The disruptive potential of AI in ITSM offers much more than simply automating the service desk for efficiency gains. The true power of AI lies in its ability to orchestrate an intelligent ecosystem, coexisting with human expertise, to transform user experience and build organizational resilience. Shift your service desk vision from AI-driven to AI-orchestrated with a step-by-step framework that will help you identify and implement AI use cases to transform your service desk.

AI’s unlimited potential is driving organizational demand for a more effective service desk to not only reduce tickets but also power seamless service delivery and predictive solutions. However, many obstacles stand in the way, from legacy systems and skills gaps to transparency concerns and the need for stakeholder buy-in. Overcome these barriers to help IT align AI initiatives with organizational priorities and governance best practices and enable a paradigm shift in your service desk.

1. Reduce incoming tickets to improve outgoing support.

Gear your AI goals toward ticket reduction rather than faster ticket handling. AI must be implemented on the foundation of a proactive IT ecosystem, where issues are predicted and resolved before they impact end users. Ticket reduction will create an opportunity for agents to work on higher-value tasks, providing more impactful results to the organization.

2. Build AI synchronicity with the ITSM ecosystem.

Align AI capabilities with your service desk workflows and operational governance framework. Deploying AI as a standalone tool will increase complexities instead of streamlining processes, wasting your investment and its potential.

3. Stay focused on the big picture, even as it changes.

AI implementation is never a one-time project – it’s a continual task that needs to be updated and governed to ensure it provides intelligent assistance. Adapt and evolve your initiatives to continuously transform your service management and stay ahead of end user expectations.

Use our comprehensive blueprint to identify and implement effective AI-based use cases for your service desk

This research will help you to explore how to transform your service desk with AI. Use this step-by-step framework, featuring practical tools and templates, to:

Assess your objectives for adopting AI for the service desk.
Implement AI use cases that will help you to transform your service desk practice.
Continuously drive improvements with AI, extend its capabilities to other areas of IT support, and remain agile in a rapidly evolving IT landscape.

Implement an AI-Orchestrated Service Desk Research & Tools

1. Implement an AI-Orchestrated Service Desk Storyboard – A comprehensive guide to making your service desk proactive and predictive using AI.

In this research, we will help you to:

Assess your goals for AI implementation, evaluate your readiness, and discover opportunities for AI use cases.
Define AI solution requirements, identify implementation risks, conduct solution planning, and design a proof-of-concept framework.
Continuously optimize your automation impacts with stakeholder adoption planning and quality data.

2. Service Desk AI Use Case Delivery Report Template – A boardroom-ready template to centrally store and communicate key information on your AI implementation plans.

Use this template to:

Document your service desk AI use case implementation strategy.
Record each step you take through use case selection, refinement, and implementation.
Gain understanding and buy-in from key stakeholders across your organization.

3. Service Desk AI Use Case Discovery Tool– A detailed Excel-based tool to help you identify the right AI use cases to explore for your service desk.

This tool allows you to:

Assess service and operational impacts across five service desk capability dimensions.
Understand which service desk capabilities require the most attention at your organization.
Identify problem statements that align to your service desk pain points or high impact opportunity areas.
Select the right AI use cases to take through value and readiness rationalization.

4. Service Desk AI Use Case Prioritization Matrix– A step-by-step evaluation matrix tool to help you track and analyze potential AI pilot use cases.

This robust tool helps you to:

Capture, track, and shortlist submitted ideas for potential pilot projects.
Assess the value and readiness of use cases in your shortlist with a customizable scoring scale.
Create a highly visual chart to communicate your priority initiatives to key stakeholders at a glance.

Implement an AI-Orchestrated Service Desk

Build a strategic approach to drive automation and efficiency.

Implement an AI-Orchestrated Service Desk

Build a strategic approach to drive automation and efficiency.

EXECUTIVE BRIEF

Analyst perspective

Unleash the power of AI to enable a paradigm shift in your service desk.

