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Using AI To Up Your ITSM Game.


AI or artificial intelligence has the potential to transform IT Service Management. Applied appropriately it can streamline processes and improve customer experience. This blog will look at how AI can be used so we can collectively up our ITSM game.

What is AI?

AI is the application of technology to simulate, replace or improve on the work of a human. To be truly effective AI systems need to demonstrate at least some of the following traits; problem solving, learning, planning and reasoning. AI technologies may include machine learning, virtual assistants or natural language processing aka the three pillars of AI:

  • Machine learning; a field of science that learns from data patterns and is then able to make decisions or recommendations
  • NLP – natural language programming is the interaction of intelligent machines using a natural language to communicate with each other
  • Virtual agents – also known as self-service. These are digital assistants that provide solutions drawn out of data models and previous interaction history. This also facilitates self-service and a consistent user experience. Some real-life examples include Amazon’s Alexa or the Siri virtual assistant offering from Apple.

How can it be applied to ITSM?

AI is the science of making intelligent devices. It can be used to automate processes by drawing patterns from data and predicting solutions; enabling your technology to learn over time which will improve accuracy and usability. In time this will enable it to provide an automated response to a common prompt. A recent Gartner research article found that IT organisations spend over 66% of their resources on day-to-day operational activities – all things that are routine and have the potential to be automated. Here are some examples in the ITSM world:

  • Incident Management
  • Problem Management
  • Request Management
  • Change Control
  • IT Security

Incident Management

Incident management is the front of house practice in ITSM. Everyone in your organization; from the CEO to the intern on their first day will need to ask IT for help at some stage. AI can support incident management by the provision of self-service portals, where the user can log their own incident and be prompted with suggestions from a pre-populated knowledge base so that they can self-help if appropriate. If the incident is something that requires the intervention of technical support, AI can be used to prompt the service desk technician with suggested methods to fix the issue based on previously raised issues related to that service.

Problem Management

Problem management is the practice that identifies that root cause of incidents and provides interim and permanent resolutions. Advances in big data and analytics mean improvements in predictive and correlative capabilities for ITSM tools. AI and machine learning can use analysis of previously logged incidents, and user behavior patterns can predict potential issues, reduce faults using self-healing technologies, or preempt and fulfill user requests proactively.

Request Management

Request management manages the lifecycle of service requests from the first point of contact to delivery and customer closure. AI can be used to automate the request logging process so instead of a customer calling the service desk, they can visit a self-service portal to log the request directly or interact with a text chatbot. The required product or service is selected and delivered to that user’s device in a seamless experience.

Change Control

Change control manages IT and technical change and is an ideal candidate for automation and AI. Some examples of how AI can improve your change control offerings include:

  • Pre-approving certain change types below a pre-agreed risk threshold
  • Using models to template frequently requested changes
  • The use of delegated authority to automatically authorise changes to particular service and infrastructure types.

IT Security

The use of AI can be extremely beneficial in improving IT security because it is trained to learn, develop, grow and adapt using the source material and data it is given, An AI system is in a constant state of change by its very nature, just as malicious agents are continuously developing new threats in the cyber security environment. AI can be used to interpret new security data and prioritize issues for security teams to address. Another application of AI in an IT security environment is the use of signature based systems that recognise and block malicious code and exploits.

Final Thoughts

Using AI in ITSM processes will make them leaner, more efficient and less prone to human error, but care must be used to not treat AI as a silver bullet. If you automate too much you risk hiding behind the technology and missing out on relationship management and engaging directly with your stakeholders. A balanced approach however means that you can improve user experience, make IT more responsive and improve customer satisfaction. What’s not to love?