5 ways AI can be used to improve ITSM workflows and efficiency
How AI and automation improve ITSM efficiency
AI is reshaping IT service management (ITSM) by automating routine tasks, accelerating resolution times, and giving teams the insights they need to work proactively instead of reactively.
New research by Freshworks shows that as businesses scale their IT environments become increasingly more complex, which has a significant impact on both employee productivity and overall operational efficiency. In fact, organizational complexity now accounts for 7% of total annual revenue loss for an average business. That’s about the same size as a typical R&D budget, effectively erasing innovation investment and slowing the pace of progress.
AI-powered ITSM workflows help solve this issue by giving service teams the tools they need to manage higher volumes, reduce manual effort, and deliver more consistent service experiences. The result is a more efficient service desk and improved operational performance across the business.
What AI does in modern ITSM
AI brings structure, speed, and intelligence to the core operations of ITSM. Modern platforms use machine learning and natural language processing to accomplish a range of complex tasks, including:
Understanding the intent of incoming requests
Classifying and prioritizing tickets automatically
Routing issues to the right team based on context
Recommending knowledge or next steps to agents
Detecting patterns and predicting service disruptions
Instead of relying solely on manual triage or human analysis, teams using AI-powered solutions gain scalable automation that strengthens accuracy, ensures repeatability, and shortens response and resolution time. AI also bridges the gap between self-service, operations, and support by making ITSM systems more intelligent, more intuitive, and easier for employees to navigate.
How can AI streamline ITSM workflows?
AI reduces manual work across every stage of the ITSM process, from ticket intake to resolution and documentation. These improvements help service teams focus on higher-value tasks without getting slowed down by repetitive operational steps. Below are five ways AI can be used to streamline ITSM workflows:
Automated ticket classification and routing: AI models can analyze written requests, identify their underlying intent, and instantly categorize them. This removes the need for manual triage and ensures issues reach the correct team without delay. It also improves SLA adherence by prioritizing high-urgency issues earlier.
End-to-end workflow automation: AI-powered workflows trigger actions based on specific conditions. A great example is escalating an overdue ticket or gathering missing information automatically. This eliminates bottlenecks and reduces the risk of human error.
Intelligent self-service: Conversational AI and virtual agents handle common IT tasks, such as password resets, access requests, and device troubleshooting, without requiring human involvement. This reduces ticket volume and gives employees faster resolution pathways.
AI-driven knowledge recommendations: AI identifies relevant knowledge articles based on ticket content, helping agents solve issues quickly and improving self-service search accuracy.
Analytics for operational visibility: AI surfaces trends, recurring issues, and workload patterns. IT leaders gain a clearer view of service performance and where workflow improvements are needed.
Generative AI and the future of ITSM efficiency
Generative AI (gen AI) introduces a new layer of acceleration across ITSM. Where traditional AI automates classification and routing, generative models automate knowledge work and communication. This enhances operations through powerful new capabilities, such as:
Automatically drafting responses to incidents, emails, updates, and chat queries
Summarizing ticket histories, incident timelines, and troubleshooting steps
Creating knowledge articles from resolved tickets
Improving documentation quality by rewriting or updating outdated content
Enabling conversational self-service for more complex employee questions
This allows service teams to work faster while maintaining clarity, consistency, and accuracy across all touchpoints.
What are the main business outcomes of AI-enhanced ITSM operations?
AI doesn’t just streamline workflows; it drives measurable improvements in operational performance, including:
Reduced MTTR (mean time to resolution): Automated routing, knowledge recommendations, and predictive insights shorten the time required to diagnose and resolve issues.
Higher SLA compliance: Faster triage and more accurate prioritization ensure teams meet service expectations more reliably.
Increased productivity across IT Teams: Agents spend less time on manual tasks and more time solving meaningful problems.
More scalable support operations: AI enables teams to support growing user populations without proportional increases in staffing.
Improved employee experience: Faster resolutions and stronger self-service options reduce frustration and keep employees productive.
A well-implemented AI strategy benefits the entire organization, from the service desk through to leadership teams.
How to get started with AI-powered ITSM
Businesses can introduce AI gradually by focusing on the workflows with the biggest impact. Below are six simple steps to get new initiatives up and running:
Automate high-volume request types: Password resets, access provisioning, VPN help, and software installation are ideal starting points for any new initiative.
Enable AI-driven classification and routing: This delivers immediate improvements in consistency and response time.
Deploy agent assist tools: Features like suggested replies and summaries provide fast productivity gains without process disruption.
Use generative AI to build or improve your knowledge base: AI can convert resolved tickets into new articles or refine outdated content.
Introduce conversational AI for scalable self-service: Virtual agents can be used to offload a significant percentage of repetitive requests, freeing up agents.
Adopt AI gradually, with governance: Platforms offering no-code configuration, such as Freshservice=, help teams implement AI safely, with transparency and control.
Summary
AI is quickly becoming an essential part of modern ITSM. Automating repetitive work, accelerating resolutions, and improving access to knowledge help service teams operate with greater speed, accuracy, and efficiency. As organizations grow and IT environments become more distributed, AI-powered ITSM lets teams scale service delivery without increasing complexity. With the right approach, IT teams can shift from reactive support to proactive, high-performing operations that deliver better outcomes for employees and the business.
FAQ
Q: How does AI reduce incident resolution times?
A: AI speeds up resolution by automatically categorizing and routing tickets, suggesting fixes based on historical data, and triggering automated remediation actions when appropriate. Virtual agents also handle many issues instantly, reducing the load on human teams and shortening overall turnaround times.
Q: Can AI be integrated with platforms like Freshservice?
A: Yes. Modern ITSM platforms like Freshservice already include native AI capabilities and support integrations through APIs and connectors. This allows organizations to enhance existing workflows without major process changes or disruptions.
Q: What data is required for AI to be effective in ITSM?
A: AI performs best when it has access to clean, consistent data such as historical tickets, CMDB records, change logs, service maps, and knowledge articles. High-quality data enables accurate predictions and reliable recommendations.
Q: What challenges should organizations expect when applying AI to ITSM?
A: Common challenges include poor data quality, user distrust of AI recommendations, integration issues with older systems, and the need to protect sensitive operational data. These obstacles are typically manageable by starting small and keeping humans in the loop.
