IBM and ServiceNow have announced a strategic collaboration designed to help enterprises unlock the power of artificial intelligence (AI) by modernizing their aging legacy systems. The joint initiative will combine IBM's deep expertise in AI, data management, and automation with ServiceNow's AI-powered workflow platform, offering a suite of services that promise to transform decades-old IT environments without requiring painful rip-and-replace projects. The companies assert that this partnership will enable organizations to evolve existing systems into AI-ready infrastructures, ultimately accelerating their adoption of agentic AI and autonomous operations.
The Challenge of Legacy Systems
For years, enterprises have struggled with the complexity of deeply interconnected legacy systems. These environments, often built around mainframes, proprietary databases, and custom applications, have accumulated over decades. They represent the backbone of critical business operations, but their rigidity has become a major obstacle to innovation. According to IBM and ServiceNow, the biggest barrier to moving fast on AI is precisely this tangled web of legacy infrastructure. Many organizations have attempted modernization in the past, only to be thwarted by the risks, costs, and operational disruptions involved. The new partnership aims to change that narrative by providing a practical, phased approach that leverages AI itself to help untangle legacy dependencies.
By combining IBM's strengths—particularly in mainframe environments and large-scale system integration—with ServiceNow's cloud-native workflow and agent management capabilities, the two vendors believe they can offer enterprises a clear path forward. John Aisien, senior vice president and general manager for central product management, security, and risk at ServiceNow, highlighted the core issue: '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.'
Three Core Services for 2026
The collaboration will deliver three primary services, all slated for availability in the second half of 2026. These services target the most common pain points in legacy modernization: application refactoring, infrastructure automation, and data governance.
Application Modernization
This service aims to scan and refactor legacy applications using a combination of IBM tools including Bob (an AI-powered code analysis and refactoring platform), Enterprise Application runtime (Java), and watsonx.data. The goal is to help enterprises bring existing applications into the AI era without starting from scratch. By automating much of the discovery, mapping, and transformation process, IBM and ServiceNow claim organizations can dramatically reduce the time and cost associated with modernizing core systems. The service will also leverage service mapping and dependency analysis from ServiceNow to ensure that changes do not disrupt other interconnected applications.
Autonomous Infrastructure Operations
This offering integrates a powerful stack of automation and observability tools—Red Hat Ansible, IBM Bob, Instana, HashiCorp Terraform, and HashiCorp Vault—directly into ServiceNow’s IT workflows. The result is an environment where infrastructure issues can be detected, remediated, and resolved before they impact business operations. The autonomous operations service uses AI-driven event correlation and root cause analysis to trigger automated remediation via predefined playbooks. This aligns with the broader industry trend toward AIOps (Artificial Intelligence for IT Operations), where machine learning models help maintain system health proactively. For enterprises running legacy systems that lack native monitoring capabilities, this service provides a bridge to modern observability without requiring a complete infrastructure overhaul.
Data Governance
Data is the lifeblood of AI, and many legacy systems contain valuable data trapped in silos with inconsistent quality and governance. The data governance service extends ServiceNow’s Workflow Data Fabric with IBM watsonx.data to unlock capabilities such as data quality monitoring, observability, master data management, and an integrated data catalog. This enables mutual customers to track and manage their AI-ready data across hybrid environments. By providing a unified view of data assets and enforcing governance policies automatically, the service aims to reduce the risk of bias, compliance violations, and poor model performance. IBM and ServiceNow emphasize that this governance layer is critical for building trust in AI initiatives at scale.
A Long-Standing Relationship
The partnership between IBM and ServiceNow is not new. The two companies have collaborated for years across a wide range of initiatives, including cloud computing, automation, security, IT service management (ITSM), and observability technologies. This history provides a strong foundation for the new AI-focused services. Both companies recognize that enterprise AI adoption requires a holistic approach that spans not only algorithms and models but also the underlying systems and data that feed them. By combining their respective portfolios, they can offer a more complete solution than either could alone.
