Navigating AI integration in IT: the path to responsible scaling

A recently published global research report by Ivanti highlights the increasing role of AI in modern IT operations, alongside attention to how governance structures are developing at a slower pace than adoption, which may create challenges as automation expands.

IT departments are facing ongoing demands to improve efficiency and resilience. This has contributed to rapid uptake of AI technologies. In many cases, the speed of adoption has exceeded the development of comprehensive governance models, creating gaps in oversight and accountability. As AI becomes more embedded in everyday IT processes, addressing these gaps is increasingly part of organisational planning.

The research indicates that organisations with higher levels of AI maturity report gains in efficiency, confidence, and operational resilience. These organisations also describe benefits such as improved proactive issue detection and productivity improvements. At the same time, organisations in earlier stages of AI adoption are continuing to expand their use and development of these systems.

Key findings from the report

• Integration beyond experimentation: More than half of surveyed organisations have moved beyond early experimentation with AI, with AI now being used across a range of IT workflows.
• Autonomous management: Organisations with more mature AI adoption report using AI for autonomous endpoint management, including automated resolution of certain issues without human intervention.
• Improved data and knowledge sharing: Around half of IT professionals report that AI is supporting collaboration and knowledge sharing, helping to reduce long-standing data silos.
• Governance and accountability: While many organisations have AI-related policies in place, the report notes that clear accountability structures are not always fully established.

Even among more mature adopters, around one-third of IT operations are reported to lack fully embedded governance frameworks for AI oversight.

Overall, the findings describe differences in AI maturity across organisations. They also note that as AI is scaled within IT environments, governance, data quality, and oversight frameworks remain relevant considerations for maintaining reliable operations.