Artificial intelligence in IT service management is usually considered an automation engine that helps gain efficiency. Although these benefits have been tangible and significantly helped IT teams, they don’t capture the full disruptive potential of AI in service management. Despite the promising impacts of AI, the service desk may have multiple challenges with implementation, such as data fragmentation, agent concerns, and AI governance. Addressing these concerns can help ensure IT teams align their AI initiatives with organizational priorities and governance best practices.

Although AI can help the service desk reduce costs through staff optimization and a decrease in ticket volume, this perspective is short-sighted. The true power of AI in the service desk lies in building organizational resilience and transforming the user experience, positioning ITSM beyond saving costs.

This research is designed to help you identify AI-based use cases and create an implementation plan to use AI capabilities effectively.

Photo of Mahmoud Ramin, Senior Research Analyst, AI Research, Info-Tech Research Group.

Mahmoud Ramin
Senior Research Analyst, AI Research
Info-Tech Research Group

Executive summary

Your Challenge

Given the various potential uses of AI, organizations are demanding a more effective service desk to not only reduce tickets but also drive seamless service delivery and predictive solutions. However, they face the following challenges to drive such capabilities:

Lack of a clear AI governance and implementation framework leads to concerns about risks following implementation.
Service desk is already firefighting due to current issues, making AI adoption challenging.
IT does not have a clear understanding about AI use cases for the service desk.

Common Obstacles

AI is hailed as a transformative solution, but many organizations struggle to use its capabilities due to the following obstacles:

ITSM environments are fragmented and outdated, resulting in low data quality and integration issues.
Organizations are concerned about AI hallucination and inaccurate responses.
AI requires significant investment, training, and infrastructure updates, which are a financial burden.
Service desk has difficulty getting leadership and other stakeholder buy-in for AI use cases due to lack transparency and job security concerns.

Info-Tech’s Approach

This research will help you:

Assess your objectives for adopting AI for the service desk.
Implement AI use cases that will help you transform your service desk practice.
Continuously drive improvements with AI, extend its capabilities to other areas of IT support, and stay agile in a rapidly evolving IT landscape.

At the end of this research, you will walk away with a delivery report that will help you communicate your AI implementation plan for the service desk and your strategy to get ready for other AI-powered use cases.

The future of the service desk is AI-orchestrated instead of AI-driven

AI’s biggest impact on the service desk goes beyond process automation. AI will transform the service desk by orchestrating an intelligent ecosystem, coexisting with human expertise.

Common barriers to AI-enabled transformation

AI implementation presents several common challenges that organizations should navigate.

57% — Lack of Skills

57% of organizations believe they have a shortage of internal expertise to implement AI solutions. (ITSM.tools, 2023)

43% — Legacy Systems

43% of organizations have challenges with outdated and legacy applications, making AI adoption difficult. (ITSM.tools, 2023)

62% — Employee Resistance

62% of managers have reported that their employees are concerned that AI will replace their jobs. (The HR Director, 2024)

55% — Data Security Concerns

55% of data leaders are concerned about exposure of sensitive data by large language models (LLMs). (Immuta, 2024)

Key business challenges of implementing AI for the service desk

High Costs
AI deployment requires significant upfront and maintenance investments.
Integration Challenges
Data synchronization is pivotal to ensure ML algorithms are accurate, making it complex for teams using legacy systems.
Security Concerns
Data privacy is a big concern, especially for those organizations processing highly confidential data.
Lack of Human Touch
Despite its huge capabilities, AI may struggle with handling complex issues that require human judgment.
Trust Issues
Service desk agents may fear job displacement due to AI automation, leading to their resistance.
Transparency Concerns
AI can potentially act like a “black box,” leading to concerns about lack of process understanding.
Scalability Challenges
Scaling AI to drive continuous improvement and customizing use cases to specific organizational requirements can be difficult.
ROI Measurement Difficulties
It is challenging to demonstrate a clear return on AI investment for the service desk, making it difficult to get leadership buy-in.

