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The Transformative Role of
AI in IT Service Management

Oct 10, 2024  |  Reading Time: 8 minutes

It’s no surprise that the IT sector — an industry well-versed in adopting and understanding new technologies — is also facing disruption from the latest AI innovations. AI’s ability to automate processes such as information retrieval and accelerate search and response times has led 80% of company leaders to view Generative AI as a core lever for reinvention. So how can companies integrate AI in IT service management?

Keep reading to discover the three must-have use cases, the benefits teams can expect, and how to navigate potential challenges.

Understanding AI in IT Service Management

To understand the full potential of AI in IT service management, we must first understand the various terms and technologies associated with this topic.

  • AI Hallucination: A hallucination happens when a Large Language Model generates outputs that are inaccurate or that aren’t based on the input data. In other words, when AIs produce realistic, yet incorrect information. Engineers must look out for these mistakes to moderate the hallucination while using the model.
  • Generative AI (GenAI): GenAI refers to a category of AI that produces content including text, images, audio, or code, making it a valuable tool for many industries. It uses datasets to study patterns and then create similar data in response to prompts. Often, GenAI uses LLMs to understand and/or produce natural language. Examples of GenAI platforms include ChatGPT or DALL-E2.
  • Large Language Models (LLMs): LLMs are the result of algorithms trained on vast amounts of data. LLMs process data and produce outputs from a specific input which may ask it to recognize, summarize, translate, predict, or generate content using very large datasets.
  • Machine Learning (ML): This is a subtype of AI that consumes data and algorithms to build systems and enable AI to simulate how humans learn. By continuously learning, its goal is to improve the accuracy of its outputs.
  • Natural Language Processing (NLP): NLP is a computer program’s ability to understand human language. NLP is used as opposed to programming languages (java, C++, Python, etc.) which are not “natural”. This allows humans to successfully interact with computers using natural sentences.
  • Retrieval Augmented Generation (RAG): RAG is the process of enhancing the outputs of an LLM. This is done by allowing it to retrieve data from a separate knowledge base, such as a company’s internal content.

What is IT Service Management (ITSM)?

IT service management, or ITSM, refers to how IT teams manage their end-to-end delivery of IT services to users. This includes planning, creating, implementing, and delivering support to customers and employees. Unlike other IT management practices that focus primarily on technology, ITSM takes a process-driven approach and plays a critical role in ensuring the efficient operation and effective use of a company’s IT infrastructure.

ITMS is closely linked with frameworks like ITIL (Information Technology Infrastructure Library) and DevOps, which help streamline IT services and align operations with business strategies.

What is AI Service Management (AISM)?

AI service management, or AISM, is the application of AI in IT service management to enhance efficiency, automation, and decision-making. It is also known as AITSM.

AISM uses technologies like GenAI, ML, and NLP to detect and resolve IT problems quickly through contextually relevant, accurate customer service experiences. Typical examples of AISM are:

  • Intelligent Knowledge Management: AI facilitates efficient knowledge discovery with advanced enterprise search, streamlining access to critical information for IT teams.
  • AI-Enabled Customer Support: Chatbots and virtual agents deliver 24/7 customer support, resolving routine queries and technical issues autonomously.
  • AI-Powered Self-Service: AI-enhanced self-service platforms such as knowledge bases empower users to independently solve common technical issues, improving efficiency and reducing the burden on IT support teams.
  • Predictive Analytics: Leveraging AI, historical data can be analyzed to forecast potential system failures or service disruptions, enabling proactive maintenance and reducing downtime.

3 Use Cases of AI in ITSM

AI enhances and transforms IT service delivery to increase employee efficiency and improve user experiences. We recommend implementing AI in the following use cases.

AI for Enhanced Knowledge Management

AI is changing the game for knowledge management in ITSM by helping teams keep information organized and easy to find. Traditional knowledge management systems often struggle with outdated information, slow updates, and manual processes. As a result, companies have implemented knowledge bases, user portals, IT help desks, and in-product support to deliver enterprise knowledge across customer touchpoints.

By incorporating AI, these systems become more dynamic and accurate, enabling both IT staff and users to easily access the right information when they need it.

How Fluid Topics Improves Knowledge Management for ITSM

The Fluid Topics Content Delivery Platform (CDP) helps companies centralize all their information to make it easier for IT teams to manage and share technical content quickly and efficiently. As technology changes or new issues arise, updated content can be pushed to the dedicated channel (i.e. knowledge base) without any delays, ensuring that IT teams and end-users always have access to the most up-to-date information.

With its powerful features, IT departments can simplify support tasks, make better use of their knowledge across the team and enhance customer service.

AI Ticketing Solutions

With the rapid creation of new, increasingly complex technologies, it’s no surprise that IT service desk agents are overwhelmed with technical issues. Consequently, IT departments face a high volume of service tickets that need quick attention. New agents often spend significant time searching for solutions, which leads to longer resolution times, while experienced agents are burdened with answering the same

By embedding your IT help desk with AI-powered search technology, you can optimize the workload of both new and experienced agents. The algorithm analyzes user queries and suggests appropriate responses, leading to a reduction in the average response time for IT help desk tickets.

How Fluid Topics Boosts IT Incident Team Productivity

Fluid Topics’ Augmented Support Agent feature is a smart assistant that seamlessly integrates into any company’s IT helpdesk or incident management system. This AI agent tool connects to any centralized knowledge hub of documentation. Therefore, when new tickets arise, this digital IT assistant instantly creates clear, relevant answers to user questions.

To guarantee reliable answers, Fluid Topics ensures the IT service team can check and fine-tune these replies before sending them to the user. Our Augmented Support Agent provides links to the specific documents used to craft each answer. This improves transparency and security. As a result, IT service teams automate responses and cut ticket handling time by 50%.

