IT service management (ITSM) has long been touted as a way for organizations to optimize the costs associated with the use of technology while simultaneously enabling the realization of recognizable business value. And some organizations have succeeded in doing just that… to some degree.
Frequent service requests have been designed and instantiated within ITSM to enable consistent and repeatable fulfillment of common consumer needs, such as password resets or delivery of a new laptop computer. Centralized service desks were established, providing consumers with a single point of contact for getting help or advice regarding IT-provided services.
However, these frequent and highly repetitive requests for IT support are typically labor-intensive and very reactive. Because human resources at the service desk are finite, IT often cannot scale adequately to meet increases in support demand. Many ITSM solutions provide limited or pre-defined reporting capabilities, limiting IT’s ability to gain insights into process performance or analyze repeating patterns within day-to-day work.
This reactive, backward-looking approach to ITSM seems only to drive costs, dilute the perception of value, and wastes human talents and energies.
How AI helps IT become “better, faster, cheaper”
The introduction of AI is changing the game for IT.
AI-powered automation of tedious and repetitive tasks in IT operations can help reduce error and increase productivity. One of AI’s most powerful capabilities is its ability to optimize IT daily work activities, like monitoring servers and networks, planning capacity, ensuring security, and allocating resources. Applying AI within IT systems and infrastructure reduces the need for manual intervention and enhances effectiveness and dependability.
AI is just what ITSM needs
When AI capabilities are extended into ITSM, ITSM transforms from being a theoretical concept to a value-added capability. Here are a few examples of how introducing and using AI-capable technologies helps organizations realize enhanced ITSM capabilities.
Incident Management
Incident management is typically the most visible ITSM practice within an organization. With AI, many incidents can be resolved in real-time. AI can automatically triage and classify incidents and apply fixes where necessary, improving MTTR. When incidents cannot be resolved automatically or front-line, the ticket can be sent to the proper IT team for resolution.
Knowledge management
The more accurate the knowledge base is within an ITSM application, the more efficiently and effectively an AI tool can help IT improve ITSM performance. Based on a search criteria or IT issue, AI tools provide appropriate information to a question or respond with the most likely corrective action regarding an IT issue. As AI tools use machine learning to analyze past experiences, the knowledge base continually becomes more accurate with provided responses to IT staff and customers.
Problem Management
An ongoing challenge for many organizations is utilizing problem management to improve service delivery and eliminate potential or recurring incidents. Like most current organizational ITSM capabilities, problem management is a very reactive practice. That changes with AI. AI can provide real-time insight into service performance and identify potential problems and issues before they impact service consumers. Using machine learning capabilities, AI can identify patterns and predict future issues – issues that can be addressed proactively before impacting business productivity.
Service Desk
As marketplace demands continue to evolve and technology environments grow in complexity, the ability of a service desk to deliver timely and effective end-user support becomes even more important. By using AI-enabled chatbots that leverage natural language processing (NLP), service desks can provide 24/7 support to service consumers. These chatbots can provide automated issue resolution, self-service options, and access to knowledge bases, allowing users to find answers independently. AI-powered chatbots can intelligently route incidents, maintain contextual conversations, and provide personalized support based on user preferences.
Service Request Management
AI enables service request workflows to become proactive through automation. Many service requests tasks, such as password resets, access provisioning, and providing advice or guidance, can be automated through a pre-defined chatbot dialog flow.
Monitoring and Event Management
AI and machine learning can be leveraged to recognize events and monitoring alerts to automate corrective actions through other ITSM practices, such as incident management or change management, all without human intervention.
Extend what AI does for ITSM to ESM
However, the benefits of introducing AI within an organization’s ITSM environment needn’t stop with IT. These same benefits can be realized within an implementation of ESM or enterprise service management. ESM is an enterprise-level organizational capability for delivering business value and outcomes by leveraging the enterprise’s resources (including technology) to produce and deliver products and services.
The fact is that, in addition to IT, there are several service providers within an organization, such as HR, Facilities, Finance, and other teams. The same capabilities AI enables with ITSM can also be applied to ESM.
For example, AI-enabled capabilities can help employees change benefits elections via self-service, request the setup of an office or workspace, request routine facilities requests (such as changing a light bulb), and enable automation of approval and payment of invoices. AI technologies can help organizations address knowledge management challenges by allowing the capture, management, and reuse of organizational knowledge.
By using AI capabilities across the enterprise, organizations can shift from a reactive to a proactive approach for delivering and supporting products and services.
Things to consider
While AI will open a world of capabilities for any organization, it is not a “magic wand”. There are a few issues that any organization must address before adopting AI.
- Data governance– Effective AI requires accurate, high-quality data. This is the top consideration for success with the use of AI-enabled technologies. An effective approach to data governance improves data quality, enhances an organization’s ability to comply with laws and regulations, and increases data security. And enables the effective use of AI capabilities.
- Digital strategy – Random and haphazard introductions of technologies, like AI, typically do not deliver the anticipated benefit for an organization. The first step for any use of digital technologies is to define the strategy for the use of digital technology. What does the business function want to achieve using digital technologies? How will digital technologies impact business models?
Get ready to use AI to improve ITSM
What must organizations do now to realize the benefits of introducing AI into their ITSM implementations?
- Learn more about AI – Many ITSM practitioners are unfamiliar with AI/ML technologies and lack the knowledge to effectively implement AI within ITSM environments.
- Audit existing practices for effectiveness and efficiency – Many organizations have not revisited their process designs since the initial implementation of the ITSM solution. Now is the time to review those processes to ensure effectiveness and efficiency so that the optimal benefit of AI can be achieved.
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