AI maturity journey for the service desk: From manual to autonomous

Foundational

Limited or no use case for AI
Manual processes
Reactive service desk

Intermediate

Early integration of AI tools into specific processes
Recurring incidents and requests identified by AI

Advanced

AI used for major service desk processes
Incident and request prediction
Conversational AI

Optimized

Autonomous service desk processes
Complex troubleshooting
Cross-departmental process optimization

Integration of voice AI with a ticketing system to enhance service desk efficiency

INDUSTRY: Customer experience | SOURCE: Retell AI

Everise implemented a voice AI tool to tackle ticket overload and save time.

Challenge

Everise is a global customer experience solutions provider with over 20,000 employees worldwide. The company had an internal challenge with high call request volumes, resulting in long wait times of 5-6 minutes.

The call volume and waiting time increased operational costs and resulted in decreased employee satisfaction. The service desk had been relying on a complex interactive voice response (IVR) system, which was identified as the main root cause of the challenge.

Solution

Everise integrated a voice AI technology, Retell AI, into their service desk operations. This solution had the capability to:

Seamlessly integrate with internal systems to identify and authenticate users.
Understand the requester’s content through natural language processing (NLP).
Integrate with Everise’s ITSM platform to help with ticket creation and modification.
Handle multiple languages to enable Everise’s global workforce.

Results

Retell AI deployment helped Everise to:

Contain 65% of voice tickets that used to require live agent intervention, resulting in a significant reduction of the human agent workload.
Save about 600 work hours per month, which helped agents focus on more complex tasks.
Decrease call wait times by 100%, leading to employee satisfaction and productivity.

Info-Tech’s methodology for implementing AI in the service desk

	1. Assess Goals and Current State	2. Outline Solution Requirements	3. Develop a Continuous Improvement Strategy
Phase Steps	Define goals Discover opportunities	Define AI solution requirements Identify implementation risks Conduct solution planning and a proof of concept (POC)	Optimize automation impacts through stakeholder adoption planning Optimize automation with quality data
Phase Outcomes	Alignment of AI objectives with business strategy Current service desk pain points for adopting AI Prioritized AI use cases for service desk	Guidelines for AI use in service desk processes AI solution requirements (data requirements, process integrations, potential risks, and risk mitigation strategy)	AI performance monitoring metrics Stakeholder engagement plan Continuous AI training and governance strategy

Insight summary

The future of the service desk is AI-orchestrated instead of AI-driven

AI’s biggest impact on the service desk is beyond process automation. AI will transform the service desk by orchestrating an intelligent ecosystem, coexisting with human expertise.

Reinvent the service desk with AI

The true power of AI in the service desk is making it proactive and predictive, resulting in eliminating the need for tickets. In the meantime, it creates a big opportunity for service desk agents to evolve their roles into something more strategic, creating higher values.

Synchronize AI with your ITSM platform

Align AI capabilities with service desk workflows and your operational governance framework. If you deploy AI as a standalone tool, your investment and its potential will be wasted, increasing complexities instead of streamlining processes.

Go beyond AI deployment

AI implementation is not a one-time project. It’s a continual task that needs to be updated and governed to ensure it provides intelligent assistance. Make sure to adapt and evolve your initiatives to continuously transform your service management and stay ahead of end user expectations.

Pivot your goals from automation to ticket reduction

The goal of AI deployment in the service desk should be ticket reduction rather than faster ticket handling. AI should be used to create proactive IT ecosystem where IT issues are predicted and resolved before they impact end users.

An AI platform is as smart as the data used for its training

Instead of rushing into AI implementation for the service desk, consider a solid data quality, governance, and integration to convert your service desk platform into a smart engine. Use historical ticket data, behavioral patterns, and system telemetry to drive proactive support.

Blueprint deliverables

Key deliverable

Service Desk AI Use Case Delivery Report Template

Document your service desk AI use case implementation strategy and the steps you take through the use case selection, refinement, and implementation process in this boardroom-ready template.

Sample of the Service Desk AI Use Case Delivery Report Template deliverable.

Follow the blueprint steps to conduct a thorough assessment of automation use cases and initiatives using the IT Operations Automation Workbook:

Service Desk AI Use Case Discovery Tool

Use this tool to guide your service desk AI use case selection process.

