• The evolution of natural language processing and machine learning applications has led to specialized AI-assisted toolsets that promise to improve the efficiency and timeliness of IT operations.

Our Advice

Critical Insight

• These are early days. These AI-assisted toolsets are generating a considerable amount of media attention, but most of them are relatively untested. Early adopters willing to absorb experimentation costs are in the process of deploying the first use cases. Initial lessons are showing that IT operations in most organizations are not yet mature enough to take advantage of AI-assisted toolsets.
• Focus on the problem, not the tool. Explicit AI questions should be at the end of the list. Start by asking what business problem you want to solve.
• Get your house in order. The performance of AI-assisted tools depends on mature IT operations processes and reliable data sets. Standardize service management processes and build a knowledgebase of structured content to prepare for AI-assisted IT operations.

Impact and Result

• Don’t fall prey to the AI-bandwagon effect. AI-assisted innovations will support shift-left service support strategies through natural language processing and machine learning applications. However, the return on your AI investment will depend on whether it helps you meet an actual business goal.
• AI-assisted tools presuppose the existence of mature IT operations functions, including standardized processes, high-quality structured content focused on the incidents and requests that matter, and a well-functioning ITSM web portal.
• The success of AI ITSM projects hinges on adoption. If your vision is to power end-user interactions with chatbots and deploy intelligent agents on tickets coming through the web portal, be sure to develop a self-service culture that empowers end users to help themselves and experiment with new tools and technologies. Without end-user adoption, the promised benefits of AI projects will not materialize.