ITSM Trends in 2026

ITSM in 2026: Strategic context and market direction

The market defines rising complexity, increasing ticket volumes, and greater expectations from business across the board. In 2026, digital services failures will lead to downtime, lost productivity, or a service outage. Losing a productivity/service isn’t an option. On top of this, enterprises are addressed with new data protection risks, regulatory pressures, and the growing impact of AI on operational outcomes.

The data from the industry, in particular, Gartner, suggests a shift in AI, which has traditionally been applied in a siloed manner, to integrated operational intelligence. This burgeoning paradigm shift creates significant challenges to the nature of modern ITSM. Enterprises will need to consider the balance of control and innovation.

From AI assistance to agentic automation

The implementation of AI models is a paradigm shift across IT service management, with the expected trend in 2026 being the implementation of AI. Simple copilot models have historically been relied on; models where AI service features guide agents with a suggestion. Today, with agentic, we are moving into a new paradigm.

Organizational processes, in an agentic fashion, are being automated. Certain processes are repetitive and structurally aligned (such as password resets, access provisioning, and incident triage). Agentic AI platforms, within low-code and controlled orchestration, reduce applied manual efforts and set parameters to retain human oversight.

This evolution promotes quicker resolutions, though only when deployed within low-risk situations and governed by clear parameters.

Governance-first ITSM as a foundation

As AI-driven capabilities expand, governance becomes a central requirement rather than a secondary concern. In 2026, enterprises adopt a governance-first approach to ITSM, ensuring that automation, data usage, and decision-making remain transparent and auditable.

Effective governance includes:

• Clearly defined framework structures
• Clear policies for AI usage
• Strong compliance alignment
• Robust explainability for automated outcomes

Without these safeguards, organizations risk exposing sensitive data, increasing change risk, and undermining trust in service operations. Responsible AI is therefore essential for sustainable ITSM solutions.

Workflow simplification and scalable automation

The design and fragmentation of workflows have represented barriers to the effective functioning of ITSM. In 2026, companies will begin to redesign their workflows to enable seamless automation across services. Workflows that are simplified in ITSM require less manual work and lead to more predictable, consistent results.

Using technologies like RPA (robotics process automation), and workflow automation have been particularly effective in the management of incidents and changes that require formal approval and changes.

Confidence comes from the structure of this approach which allows services to remain strong and reliable even in the most stressful situations.

Observability, AIOps, and predictive operations

The combination of AIOps, observability and, perhaps the most important of all, IT service management workflows, is yet another example of the most prevalent trends in ITSM. A mix of operational data and pattern recognition allows companies to identify emerging trends and subsequently implement predictive analytics to avoid the disruption.

Predictive analytics helps IT avoid disruption with proactive resolutions so as to improve operational stability and mitigate the adverse impact of services. Ultimately, AI-based analytics improves service management.