Sample of the Service Desk AI Use Case Discovery Tool deliverable.

Service Desk AI Use Case Prioritization Matrix

Use this tool to produce a shortlist of service desk AI use cases.

Sample of the Service Desk AI Use Case Prioritization Matrix deliverable.

Blueprint benefits

IT Benefits

Automating routine processes improves IT productivity and efficiency and allows teams to focus on higher-value tasks.
AI helps decrease IT workload and optimize resource use through AI-human collaboration, resulting in efficiency improvement and cost saving.
Real-time analytics allow IT managers to optimize processes and initiatives based on data-driven insights.
Prioritizing the right AI use cases helps IT make a strong case to get approval from the business.

Organization Benefits

AI-driven ticket reduction helps the business improve service costs and financial efficiency.
AI-enabled automation provides faster and more efficient IT support, minimizing business disruptions and improving end user satisfaction.
AI-powered ITSM improves business transformation, making the business ready to transition into a modern and responsive service provider.
Focused AI initiatives for ITSM improve IT alignment with business objectives and technology investments.

Quantify your strategic approach

Use the following metrics throughout this process to track the impact of AI on improving the service desk and driving measurable outcomes:

Ticket Volume: Used to analyze the total volume of tickets created in a defined period, calculated to showcase the impact of proactive issue prevention.
Agent Use Rate: Calculated by measuring the percentage of time that service desk agents spend on IT support tasks as opposed to their available time.
Cost Per Ticket: Average cost of ticket resolution, which will be essential to analyze the ROI of AI implementation in the service desk.
Customer Satisfaction: This measurement of end user satisfaction is collected through surveys to demonstrate the service desk’s timeliness and effectiveness.

Organizations that have adopted AI have reported positive impacts on support and processes.

75% — Implementation of generative AI at the service desk leads to a 75% reduction of resolution times (Rezolve.ai, 2024).
15% — AI-powered conversational assistants increase productivity by 15% (arXiv, 2023).
35% — AI implementation leads to a 35% reduction of customer support costs (Plivo, 2024).

Info-Tech offers various levels of support to best suit your needs

DIY Toolkit	Guided Implementation	Workshop	Executive & Technical Counseling	Consulting
“Our team has already made this critical project a priority, and we have the time and capability, but some guidance along the way would be helpful.”	“Our team knows that we need to fix a process, but we need assistance to determine where to focus. Some check-ins along the way would help keep us on track.”	“We need to hit the ground running and get this project kicked off immediately. Our team has the ability to take this over once we get a framework and strategy in place.”	“Our team and processes are maturing; however, to expedite the journey we'll need a seasoned practitioner to coach and validate approaches, deliverables, and opportunities.”	“Our team does not have the time or the knowledge to take this project on. We need assistance through the entirety of this project.”
Diagnostics and consistent frameworks are used throughout all five options.

Guided Implementation

A Guided Implementation (GI) is a series of calls with an Info-Tech analyst to help implement our best practices in your organization.

A typical GI is between 5 to 8 calls over the course of 3 to 4 months.

What does a typical GI on this topic look like?

Phase 1

Phase 2

Phase 3

Call #1: Determine goals and uncover pain points.

Call #2: Define the top AI-driven problem statements and identify the top use cases.

Call #3: Prioritize use cases.

Call #4: Identify technical, data, and operational requirements.

Call #5: Discover AI adoption risks and plan a mitigation strategy.

Call #6: Create a list of deployment plans and expected milestones.

Call #7: Determine key metrics and KPIs for performance monitoring.

Call #8: Build a communication plan and establish a feedback loop.

