Artificial intelligence holds unmatched potential for solving IT service management challenges. Companies of all sizes are adopting AI tools as a cost-effective and efficient means of solving IT issues, from improving processes and increasing productivity to helping the organization reach its goals.
Although some fear that the expansion of AI in IT service management means the end of human-centered services, the fact is that AI offers problem-solving tools that can alleviate the burden on human experts and free up their time to focus on higher-value projects and more complex service needs. Understanding the potential and best ways to use AI-driven IT service management tools ensures an efficient and effective support environment.
Addressing Common Issues With AI in Service Management
Despite the increasing adoption of AI-driven configuration management tools, many companies struggle with IT service management. One prevalent issue is the lack of understanding within organizations of the root causes of process issues and failures. Instead of digging deeper into problems like skyrocketing spending to figure out what’s happening, many leaders are turning to AI solutions to solve the surface issues. In short, the excitement over AI leads many companies to view it as a “magic wand” that will solve all their issues.
Solving any problem requires first understanding its causes, though. That’s one area where AI can shine, and companies that leverage the power of predictive analytics can gain the critical insights they need to get to the heart of issues and find practical solutions. AI can extract insights, identify patterns and trends, and summarize events, giving IT teams a more accurate look at the organization’s challenges and where to prioritize solutions.
Other Ways AI Will Revolutionize IT Service Management
Clarifying the organization’s needs and streamlining a response isn’t the only role of AI in IT service management. The technology will also provide better incident prevention and response and help close the skills gap within the industry in the following ways:
- Proactive Incident Response: Predictive analytics and natural language processing (NLP) analyze unique organization data to identify patterns and metrics and compare them to real-time data, revealing the potential for events ahead of time.
- Automation: AI tools can handle routine tasks and simple issues so teams can focus on more pressing concerns. They can generate incident resolution and triage insights, either solving the problems automatically or creating reports for human review. Ultimately, this approach improves and targets automation efforts, saving the company time and money via faster, more focused corrective actions.
- Streamlined Configuration: AI-driven configuration management streamlines infrastructure provisioning and maintenance, freeing staff time for other priorities. It also simplifies configuration management by automatically predicting the impact of configuration changes and automating optimization.
The increased presence of AI in IT service management will not eliminate the need for human-centered support, but it will change how they work. There will be a reduced need for frontline analysts and customer support agents and an increased call for people with data science and engineering skills to help train and leverage AI tools to their greatest advantage.
Keeping up with these trends will be the key to success.
