AI-driven ITSM trends to expect in 2025

As we settle into 2025, AI is no longer a tool of speculation; it has clearly established itself as the cornerstone of IT service management (ITSM), embedded in the very processes that drive IT service delivery, efficiency, and user satisfaction. Along with optimizing what's already in place, AI is enabling IT teams to rethink how services are designed, how issues are anticipated, and how support is delivered on a much larger scale. With this technology maturing rapidly, the discussion shifts to how AI will reshape ITSM in even more profound ways.

In this article, let’s explore the key AI trends that are likely to shape the future of ITSM.

The rise of agentic AI

In 2024, the focus was on embedding generative AI into ITSM practices, but the next wave of AI transformation is set to be more nuanced, where agentic AI will begin to take on increasingly complex tasks autonomously. By 2028, Gartner predicts that 33% of enterprise software applications will include agentic AI, a huge leap from where we are today. These advanced systems, powered by large language models (LLMs), are not bound by static prompts or decision trees, instead are dynamic software programs that are capable of thinking, learning, reasoning and acting on their own.

Picture this: an employee reports a broken laptop, and instantly, agentic AI springs into action. It diagnoses the issue, determines if a replacement is needed, checks inventory, places a new order, and coordinates delivery. The best part? All of this is done without human intervention, saving time, and accelerating resolutions. Unlike traditional AI systems, which rely on extensive training and constant updates, these AI agents will operate autonomously, leveraging data from existing tools, scaling and adapting in real time to meet evolving needs. With 24/7 support, they will not only resolve issues faster, but also enhance employee satisfaction.

However, the promise of agentic AI comes with key considerations. First, it's essential to evaluate the ROI before deployment since these systems can be exorbitant, requiring substantial GPU resource consumption for vendors, and yield only marginal productivity improvements. Second, agentic AI should be built on mature ITSM practices and clean data to avoid exacerbating inefficiencies. Finally, balancing autonomy with ethical responsibility is crucial to prevent harm or bias. With all these factors in place, in 2025, with agentic AI leading the way, IT teams will experience faster, smarter, and more intuitive IT service delivery.

The new era of AI-based ITSM metrics

As AI takes on a bigger role in ITSM, measuring the ROI will require new, AI-centric KPIs. These metrics help organizations understand how AI is driving value, enhancing efficiency, and improving IT operations. In 2025, organizations need to track metrics beyond traditional ones like resolution time, first-call resolution rate, and net promoter score. For instance, rather than just measuring the average time to resolution, organizations should look at how swiftly AI identifies and addresses issues by assessing incident or problem lead times. Supported by AI's ability to leverage proactive incident identification and clustering, this can help prevent issues before they turn into formal service tickets.

New AI-driven KPIs have been introduced. The ticket deflection rate measures the percentage of employee inquiries that AI chatbots can handle on their own, reducing manual ticketing efforts. The cost reduction per ticket metric reflects how much more cost-efficient the process becomes due to the automation powered by AI.

Additionally, human handoff rates will measure how often chatbot conversations require escalation to a human agent, and how much faster technicians can resolve tickets thanks to the context and details gathered by AI during the initial interaction. Other metrics that measure the quality of AI interactions with employees could include AI fallback rates and satisfaction rates.

Closing the IT skills gap

As we embrace AI's potential, the demand for skilled professionals is increasing, and organizations are scrambling to fill those gaps. IDC forecasts that by 2026, over 90% of organizations globally will experience the impact of the IT skills shortage, leading to an estimated $5.5 trillion in losses due to product delays, reduced competitiveness, and lost business opportunities. In 2025, to prevent these monetary mishaps, businesses are expected to double down on upskilling their existing talent pool. Low-code and no-code tools will make it easier for non-technical employees to embrace digital transformation.

Organizations will also leverage AI systems to identify, organize, and distribute enterprise-specific IT knowledge. According to Gartner, by 2027, generative AI will create more IT support and knowledge-based articles than humans will. This will allow IT staff to troubleshoot faster, resolve issues more efficiently, and improve overall productivity. As organizations scale their AI initiatives, automated ITSM workflows, such as orchestrated run-books, will further reduce manual work by automating repetitive tasks and enabling teams to focus on higher-value projects.

In line with the need for upskilling, many organizations will appoint specialized leadership roles, such as chief AI officers, chief data officers, and AI trainers, to work closely with CIOs. These leaders will play a crucial role in driving AI adoption and talent development. This way, organizations will ensure a seamless intersection of technology and people, empowering teams to not only adapt to AI but also develop the skills necessary to thrive in a fast-evolving landscape.

ITSM practices redefined by AI

In 2025, AI's transformative impact on core ITSM practices will be undeniable. Our survey last year, The State of AI in ITSM - 2024 and beyond, revealed that the most significant AI-driven changes will be seen in incident management (79%) and knowledge management (73%), with service request management (63%) following closely behind.

Key insights from the survey show how AI will impact specific ITSM practices.

• Incident management: AI will take over routine diagnostics, issue resolution, and ticket creation, significantly reducing resolution times and preventing downtime.
• Knowledge management: AI will automate content categorization, knowledge base updates, and provide real-time access to relevant information.
• Service request management: AI will streamline software requests and break-fixes, enabling faster and a more personalized service delivery.
• Problem management: AI will enable proactive identification of patterns across incidents, allowing teams to predict and resolve potential issues before they escalate into major outages.
• Change management: AI will gradually assist with impact analysis and optimization of deployment processes, making changes free of risks and reducing disruptions.

While much of the spotlight on AI has focused on IT service management, AI is also making waves in IT asset management. ITAM is set to be transformed by AI and we discuss three key ways in our detailed article.