enterprise Application Runtime, and watsonx.data. The approach acknowledges that many large organizations continue to operate deeply interconnected legacy environments that support critical business processes. These environments are a major obstacle to moving quickly on AI initiatives because they contain valuable data but often lack modern interfaces and integration capabilities. By focusing on scanning, refactoring, and modernization rather than migration and replacement, IBM and ServiceNow are attempting to reduce disruption while extending the useful life of existing enterprise applications.
Data Readiness Remains the Central Challenge
The partnership places equal emphasis on enterprise data governance and data readiness. IBM and ServiceNow plan to extend ServiceNow Workflow Data Fabric with IBM watsonx.data capabilities that include data quality, observability, and master data management while leveraging the ServiceNow Data Catalog. Data trapped inside legacy systems can slow business analytics, create incomplete visibility, and hinder AI deployment efforts. ServiceNow has consistently positioned itself as a platform that connects systems, workflows, and enterprise context, while IBM brings data management and governance capabilities designed to improve the quality and accessibility of enterprise information. The collaboration recognizes that access to AI models alone does not solve enterprise AI challenges if organizations cannot trust, govern, or locate the data those models require.
Expanding Beyond Workflows Into Autonomous Operations
The autonomous infrastructure operations component extends the partnership beyond application and data modernization. IBM and ServiceNow plan to integrate Red Hat Ansible, Instana, HashiCorp Terraform, HashiCorp Vault, IBM Bob, and ServiceNow workflows to detect, remediate, and resolve issues before they affect business operations. The combination brings together automation, observability, infrastructure management, security, and workflow orchestration capabilities within a single operating framework. According to the announcement, the objective is to enable more autonomous IT operations while reducing the operational friction that often slows modernization initiatives. This portion of the collaboration demonstrates that the companies view AI adoption as an operational challenge as much as a data or application challenge.
A Broader Effort to Build the Enterprise AI Foundation
The expanded partnership also highlights how both companies are attempting to address foundational requirements for enterprise AI adoption. ServiceNow executives describe the challenge as moving enterprises from AI ambition to scalable outcomes, while IBM emphasizes the need to rethink systems, data, and workflows rather than focusing solely on access to AI models. According to Futurum’s 1H 2026 Enterprise Software Decision Maker Survey Report, 41.0% of organizations plan to reduce or consolidate their application stack, with 65.9% now favoring a platform-centric approach. The emphasis on a common platform, integrated data capabilities, and workflow orchestration reflects the growing importance of bringing fragmented systems together before organizations can scale AI initiatives. Legacy modernization as an area is receiving significant attention because AI tools can assist with understanding, documenting, and refactoring older systems. At the same time, modernization efforts still require substantial oversight and validation despite advances in AI-assisted development. The partnership ultimately positions modernization, governance, and operational automation as interconnected components of enterprise AI readiness rather than isolated technology projects.
What to Watch:
- Whether enterprises adopt the modernization approach at scale or continue pursuing broader application replacement strategies.
- How effectively IBM watsonx.data and ServiceNow Workflow Data Fabric work together to improve data quality, observability, and master data management.
- Whether autonomous infrastructure operations deliver measurable reductions in operational complexity and incident resolution times.
- How organizations balance AI-assisted modernization with the expert oversight and validation that industry observers say remains necessary.
- Customer adoption levels once the joint solutions become available in the second half of 2026.
See the complete announcement regarding IBM and ServiceNow’s expanded collaboration to unlock enterprise data for AI at scale on the ServiceNow website.
Declaration of generative AI and AI-assisted technologies in the writing process: This content has been generated with the support of artificial intelligence technologies. Due to the fast pace of content creation and the continuous evolution of data and information, The Futurum Group and its analysts strive to ensure the accuracy and factual integrity of the information presented. However, the opinions and interpretations expressed in this content reflect those of the individual author/analyst. The Futurum Group makes no guarantees regarding the completeness, accuracy, or reliability of any information contained herein. Readers are encouraged to verify facts independently and consult relevant sources for further clarification.
Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.
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Author Information
Keith Kirkpatrick is VP & Research Director, Enterprise Software & Digital Workflows for The Futurum Group. Keith has over 25 years of experience in research, marketing, and consulting-based fields.
He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.
In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek, CNBC.com, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.
He is a member of the Association of Independent Information Professionals (AIIP).
Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.
