IBM and ServiceNow have announced a strategic collaboration aimed at helping enterprise customers transform their aging legacy environments into AI-ready infrastructures. The partnership, which combines IBM's expertise in AI, data, and automation with ServiceNow's AI platform, will deliver a suite of services designed to modernize decades-old systems, enable autonomous IT operations, and allow organizations to evolve their existing infrastructure rather than undertaking costly full-scale replacements.

The initiative comes at a time when many large enterprises are eager to adopt artificial intelligence but face significant barriers due to deeply interconnected legacy systems. These systems, often built over 30 or 40 years, consist of tightly coupled mainframe applications, custom-coded middleware, and complex databases that cannot easily be integrated with modern AI technologies. IBM, with its long-standing experience in mainframe environments and legacy application management, is well-positioned to address this challenge. ServiceNow brings its AI-Platform, which acts as a workflow layer on top of existing systems, automating tasks and orchestrating processes across disparate technologies.

The Core Services

The vendors outlined three main service areas that will become available in the second half of 2026:

• Application Modernization: This service uses tools such as IBM Bob, Enterprise Application runtime (Java), and IBM watsonx.data to scan and refactor legacy applications. The goal is to help enterprises bring their existing codebases into the AI era without rewriting everything from scratch. By analyzing the structure and dependencies of legacy applications, the tools can identify opportunities to modernize incrementally, reducing risk and preserving business logic.
• Autonomous Infrastructure Operations: By integrating Red Hat Ansible, IBM Bob, Instana, HashiCorp Terraform, and HashiCorp Vault into ServiceNow IT workflows, this service aims to detect, remediate, and resolve infrastructure issues before they impact business operations. The autonomous operations capability leverages AI to predict failures, automate incident response, and optimize resource allocation across hybrid cloud environments.
• Data Governance: This offering extends ServiceNow Workflow Data Fabric with IBM watsonx.data to unlock capabilities like Data Quality, Observability, and Master Data Management. The ServiceNow Data Catalog allows mutual customers to track and manage their AI-ready data, ensuring that data fed into AI models is accurate, consistent, and compliant with regulatory requirements.

These services are designed to work together, creating a comprehensive modernization pathway. For example, once legacy applications are refactored and data is governed, autonomous operations can ensure the new environments run smoothly. The integrated approach is expected to significantly reduce the time and cost typically associated with digital transformation initiatives.

Historical Context and Partnership Background

IBM and ServiceNow have a long-established relationship dating back over a decade. They have previously collaborated on projects involving cloud computing, automation, security, IT service management (ITSM), and observability. This new collaboration deepens that relationship, focusing specifically on the intersection of AI and legacy system modernization. Historically, many enterprises attempted to modernize through 'rip and replace' strategies, but these often led to business disruption and data loss. The AI-powered incremental approach promoted by IBM and ServiceNow is less risky and allows organizations to maintain continuity.

John Aisien, senior vice president and general manager at ServiceNow, emphasized that most enterprises have the ambition to deploy agentic AI but lack the foundation to run it at scale. IBM provides the tooling to modernize systems and extend ServiceNow's data capabilities, while ServiceNow offers the platform to put that data to work across every business workflow. This synergy is critical as companies move from experimental AI projects to production-grade deployments.

Challenges in Legacy Modernization

Legacy systems are often considered the single biggest obstacle to AI adoption in large enterprises. These systems include mainframe applications written in COBOL, custom ERP modules, and decades-old database schemas that are poorly documented and difficult to change. The interconnected nature of these systems means that a change in one area can have unforeseen consequences in another. IBM's familiarity with these environments, especially its own mainframe ecosystem (z/OS), gives it unique credibility. The company has been investing heavily in modernizing its mainframe portfolio, including adding AI capabilities through IBM watsonx and integrating with cloud-native tools.

The new partnership will also leverage Red Hat Ansible Automation Platform, which is part of IBM's software portfolio, to automate the deployment and configuration of modernized components. HashiCorp tools (Terraform and Vault) are already widely used for infrastructure as code and secrets management, and their integration into ServiceNow workflows will provide a unified view of IT operations.

Implications for Enterprise IT

For IT leaders, the announcement signals a shift toward practical, vendor-supported paths for AI adoption. Rather than asking enterprises to rip out their existing systems, IBM and ServiceNow are offering a way to overlay AI capabilities on top of what they already have. This approach can accelerate time-to-value and reduce the capital expenditure required for full transformation. The three core services address common pain points: application modernization for technical debt, autonomous operations for operational efficiency, and data governance for trust and compliance.

As AI becomes more pervasive, the ability to integrate it with legacy systems will be a competitive differentiator. Enterprises that can leverage their historical data and existing processes while adding intelligent automation will be better positioned to innovate. The partnership also highlights the growing importance of platform play—where a workflow automation layer (ServiceNow) and an AI/automation infrastructure layer (IBM) come together to provide end-to-end solutions.

Both companies have committed to delivering these services in the second half of 2026, giving enterprises time to prepare their environments and data. Early adopters are expected to include large financial institutions, healthcare providers, and government agencies that operate extensive legacy systems and are under pressure to adopt AI while maintaining strict regulatory compliance.

The collaboration is also notable because it combines two distinct approaches: IBM's strength in data and AI platforms (watsonx) and ServiceNow's strength in workflow and agent-based automation. Together, they aim to provide a unified layer that can orchestrate AI-driven processes across the entire enterprise, from mainframe to cloud.

As the timeline for availability approaches, more technical details and use cases are expected to emerge. Industry observers will be watching to see how these solutions perform in real-world environments and whether they can deliver on the promise of seamless AI integration with legacy systems.

Source: Network World News