IBM and ServiceNow have announced a strategic partnership aimed at helping enterprise customers modernize their legacy systems and make them ready for artificial intelligence. The collaboration will combine IBM's deep expertise in AI, data, and automation with ServiceNow's AI-powered workflow platform to address one of the biggest hurdles to AI adoption: decades-old, deeply interconnected legacy infrastructure.

The companies stated that most enterprises have the ambition to deploy agentic AI but lack the foundation to run it at scale. By working together, they aim to evolve existing systems rather than replace them, opening the door for AI to transform business operations without the risk and cost of rip-and-replace projects.

The Challenge of Legacy Systems

Legacy systems—often running on mainframes, proprietary databases, and custom-coded applications—are the backbone of many large organizations. They handle critical tasks like transaction processing, customer relationship management, and supply chain operations. However, these systems were built decades ago, long before the era of cloud computing and AI. Their monolithic architectures, rigid data structures, and lack of modern APIs make them difficult to integrate with newer AI tools.

According to industry analysts, the cost of maintaining legacy systems can consume up to 80% of an enterprise's IT budget, leaving little room for innovation. Worse, the knowledge required to maintain these systems is aging out, as the original developers retire. This creates a pressing need for modernization strategies that preserve business logic while introducing AI capabilities.

IBM has long been a leader in mainframe and legacy system management, with its z/OS platform and tools like IBM Bob (Business Object Broker) and Enterprise Application runtime for Java. ServiceNow, on the other hand, has built a dominant platform for IT service management, workflow automation, and now AI agents. Their combined offering targets the sweet spot where legacy infrastructure meets modern AI needs.

Three Core Services for AI-Ready Infrastructure

The partnership will deliver three specific services, all slated for availability in the second half of 2026. These services are designed to address different facets of legacy system modernization, from application refactoring to autonomous operations and data governance.

Application Modernization

The first service focuses on scanning and refactoring legacy applications using IBM Bob, Enterprise Application runtime (Java), and IBM watsonx.data. This service helps enterprises bring existing applications into the AI era without starting from scratch. By analyzing code, identifying dependencies, and automatically generating modular, API-ready versions, the service reduces the time and risk typically associated with migration projects.

IBM Bob, in particular, is a tool that helps understand and transform COBOL and other legacy code. Combined with watsonx.data, which provides a fit-for-purpose data store for AI workloads, enterprises can unlock the data trapped in legacy applications and make it available for AI models. ServiceNow's platform then provides the workflow layer to orchestrate these new AI-enhanced processes.

Autonomous Infrastructure Operations

The second service integrates Red Hat Ansible, IBM Bob, Instana, Hashicorp Terraform, and Hashicorp Vault into ServiceNow IT workflows. This combination enables autonomous detection, remediation, and resolution of infrastructure issues before they affect the business. By embedding AI-driven observability and automation into existing IT operations, enterprises can reduce downtime and improve efficiency.

For example, if a mainframe workload begins to experience performance degradation, the integrated system can automatically scale resources, apply patches, or reroute traffic—all without human intervention. ServiceNow's platform provides a single pane of glass for monitoring and managing these complex hybrid environments.

Data Governance

The third service extends ServiceNow Workflow Data Fabric with IBM watsonx.data to unlock key capabilities like Data Quality, Observability, and Master Data Management. By employing the ServiceNow Data Catalog, mutual customers can keep track of their AI-ready data assets. This ensures that data used for AI training and inference is accurate, compliant, and well-governed.

Data governance is a critical component of any AI strategy, as poor data quality can lead to biased models, regulatory fines, and operational failures. The combined offering helps enterprises establish a solid data foundation, making it easier to deploy AI at scale across the organization.

Long-Standing Relationship

IBM and ServiceNow have a history of collaboration, having worked together on cloud computing, automation, security, IT service management, and observability technologies. This new partnership deepens that relationship by focusing specifically on the legacy-to-AI transformation challenge.

John Aisien, senior vice president and general manager of central product management, security, and risk at ServiceNow, highlighted the importance of the partnership: "Most enterprises have the ambition to deploy agentic AI, but lack the foundation to run it at scale. 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."

IBM's expertise with large systems, including its mainframe environment, complements ServiceNow's strength in workflow orchestration and agent management. Together, they are positioning themselves as a one-stop shop for enterprises seeking to harness AI without abandoning their existing investments.

Market Context and Impact

The announcement comes at a time when enterprises across all industries are under pressure to adopt AI. However, many are held back by the complexity and risk of modernizing legacy systems. Gartner predicts that through 2026, more than 60% of legacy application modernization projects will fail to meet their objectives due to lack of skilled resources and insufficient planning.

By offering a structured, tool-based approach, IBM and ServiceNow aim to increase the success rate of these projects. Their joint services allow enterprises to incrementally modernize, reducing risk and enabling faster time-to-value. For ServiceNow, this partnership expands its reach into the mainframe and legacy world, a market that IBM has dominated for decades.

From a competitive standpoint, the collaboration also positions both vendors against other players in the AI modernization space, such as Accenture, Deloitte, and specialized software vendors like Micro Focus (now part of OpenText). However, the deep integration between IBM's infrastructure tools and ServiceNow's workflow engine gives them a unique edge.

Enterprises that adopt these services can expect to see improvements in operational efficiency, reduced IT costs, and the ability to deploy AI agents that interact with legacy systems seamlessly. For example, an insurance company could use AI to process claims across a mainframe policy system without modifying the underlying code.

The partnership also addresses the growing demand for autonomous IT operations, sometimes called AIOps. By integrating monitoring, automation, and remediation into a single workflow, enterprises can reduce the burden on IT staff and achieve higher service levels.

As AI continues to evolve, the ability to connect modern AI models with legacy systems will become increasingly important. IBM and ServiceNow are betting that their combined expertise will make this transition smoother for the world's largest enterprises. The services are expected to be available in the second half of 2026, with early access programs likely to launch sooner.

Source: Network World News