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EasyVista recently shared insights from research on the current state of AI adoption within IT service management (ITSM). The findings indicate that while reported adoption is widespread, only a small proportion of enterprises describe their approach as fully mature and proactive, at 12%.
The global survey of 1,100 IT professionals found that 95% of organisations have incorporated AI into their ITSM processes. These tools are most commonly used to support workflow automation, improve reporting, and assist with incident prevention. Although many respondents report satisfactory outcomes, particularly in structured use cases such as task automation, there remains caution around deploying AI without human oversight. This is often linked to the absence of clearly defined return-on-investment (ROI) metrics.
The research also points to a shift towards more integrated, workflow-focused applications of AI, rather than isolated or fragmented implementations. Within this context, AI capabilities are being embedded into ITSM platforms, including features such as EV Pulse AI Conversations, which are designed to support service interactions.
At the same time, scaling AI use presents operational challenges. Key issues include weak process discipline, limited integration across systems, and poor data quality. These factors can restrict the extent to which organisations are able to realise value from AI.
Broader organisational constraints also play a role. Enterprises report challenges such as budget limitations (38%), shortages of skilled IT personnel (36%), and integration gaps (35%). Additional barriers specific to AI adoption include integration complexity (18%), lack of expertise (13%), and cost concerns (13%).
Overall, the findings describe an ongoing progression in how AI is being used within ITSM, with continued emphasis on improving operational maturity and workforce capability to support more effective and scalable adoption.
"AI is already widely adopted in ITSM, particularly in early-stage use cases, and that is an important signal,” said Keith Andes, Head of Product Marketing, EasyVista. “However, leader sentiment is outpacing reality, as the value of global deployment outcomes are not yet proven. This research shows that weak process discipline, poor integration, and low-quality data limit what AI can consistently deliver. Scaling from here will require organizations to invest in operational maturity."