Workshop overview

Contact your account representative for more information.
workshops@infotech.com 1-888-670-8889

	Day 1	Day 2	Day 3	Day 4	Day 5
	Assess Goals, Gaps, and AI Use cases	Prioritize Use Cases and Define Requirements	Create a Solution Deployment Plan and a Change Management Strategy	Enable Continuous Improvement and Efficient Monitoring	Next Steps and Wrap-Up (offsite)
Activities	1.1 Define actionable goals for implementing AI in the service desk. 1.2 Define your service desk problem statement. 1.3 Establish your solution objectives. 1.4 Prioritize your service desk capability focus. 1.5 Use mapping tables to align potential use cases.	2.1 Quantify the value and readiness of each use case. 2.2 Narrow use cases from the longlist down to a shortlist. 2.3 Define user requirements. 2.4 Define data requirements. 2.5 Define governance, risk, and compliance considerations.	3.1 Define your POC framework. 3.2 Establish your testing framework. 3.3 Establish a structured deployment plan. 3.4 Plan a structured change management strategy. 3.5 Design a training plan for identified use cases. 3.6 Design a communication plan for the identified use cases.	4.1 Develop an impactful business case for service desk AI use cases. 4.2 Establish your monitoring framework. 4.3 Design a framework to continuously drive innovation in the service desk.	5.1 Complete in-progress deliverables from the previous four days. 5.2 Set up review time for workshop deliverables and to discuss next steps.
Deliverables	Service desk AI goals Service desk gaps AI solution objectives Service desk capability priorities Longlist of use cases	Use case value and readiness Prioritized use cases Use case user requirements Use case data requirements Use case governance, risk, and compliance strategy	POC framework Testing framework Deployment plan Change management strategy Training plan Communication plan	Service desk AI business case Monitoring framework Continuous improvement framework	Completed service desk AI delivery report

Workshop Prerequisites:

Organization’s vision and mission statements/goals for adopting automation or AI.
Service desk’s current state (e.g. end user sentiments, satisfaction scores, diagnostic results).

Implement an AI-Orchestrated Service Desk

Phase 1

Assess Goals and Current State

Phase 1

Phase 2

Phase 3

1.1. Define goals

1.2. Discover opportunities

2.1. Define AI solution requirements

2.2. Identify implementation risks

2.3. Conduct solution planning and a POC

3.1. Optimize automation impacts through stakeholder adoption planning

3.2. Optimize automation with quality data

Phase 1 will walk you through the following activities:

Identify business objectives associated with adopting AI in the service desk.
Discover the overarching problems that AI will tackle.
Identify the top service desk AI use cases.

Phase 1 involves the following participants:

IT leader
IT operations manager
Service desk manager

Step 1.1

Define goals

Activities

1.1.1 Define actionable goals for implementing AI in the service desk.
1.1.2 Define your service desk problem statement.
1.1.3 Establish your solution objectives.

Outcomes of this step:

Alignment of organizational goals with AI adoption in the service desk
Service desk problem statement that AI can help alleviate

Assess Goals and Current State

Step 1.1 › Step 1.2

Structure your AI adoption plan with a focus on business value

Not every task that can be automated should be automated.
Automation can require a large investment.
Use a defensible, consistent method to demonstrate the value of the automation you intend to implement.

Why should you define automation goals?

AI must drive clear and measurable values.
Automation goals should be aligned with organizational objectives to ensure service desk innovation initiatives meet business requirements.
Without clear objectives, AI may lead to inefficiencies, resource loss, and missed opportunities.

“Understanding business needs is a big challenge that organizations may face in aligning AI with business objectives. Goals should be to support the business as best and efficiently as we can and to be supportive of the business cases and business objectives moving forward. It's not all rainbows and unicorns. There are some things we need to be aware of to avoid constraining our approach. We should assess the situation from multiple levels.” (John Lucero, IT Security Manager, City of Santa Fe)

Build a strategic approach to drive automation and efficiency.

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

Table of Contents

Implement an AI-Orchestrated Service Desk Storyboard
Service Desk AI Use Case Delivery Report Template
Service Desk AI Use Case Discovery Tool
Service Desk AI Use Case Prioritization Matrix

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Guided Implementation 1: Assess Goals and Current State

Call 1: Determine goals and uncover pain points.
Call 2: Define the top AI-driven problem statements and identify the top use cases.
Call 3: Prioritize use cases.