In the context of the IT Service Desk, support agents are involved in a variety of tasks. Some involve repetitive and predictable actions such as communicating known solutions to known problems to the requesting user. Other tasks involve careful interaction and analysis with users to identify the nature of the request and rout the ticket to the right resolution team. These complex support tasks also require the use of AI technologies for use cases such as analyzing historical ticketing archives and monitoring real-time log metrics. The resulting insights then empower the support staff to guide users and ticketing workflows to the right solution. Does it mean that AI and human support agents are in direct competition with each other?

Consider the history of technology evolution. During the early years of the Industrial Revolution, many feared that machines would replace the human workforce entirely. Industrial organizations saw a benefit in automating independent and individual components of manufacturing line processes performed by humans. The end-to-end process itself evolved, industries redesigned their manufacturing lines and the workflows became more complex to scale production exponentially through the use of automated machines. The manufacturing process itself became too complex and relied on human decision making to perform cognitive tasks at scale. This resulted in an influx of jobs that require technology skills and expertise – the role of automation improved over the decades in solving complex cognitive problems, but the demand for skilled workforce only increased ever since.

Now coming back to the routine tasks of an IT Support agent. Modern business services and products rely on complex technologies and data-driven operational workflows. The vision for the near future at least, in solving complex service requests and ensuring operational excellence, is not about replacing everything with robots. It’s about effectively solving challenging problems facing technology-driven services. Philosophically, the idea of viewing the competition between AI and humans cannot be seen as a zero-sum game – where only one winner can emerge at the expense of loss for the other party. This is because AI technology itself is evolving at a rapid scale and the role of human support staff is crucial in helping understand true user sentiment, preferences and issues, communicating it to business and technology decision makers, and ultimately, helping shape AI solutions that improve the service experience for end-users in return.

While one could argue that AI technology can be eventually designed to achieve these goals itself by some success, comprehending human interactions in terms of emotions, culture, behavioral and mental sensitivities, and intuition remains strictly within the domain of human capabilities. At least for now, machine intelligence can take the important role of augmenting this human capability and assist with complex data-driven tasks within a closed management system led by the support staff, engineering teams and key business decision makers.

Progressive ITSM organizations can take advantage of AI technologies by strategically investing in capabilities to complex cognitive tasks that require authentic intelligence. Technology companies generate and collect vast volumes of data in the form of log metrics, tickets and user interactions, system and application performance, market research and other avenues of information on users, business operations, markets and more. The next step for ITSM is to establish a mechanism that can embed intelligent automation across all aspects of ITSM at the process level: from NLP analysis of tickets to ticket routing; from incident detection and root cause analysis to proactive control actions. This can be seen as a hyperautomation intelligence approach that not only automates repetitive processes but also augments human decision makers with the right insights.