IBM and ServiceNow have announced a major collaboration aimed at helping enterprise customers bridge the gap between aging legacy systems and the rapidly advancing world of artificial intelligence. The partnership, which combines IBM’s deep expertise in data, automation, and large-scale systems with ServiceNow’s AI-powered workflow platform, is designed to enable organizations to evolve their existing infrastructure rather than undergoing costly and disruptive replacements.
Decades of deeply interconnected legacy systems have long been identified as the single biggest obstacle to adopting AI at scale. Many enterprises run critical business processes on mainframes, midrange servers, and custom applications that were built long before AI and machine learning became mainstream. These systems often contain invaluable data but are notoriously difficult to integrate with modern AI tools. By bringing together IBM’s legacy system expertise—including its mainframe environment and extensive portfolio of enterprise applications—with ServiceNow’s intelligent workflow and agent management capabilities, the two companies aim to unlock the potential of agentic AI across the enterprise.
The announcement was made by John Aisien, senior vice president and general manager of central product management, security, and risk at ServiceNow. “Most enterprises have the ambition to deploy agentic AI, but lack the foundation to run it at scale,” Aisien said. “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.”
The collaboration will focus on three core services, all slated for availability in the second half of 2026. The first is application modernization. This service leverages IBM’s Bob tool, Enterprise Application runtime for Java, and watsonx.data to scan and refactor legacy applications. Instead of rebuilding systems from scratch, enterprises can gradually transform their existing codebases to be AI-ready. This approach is particularly valuable for organizations running critical COBOL-based applications on mainframes, which IBM has supported for decades. Modernization reduces risk, preserves business logic, and accelerates the path to AI adoption.
The second service is autonomous infrastructure operations. This integrates Red Hat Ansible, IBM Bob, IBM Instana, HashiCorp Terraform, and HashiCorp Vault directly into ServiceNow’s IT workflows. The goal is to create a self-healing IT environment that can detect, diagnose, and resolve incidents before they impact business operations. By combining observability data from Instana with automated remediation through Ansible playbooks and ServiceNow’s incident management, enterprises can drastically reduce mean time to resolution and free up IT staff for higher-value tasks. This level of automation is essential as companies scale their AI workloads, which demand reliable infrastructure.
The third service focuses on data governance. Here, the partnership extends ServiceNow’s Workflow Data Fabric with IBM watsonx.data to deliver capabilities like data quality, observability, and master data management. The ServiceNow Data Catalog will be used to give mutual customers a unified view of their data lineage, quality, and readiness for AI consumption. As organizations rush to train and fine-tune AI models, having clean, trustworthy data is paramount. This service ensures that data residing across legacy databases, cloud platforms, and enterprise applications can be properly cataloged, governed, and accessed by AI agents without exposing the organization to compliance or accuracy risks.
The partnership between IBM and ServiceNow is not new. The two vendors have a long history of working together to help large enterprises implement cloud computing, IT service management, automation, security, and observability solutions. This latest collaboration deepens that relationship by addressing what many analysts see as the next frontier in enterprise IT: integrating AI with the installed base of critical legacy systems that cannot simply be replaced overnight.
Legacy modernization has been a persistent challenge for decades. Many Fortune 500 companies still run core banking, insurance, supply chain, and manufacturing systems that were written in COBOL, PL/I, or other older languages. These systems are often highly customized and tightly coupled with business processes. Attempts to rip and replace them have a poor track record, often leading to budget overruns, project delays, and even business disruption. The IBM-ServiceNow approach offers a middle path: keep the existing systems in place but overlay them with an AI-powered smart layer that can understand, monitor, and eventually automate many of the manual tasks that IT teams currently perform.
Agentic AI—where AI systems can autonomously plan and execute actions to achieve goals—is a key concept behind the partnership. For agentic AI to work reliably at scale, it needs access to accurate, real-time data from all parts of the enterprise, including legacy systems. Without proper integration, agents may make decisions based on incomplete information, leading to errors or missed opportunities. ServiceNow’s AI Platform provides the workflow orchestration, while IBM’s tools ensure the underlying data is exposed in a secure and governable way.
The market for legacy modernization with AI is enormous. According to a 2025 report from McKinsey, more than 70% of large enterprises still operate systems that are over 20 years old, and spending on maintenance consumes a significant portion of IT budgets. Meanwhile, spending on AI infrastructure is growing at over 30% annually. The IBM-ServiceNow offering targets the intersection of these two trends, helping enterprises redirect some of their maintenance spend toward innovation.
Both companies bring complementary strengths to the table. IBM has decades of experience managing the most complex IT environments on the planet, including mainframes that process trillions of transactions annually. Its recent acquisitions—such as Red Hat, Instana, and the data governance assets that became part of watsonx—have strengthened its ability to support hybrid cloud and AI workloads. ServiceNow, on the other hand, has become the leading platform for enterprise workflow automation, with its Now AI platform providing out-of-the-box agents and low-code tools that allow business users to build automations without deep programming skills.
The joint services are expected to be particularly attractive to industries with heavy regulatory compliance requirements, such as financial services, healthcare, and government. In these sectors, data governance and auditability are non-negotiable. The integration of ServiceNow’s Workflow Data Fabric with IBM watsonx.data gives organizations a clear lineage trail, which is critical for meeting regulations like GDPR, HIPAA, and SOX.
Early adopters may include large banks that have been trying to modernize their core banking systems for years. Many have invested in APIs and microservices but still struggle with customer data scattered across legacy databases. With the new services, these banks could expose their mainframe transaction data to AI agents via ServiceNow workflows, enabling faster fraud detection, personalized customer experiences, and more efficient compliance reporting.
Another promising use case is IT operations itself. ServiceNow’s IT operations management modules, combined with IBM’s Instana observability and Ansible automation, can create a closed-loop system where AI agents monitor infrastructure performance, predict failures, and automatically trigger remediation workflows. This reduces the need for human intervention in routine tasks and allows IT teams to focus on strategic initiatives such as deploying generative AI applications.
The partnership also addresses concerns about data sovereignty and security. IBM’s portfolio includes IBM Cloud for Financial Services and other industry-specific clouds that meet strict regulatory requirements. ServiceNow’s platform can route data through these secure environments, ensuring that sensitive information never leaves the enterprise’s control. This is particularly important as governments around the world enact stricter data localization laws.
Looking ahead, IBM and ServiceNow plan to release more details about pricing and availability closer to the launch window in the second half of 2026. Industry analysts expect the services to be offered as bundled packages, with professional services from both IBM Consulting and ServiceNow’s partner ecosystem. The companies have also indicated that they will invest jointly in co-innovation labs where customers can prototype and validate their modernization strategies before committing to full-scale projects.
For enterprise IT leaders, the message is clear: legacy systems don't have to be a barrier to AI adoption. With the right combination of modernization tooling and workflow automation, even the oldest mainframe applications can become part of an intelligent, automated enterprise. The IBM-ServiceNow partnership represents one of the most concrete efforts to date to make that vision a reality.
Source:Network World News