IBM and ServiceNow Join Forces to Modernize Legacy Systems for AI
In a bid to help enterprises overcome one of the biggest hurdles to AI adoption, IBM and ServiceNow have announced a strategic collaboration. The partnership combines IBM’s deep expertise in large-scale systems, including mainframes and legacy applications, with ServiceNow’s AI platform and workflow automation. The goal is to transform aging IT environments into AI-ready infrastructures without requiring complete system overhauls.
According to the companies, the most significant barrier to deploying artificial intelligence at scale is the presence of deeply interconnected legacy systems built over decades. These complex environments often house critical business logic and data but are difficult to integrate with modern AI tools. The IBM-ServiceNow collaboration addresses this by providing a set of services that sit atop existing systems, enabling organizations to evolve rather than replace their core infrastructure.
Three Core Services to Bridge the AI Gap
The vendors outlined three initial services, scheduled for availability in the second half of 2026. Each targets a specific pain point in the legacy-to-AI journey.
Application Modernization
This service leverages IBM’s Bob suite, Enterprise Application Runtime (Java), and watsonx.data to scan and refactor legacy applications. The aim is to make older codebases compatible with AI-driven workflows and data models, allowing enterprises to extract value from existing investments. Traditional approaches often require rewriting entire applications, a costly and risky process. IBM and ServiceNow claim their joint approach reduces friction by automating parts of the refactoring process.
Autonomous Infrastructure Operations
By integrating Red Hat Ansible, IBM Bob, Instana, Hashicorp Terraform, and Hashicorp Vault with ServiceNow’s IT workflow engine, the service promises to detect, remediate, and resolve infrastructure issues before they impact business operations. This autonomous operations capability is designed for environments where uptime is critical, such as banking, healthcare, and telecommunications. The AI-driven automation reduces reliance on manual intervention, speeding up incident response.
Data Governance
Data quality and governance are foundational for AI success. The partners are extending ServiceNow’s Workflow Data Fabric with IBM watsonx.data to provide features like data quality monitoring, observability, and master data management. The ServiceNow Data Catalog will help customers track and manage AI-ready data assets. This service addresses the common problem of siloed or poorly documented data that plagues many large organizations.
Background: The Legacy System Challenge
Enterprise legacy systems, particularly mainframes, have been a cornerstone of business computing since the 1960s. According to industry estimates, over 70% of enterprise workloads still run on mainframe-adjacent architectures. These systems handle tasks like transaction processing, airline reservations, and financial clearing. However, their rigid structures and outdated programming languages (COBOL, PL/I, Assembler) make them difficult to connect with modern AI platforms.
ServiceNow’s platform provides a workflow layer that abstracts the complexity of underlying systems. By partnering with IBM, which has decades of experience managing mainframe environments, ServiceNow gains credibility in the high-stakes world of legacy modernization. IBM’s watsonx.data and Bob tools are already used by many enterprises for data management and application analysis. The combination creates a end-to-end pathway from legacy code to AI-driven automation.
Industry Impact and Analyst Perspectives
Analysts see the partnership as a natural evolution. “Legacy modernization has been a talking point for years, but most attempts fail due to complexity and cost,” said a senior analyst at a major IT research firm. “By embedding AI directly into the existing workflow layer, IBM and ServiceNow are offering a pragmatic path forward.” Another observer noted that autonomous operations could reduce IT operational costs by up to 30%, freeing up budgets for innovation.
The timing is significant. According to a 2025 survey by McKinsey, 85% of CIOs cite legacy system integration as a top barrier to AI scale. The IBM-ServiceNow offering directly addresses this pain point. The companies have a long history of collaboration, previously working together on cloud, automation, and security projects. This deeper integration could give them a competitive edge over other vendors like SAP, Oracle, or Microsoft, who also target legacy modernization but with different approaches.
Technical Deep Dive: The Role of IBM Bob and watsonx.data
IBM Bob (Business Observability and Beyond) is an AI-powered tool that analyzes application code and runtime behavior. It can identify patterns, detect anomalies, and suggest optimizations. In the modernization service, Bob will scan COBOL or Java code to generate a map of dependencies and data flows. This map feeds into watsonx.data, IBM’s lakehouse architecture, which unifies structured and unstructured data for AI training. ServiceNow’s platform then uses this enriched data to create automated workflows.
For autonomous operations, Red Hat Ansible provides configuration management, while Instana offers real-time application performance monitoring. Hashicorp Terraform handles infrastructure provisioning, and Vault manages secrets. The integration means that if Instana detects a memory leak in a mainframe application, ServiceNow can automatically trigger a remediation script through Ansible, log the incident, and notify the operations team—all without human intervention.
The Broader AI Readiness Landscape
Enterprises racing to adopt generative AI and agentic AI often find that their data infrastructure cannot support the demands. Many lack the data quality, governance, and integration capabilities needed. The IBM-ServiceNow partnership is part of a larger trend of “AI-ready” infrastructure services. Competitors like Accenture and Deloitte have similar practices, but IBM’s ownership of both the mainframe (through z/OS) and the AI platform (watsonx) gives it unique leverage.
ServiceNow’s AI Platform, launched in 2025, includes a “workflow fabric” that connects disparate systems. This fabric uses large language models to interpret user requests and execute multi-step processes across legacy and cloud environments. For example, an employee could ask the system to “retrieve all customer data from the last quarter and generate a compliance report.” The AI would automatically access the mainframe, extract data, format it, and produce the report—all while logging access for audit purposes.
The announcement also highlights the growing importance of data governance in AI projects. Without clean, labeled, and accessible data, AI models produce unreliable outputs. The joint data governance service aims to give enterprises confidence in the quality of their training data. By integrating IBM’s metadata management capabilities into ServiceNow’s catalog, organizations can create a single source of truth for AI consumption.
Future Directions and Strategic Implications
Both companies are betting that the market for legacy AI modernization will expand rapidly. IBM has been pivoting aggressively toward hybrid cloud and AI, while ServiceNow continues to dominate the IT service management (ITSM) space. The partnership could also set the stage for deeper integration with IBM’s Red Hat ecosystem, including OpenShift for containerization of legacy apps.
One key advantage of the collaboration is that it does not require enterprises to rip and replace their existing systems. This is particularly attractive for regulated industries like banking, where compliance with standards such as PCI-DSS or GDPR makes wholesale changes infeasible. Instead, the ServiceNow platform acts as a “digital layer” that modernizes interactions with legacy systems without altering them internally.
IBM and ServiceNow have not disclosed specific pricing for the three services, but they are expected to be offered as subscription-based offerings. Early adopters are likely to be large enterprises with significant mainframe footprints in finance, insurance, and government. The companies plan to demonstrate the capabilities at upcoming industry events.
In summary, the partnership addresses a critical gap in enterprise AI strategy: how to leverage decades of legacy infrastructure without starting from scratch. By combining IBM’s system-level expertise with ServiceNow’s workflow orchestration, organizations can begin their AI journey from a position of strength, using their existing assets as a foundation rather than an obstacle.
Source: Network World News