The Legacy of IT Service Management Is Holding You Back

For more than twenty years, IT Service Management (ITSM) has served as the operational backbone for managing incidents, problems, and changes. Yet in 2025, the complexity of enterprise IT environments has outpaced the frameworks and processes once deemed cutting-edge. Despite improvements in incident response, asset management, and CMDB maintenance, the reality is sobering — disruption remains costly, data remains unreliable, and siloed processes continue to slow progress.

A broader rethink is underway. Traditional ITSM, with its rigid structures and outdated assumptions, is giving way to a more adaptive model. The future lies in holistic, business-centric service management—not bound to “IT” but embedded across the enterprise. The goal isn’t more process—it’s smarter service. End-to-end visibility, real-time responsiveness, and tighter alignment with business outcomes are now the imperatives. We have outlined the many reasons this transition is needed in our recent report: The ITIL™ Dilemma: Balancing Investment With Value In IT Service Management.

From Theory to Action: 10 Ways to Improve Service Management Right Now

To break free from this legacy-rooted cycle, organizations must shift their mindset. The call to action is clear: stop chasing maturity through more governance and process and start building agility through service-centric thinking. It’s about managing services end-to-end, from customer experience to operational execution, in a way that is both human-centered, automated, and data-driven per these key actions:

  • Pivot to service management, not just ITSM. A crucial first step is abandoning the narrow focus on IT and embracing service management as a cross-functional discipline. This shift ensures that service delivery is not confined to technical teams but owned collaboratively across the business. It reframes support as a strategic function, one that delivers measurable value aligned with organizational goals, not just operational uptime.
  • Invest in new ways to automate. Too many organizations continue to postpone automation initiatives due to cost or capability gaps. But as system complexity grows, manual service management processes can no longer scale. Intelligent automation, coupled with observability platforms, provides a proactive edge, enabling systems to detect anomalies and initiate corrective action before they impact users. Now is the time to integrate automation into the operational roadmap, not treat it as a future consideration.
  • Focus on improving the employee experience. IT success hinges not just on resolution speed but on how employees experience support. Frictionless, hyper-personalized service is no longer a differentiator—it’s a baseline expectation. Data-driven support models can anticipate issues, reduce ticket volumes, and empower users with seamless self-service options. The service experience must evolve into something intuitive, intelligent, and largely invisible to the end user.
  • Unleash the potential of generative AI. Generative AI (GenAI) has matured past the experimentation stage. When deployed in production, it can compress workflows, streamline documentation, and enhance decision-making. Organizations report measurable gains, such as shaving minutes off routine transactions, resulting in significant cost savings and performance enhancements. GenAI isn’t just a novelty; it’s a force multiplier that’s ready for real-world deployment.
  • Begin experimenting with agentic AI. Agentic AI represents the next leap forward, moving from assistive models to autonomous decision-making systems. These agents can interpret data, respond to exceptions, and execute tasks independently. Implementing them in non-production environments, ideally with trusted technology partners, enables teams to assess the value and risk associated with them while preparing for a broader rollout. This is where AI begins to act, not just inform.
  • Share, communicate, and collaborate. High-performing operations demand high-trust environments. Knowledge hoarding, siloed thinking, and communication breakdowns remain common challenges. Collaboration platforms must enable cross-functional dialogue and transparency. More importantly, employees must feel secure contributing what they know, understanding that shared knowledge fuels more intelligent systems and better outcomes across the board.
  • Get your knowledge management practices in order. AI and automation require structured, accessible, and trustworthy knowledge to function effectively. Most organizations struggle with disjointed and outdated content repositories. Rather than retroactively cleaning legacy data, the focus should shift to building future-ready knowledge. This means embedding capture into daily workflows, ensuring contextual accuracy, and treating knowledge as a dynamic asset, not a static archive.
  • Invest in the success of your people. Technology cannot advance without human capability keeping pace. From training in prompt engineering to developing AI governance expertise, continuous learning must become part of the culture. Upskilling service desk personnel and educating end users alike ensures that automation initiatives are supported by a workforce equipped to manage, interpret, and improve them. IT teams should become centers of enablement, not just execution.
  • Align to common goals. Too often, IT operates in isolation, measuring success through operational KPIs tied to service management processes rather than strategic contribution. Instead, organizations should map initiatives to value streams, tracking how automation and AI improve productivity, reduce ticket volume, and support customer success. Journey-based metrics provide clarity and flexibility, allowing for iterative improvement and tighter alignment with business outcomes.
  • Avoid the extremes. Success rarely lies in radical swings. Centralization versus decentralization, agile versus waterfall, project to product, these binary decisions often lead to inefficiencies. The smarter approach is balance. Apply new technologies incrementally, test assumptions, and iterate based on feedback. This pragmatic strategy reduces risk, builds organizational confidence, and ensures sustainable transformation over time.

To learn more about these 10 approaches, watch our recent webinar: The ITIL™ Dilemma: Balancing Investment With Value In IT Service Management.

What Comes Next: Build Intelligently, Execute Relentlessly

This isn’t just a technological evolution—it’s a strategic reinvention. IT operations must stop chasing maturity through service management processes alone and begin delivering value through intelligence, adaptability, and alignment. The key lies in building smarter systems, empowering people, and leveraging technology not to replace the human element, but to give our best talent a new superpower.

Now is the time to abandon the legacy mindset. Start where you are. Think in systems. Act with clarity. These ten actions offer a clear path to modernizing operations in a world that no longer tolerates slow, siloed, or reactive IT. The organizations that succeed will be the ones that stop managing complexity and start mastering it.

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