Bengaluru, 4 Apr, (CXO Media): Kyndryl has introduced a framework aimed at helping enterprises prepare their IT environments for autonomous AI-driven operations.
The company announced the launch of Agentic Service Management, a structured model designed to support organizations transitioning from traditional IT service management to workflows capable of supporting autonomous software agents. The development reflects a growing industry need to modernize legacy IT systems that were not originally designed to support large-scale AI deployments.
Enterprises across sectors have accelerated investments in artificial intelligence in recent years, but many continue to face operational challenges in translating these investments into measurable outcomes. According to insights referenced by the company from its readiness research, governance limitations, fragmented workflows and outdated operational controls remain key barriers to scaling AI initiatives.
Traditional IT service models largely rely on manual ticket-based processes and human oversight. However, AI-driven environments require standardized governance, defined operational controls and continuous monitoring frameworks to ensure reliability, security and accountability. Experts note that the absence of these supporting structures can limit the effectiveness of AI systems and increase operational risk.
Kyndryl’s framework incorporates maturity models, assessment tools and implementation blueprints intended to help organizations evaluate their readiness for AI-native operations. The model focuses on establishing measurable adoption stages, strengthening governance practices and aligning IT workflows with emerging industry standards for AI-enabled environments.
The announcement comes at a time when enterprises are moving beyond experimental AI deployments toward production-scale applications across hybrid and multi-cloud infrastructures. As automation expands across IT service management and infrastructure operations, demand for standardized governance models and structured implementation approaches is expected to grow.