IBM, with its extensive experience in mainframe modernization, brings credibility to the legacy conversation. The company has been supporting its Z-series mainframes for decades, and its professional services teams have deep knowledge of how to modernize these environments incrementally. ServiceNow, on the other hand, has become the de facto platform for IT workflow automation, with a strong track record of integrating with diverse legacy systems through its Now Platform. The two vendors have already co-developed solutions for IT service management and security operations, and this new AI initiative represents a logical expansion of their joint strategy.
Market Context and Competitive Landscape
The announcement comes at a time when enterprises are under intense pressure to adopt AI, yet many are held back by their existing IT architectures. According to industry surveys, a significant percentage of enterprise data still resides on mainframes and other legacy systems that are not optimized for modern AI workloads. Competitors such as Microsoft, Google, and Amazon Web Services have also been promoting AI modernization services, but IBM and ServiceNow are differentiating themselves by focusing specifically on the legacy-to-AI transformation journey, leveraging IBM’s unique mainframe expertise and ServiceNow’s workflow orchestration capabilities.
Additionally, the partnership aligns with the broader trend toward 'agentic AI'—autonomous software agents that can perform complex tasks across multiple enterprise systems. For such agents to be effective, they require clean, well-governed data and reliable infrastructure integration. The Services announced by IBM and ServiceNow directly address these prerequisites. By automating the modernization process itself, the companies are also practicing what they preach: using AI to enable AI.
Implementation and Customer Benefits
Customers adopting the new services can expect a structured, phased approach. For application modernization, IBM’s Bob platform will first perform a comprehensive scan of existing code and dependencies. It will then generate recommendations for refactoring—for example, breaking monolithic applications into microservices, migrating from proprietary databases to more open standards, or wrapping legacy code with APIs. ServiceNow’s workflow layer will then help orchestrate the changes across teams and track progress in real time.
In the autonomous infrastructure operations service, the integration of Ansible and Terraform with ServiceNow will allow IT teams to define infrastructure as code (IaC) and automate remediation workflows. For example, if a legacy server begins to experience high latency, Instana will detect the anomaly, ServiceNow will create an incident, Ansible will execute a predefined playbook to restart services, and Terraform will ensure that the underlying configuration remains compliant. All of this can happen without human intervention, dramatically improving system uptime and reducing the burden on overworked IT staff.
Data governance benefits are perhaps the most transformative. Many enterprises struggle with data silos that make it impossible to feed high-quality data to AI models. By integrating watsonx.data with ServiceNow’s Data Fabric, organizations can create a unified metadata layer that spans mainframe, cloud, and on-premises data sources. The ServiceNow Data Catalog will automatically inventory and classify data assets, while IBM’s AI tools will monitor data quality and suggest corrections. This sets the stage for more reliable AI outcomes and helps organizations comply with data protection regulations.
IBM and ServiceNow have both invested heavily in AI research and development. IBM’s watsonx platform includes not only data management but also a suite of foundation models and AI governance tools. ServiceNow’s AI platform, embedded in its Now Platform, provides out-of-the-box machine learning models for ITSM, customer service, and HR. The joint offering will likely extend to include these capabilities, enabling customers to build and deploy AI agents that can operate across their legacy systems with minimal disruption.
The timeline for availability—second half of 2026—reflects the complexity of integrating these technologies and the need for rigorous testing with early adopters. The companies plan to work closely with a set of design partners to validate the services before general release. This cautious approach is wise, given the high stakes involved in legacy system modifications. A misstep could cause outages that ripple across critical business processes.
Ultimately, the IBM-ServiceNow partnership represents a pragmatic response to a long-standing problem. Rather than telling enterprises to rip out their mainframes and start fresh, the two vendors are offering a bridge to the AI future. By combining IBM’s systems-level expertise with ServiceNow’s workflow orchestration, they aim to make legacy modernization not just possible but efficient. Whether the services will achieve the scale and adoption the companies hope for remains to be seen, but the direction is clear: AI is coming to even the most entrenched enterprise environments, and it is being built on top of the systems that have run business for decades.
Source: Network World News