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AI Virtual IT Assistants

AI support assistants are built to help employees or customers expedite access to information across operations. When users search for answers, not documents, virtual support assistants like chatbots are an ideal solution for modern companies. They provide consistent customer care without requiring additional time and effort from support teams.

These conversational AI tools are only becoming more popular and by 2026, AI assistants are projected to automate one in 10 support agent interactions. Gartner further highlights the benefits of this technology, stating it reduces customer handling time by up to 33% compared to interactions with human agents.

How Fluid Topics Creates the Ultimate Business Chatbot

Fluid Topics’ Question Answering feature combines RAG with our unified knowledge hub and advanced search engine. It adds a conversational question-and-answer layer to a company’s existing data. When users submit questions to the chatbot, they automatically receive accurate, product-specific responses.

Similarly to the Augmented Support Agent technology, the Question Answering application provides links to the documentation sources it uses for each output. This provides transparency and boosts both user learning and trust. As a result, users are empowered to resolve IT issues on their own.

General Benefits of AI in IT Services

By implementing AI tools into these three core IT service use cases, companies will enjoy several advantages.

Increased Efficiency

Bringing AI into ITSM boosts efficiency throughout the support workflow. For IT teams, access to an AI-augmented knowledge base provides new hires with valuable training material. Studies report that this cuts onboarding training by more than 50% and reduces escalations by 40%.

In parallel, users gain access to 24/7 IT support chatbots that can help several users at once, in any language. This Level 0 support allows IT services to run smoothly as businesses expand without putting excess pressure on the team. The result is a clear win for companies: reduced workloads, streamlined IT services, and accelerated problem resolution.

Personalized User Experiences

Providing personalized and contextualized information is central to IT support. By configuring content metadata and user profile settings, GenAI tools generate instant, relevant responses that fit the user’s profile, product, and situation. Additionally, ML algorithms can study user patterns and the rate of success to continuously refine content suggestions, ensuring they become increasingly tailored and effective over time. This continuous improvement helps the system adjust to changing user preferences, making it better at providing relevant and useful recommendations that enhance engagement.

Cost Savings and ROI

Companies can reduce costs thanks to AI-powered self-service options. When users solve their problems with AI-enabled self-service solutions, they don’t open incident tickets. Resolving problems autonomously is much cheaper than talking to live IT support, resulting in huge savings with every successful self-service interaction.

Another way to reduce costs is through ticket deflection. Provide IT recommendations right as users are starting to create a ticket. With relevant, AI-generated information, help them solve their issues and avoid submitting unnecessary incident tickets. This similarly reduces costs by fostering successful digital self-service interactions rather than requiring live IT support.

The Cost of Live Support vs Customer Self-Service

Additionally, 65% of support teams reported reduced tickets after investing in self-service. Less tickets means teams have more time to focus on the most complex IT challenges.

IT costs are also reduced because self-service options are available for users any time of day. Therefore, there’s no need to increase the number of agents on call 24/7 as business scales.

New Considerations of Using GenAI in IT Service Management

To benefit from AITSM, companies must address a few AI challenges and concerns that may arise.

Ethical and Privacy Concerns

To optimize IT service management with AI, teams must go beyond relying solely on LLMs. These models often lack up-to-date or company-specific product data. Without this core information, LLMs may generate hallucinations.

GenAI tools often function like black boxes, providing outputs without clearly explaining how they were derived. Yet, accuracy is key as incorrect IT information leads to technical incidents, longer downtimes, and the loss of customer loyalty. Misleading AI outputs weaken product knowledge, disrupt IT support, and complicate maintenance. A resourceful solution is using RAG to fine-tune the AI algorithm with your dependable, internal content. This ensures the algorithm produces accurate, contextual responses.

In any case, human validation is key. When IT service agents use AI, they should review and edit answers to prevent misinformation, ensure quality, and guarantee customer satisfaction.

Data Security

Security remains a top concern for AI, with 90% of security professionals stating companies need new techniques to mitigate risks. Businesses are most worried about AI sharing their private data with public LLMs, leading to information leaks. To prevent this, companies must ensure their AI solutions have two critical features.

  • Internal Embeddings Management: Choose solutions that internalize the embeddings computation and a vector database. Therefore, the AI model processes content internally, never leaking sensitive information.
  • Content Access Management: With customizable content access rights, control the information available in search results and AI-generated responses for different users. Therefore, unauthorized users cannot access restricted information.

Integration and Maintenance

AI in ITSM is ineffective if content isn’t accurate, accessible, and consistent across touchpoints. Users expect the same results whether they access information through chatbots or an enterprise search engine. However, new support touchpoints — documentation portals, help desks, FSM systems, community sites — each create information silos.

Adopting GenAI without addressing complex information flows will lead to inconsistent results. To prevent this, a Content Delivery Platform gathers and unifies content across sources. When a user submits requests information, the endpoint calls relevant content from the CDP, ensuring consistency.

For example, Fluid Topics’ AI-powered CDP offers an API-first architecture that enables unlimited integration capabilities with your existing systems, tools and sources.

Finally, with an average uptime of 99.9% and a user-friendly Admin UI for configuring and monitoring your platform, Fluid Topics makes access to technical documentation easy while reducing maintenance items for IT teams.

Conclusion

AI optimizes IT’s existing service management processes. Look for a Generative AI solution that enhances responsiveness and user personalization while providing a secure self-service environment. It should correspond to your incident management and enterprise knowledge needs. Solutions like Fluid Topics are ready-made to elevate your ITSM practices, learn more here.

About The Author

Kelly Dell

With a background rooted in digital marketing for B2B startups, Kelly strives to aid tech companies understand and connect with their customers through engaging, impactful content. Her expertise spans across content marketing, social media, SEO, and project management.