The Role of AI in IT Service Management – Hype vs Reality

Artificial Intelligence is no longer a futuristic concept. It is already embedded in many core business functions, and IT service management is no exception. But as organizations scramble to adopt the latest AI-powered tools, a crucial question emerges: Is the hype around AI in IT services delivering real operational value, or is it just another layer of complexity?

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The reality is more nuanced. While AI promises to streamline ticket resolution, predict outages, and reduce operational costs, many IT teams still struggle with basic service delivery. The challenge is not merely technological but structural, strategic, and deeply human. Organizations must balance innovation with stability to make AI work, a paradox at the heart of modern IT leadership.

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Understanding the leadership paradox in IT

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IT leaders are both guardians of stability and enablers of innovation. This dual role creates a natural tension. On one hand, they must ensure systems are secure, stable, and compliant. On the other hand, they must push boundaries and adopt new technologies like AI to remain competitive.

This is the leadership paradox. Organizations must recognize that true transformation is about adding AI tools and building capacity. Without a strong operational foundation, AI amplifies inefficiencies instead of solving them.

Hype versus current IT reality

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While the marketing narrative around AI in IT services is often glowing, the actual state of IT service management paints a different picture:

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• Up to 70% of recurring incidents remain unresolved.
• 42% of incidents stay open for more than three days.
• 20–30% of tickets are reopened due to poor initial resolutions.

This reflects an industry still bogged down by reactive processes, siloed data, and limited capacity—not exactly an environment where AI can thrive.

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Building bandwidth before adopting AI

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One of the biggest misconceptions is that AI can fix poor operations. In reality, adding AI to broken workflows only scales inefficiencies. Before layering AI into IT and ERP service management, organizations need to free up capacity through structured improvements.

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The Balance Blueprint approach offers a phased strategy:

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1. Foundational Improvements: Help desk optimization, configuration management, and root cause analysis.
2. Operational Enhancements: Automation of repetitive tasks and vulnerability management.
3. Strategic Advancements: Shifting internal capacity and leveraging outsourcing to enable scalable and sustainable growth.

These footholds must be secured before AI can deliver sustainable value.

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Ethical innovation and vendor responsibility

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Vendors play a critical role in guiding AI adoption. But many push solutions without first assessing readiness. Ethical innovation means aligning tools with an organization’s culture, capacity, and strategic goals.

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IT leaders deserve better than one-size-fits-all platforms. They need tailored, responsible solutions that enhance, not destabilize, their environment.

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From firefighting to strategic leadership

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The ultimate goal is transitioning IT from a reactive “firefighting” model to a proactive, strategic role. AI can be an enabler—but only when foundational operations are sound and leadership metrics are in place.

High-performing IT teams spend just 5% of their time on unplanned work, compared to 35-45% for the average team. The difference lies in technology, leadership focus, process discipline, and capacity planning.

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Final thoughts: Delivering on the AI promise

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The promise of AI in IT services is real—but only when grounded in reality. Hype will not fix broken systems. Leadership that balances stability with innovation will.

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Organizations that prioritize structured improvement, assess their capacity, and pursue ethical innovation will be the ones that realize the true power of AI in IT services—not just as a tool, but as a catalyst for long-term transformation in IT service management.