Kyndryl offers AI-powered services for IBM Z mainframe management
Kyndryl has introduced new AI-powered managed services aimed at customers using IBM Z mainframe systems, with the objective of enhancing application development speed, operational flexibility, and business insight generation.
The company highlighted the operational and strategic aspects of integrating agentic Artificial Intelligence (AI) within their deep mainframe expertise to address challenges such as complexity in application and infrastructure management, decision-making processes, and talent gaps within customer organizations.
The technical framework incorporates agentic AI capabilities that support intelligent automation, orchestration of workflows, and integration with platforms such as Kyndryl Bridge and IBM watsonx Assistant for Z. This integration delivers functionalities including predictive analytics and service automation across mainframe infrastructure and software lifecycles.
The scope of these services extends to Kyndryl AI Assistant for Z, which embeds accumulated mainframe knowledge into operational workflows, aiming to accelerate platform management and mitigate skill shortages. Additionally, Kyndryl's approach utilizes intellectual property and collaborations with cloud hyperscalers to complement mainframe transformation efforts.
“Kyndryl is leading the way in providing world-class agentic AI-enabled delivery services to customers that will instill confidence in the mainframe's role as an engine of innovation for global enterprises,” said Hassan Zamat, Global Practice Leader for Core Enterprise 6 zCloud at Kyndryl. Skyla Loomis, General Manager of IBM Z Software, said, “Through our collaboration with Kyndryl, we're helping enterprises bring powerful AI capabilities to the core systems that run their business.”
Kyndryl's 2025 State of Mainframe Modernization Survey showed 88% of respondents have incorporated or plan to incorporate AI, including agentic and Generative AI (GenAI), within their mainframe environments, noting improvements in business agility, operational consistency, and cost savings, though 70% reported challenges in securing multi-skilled talent. Anticipated use cases include enhanced performance, resource allocation, fraud detection, and security threat assessment.