Ivanti Originals

AI: The Future of ITSM Automation

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Ivanti’s research — a global study of over 3,000 IT professionals and 6,000 office workers — examined how AI can enhance ITSM automation and be a transformative tool to build organizational resilience. 

IT organizations are struggling with a complex set of obstacles that strain resources and impact service delivery and IT professionals are convinced of AI’s ability to improve productivity and efficiency. However, adoption of more complex IT automation use cases is still moderate to low. Just 42% of IT professionals say they use automation for predictive IT maintenance, and only 28% use AI-powered root cause analysis. 

Listen to “AI: The Future of ITSM Automation” to learn what’s on the horizon for AI across the entire IT organization and what breakthrough AI use cases should prioritize to reap the greatest long-term business value.  

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To read the report and access additional media, including presentation-ready slides and downloadable charts and graphs, visit ivanti.com/ 

For more Ivanti research on IT, security and the future of work, visit ivanti.com/research. 

About Ivanti 

Ivanti elevates and secures anytime, anywhere work so that people and organizations can thrive. We make technology work for people, not the other way around. Today’s employees use a wide range of corporate and personal devices to access IT applications and data over multiple networks to stay productive wherever and however they work. Ivanti is one of the only technology companies that finds, manages and protects each IT asset and endpoint in an organization. Over 40,000 customers, including 88 of the Fortune 100, have chosen Ivanti to help them deliver excellent digital employee experiences and improve IT and security team productivity and efficiency. At Ivanti, we strive to create an environment where all perspectives are heard, respected and valued, and we are committed to a more sustainable future for our customers, partners, employees and the planet. For more information, visit ivanti.com and follow @GoIvanti. 

AI and machine learning are reshaping IT service management (ITSM) by driving smarter operations and unprecedented efficiency. What’s next on the horizon for AI-Ops? 

You’re listening to the audio version of AI: The Future of ITSM Automation, part of Ivanti’s digital employee experience research series. To see more Ivanti research visit ivanti, I-V-A-N-T-I.com/research.  

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Part one: From efficiency to resilience 

AI is widely recognized as a transformative tool for efficiency gains, but more organizations should consider its key role in building resilience. 

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IT organizations are struggling with a complex set of obstacles that strain resources and impact service delivery: 

They struggle with operational bottlenecks: handling repetitive, time-consuming tasks and service delivery delays that reduce productivity and strain teams. (Managing repetitive tasks is the #1 cited challenge by IT professionals). 

They struggle with service expectations: adapting to evolving expectations for faster, more intuitive and always-available services. 

They struggle with tech complexity: navigating growing complexity and legacy systems that limit innovation and reduce organizational agility. 

And they struggle with evolving cybersecurity challenges: protecting IT services against advanced cyberattacks while maintaining service performance and ITSM compliance. 

Most IT professionals recognize AI's transformative potential to meet these challenges, viewing it as essential for modern, efficient ITSM. 

In fact, 65% predict AI and automation will improve overall IT service quality. And 86% say AI-powered technology is key to making IT organizations more efficient. These aren’t the only IT benefits organizations can derive from AI. 

Transitioning to AI-powered operations also improves IT resilience: the ability to keep critical systems running and to recover rapidly from disruptions (e.g., proactive problem detection, faster incident response and reduced downtime). 

AI empowers organizations to spot and fix problems before they become outages. The vast majority (85%) of IT professionals believe AI and automation solutions like root-cause analysis and predictive maintenance can help decrease IT ticket volume by identifying potential issues before they impact users, though just 28% of organizations use AI-powered root-cause analysis today. 

And beyond incident management, AI strengthens a company’s resilience by improving capacity planning. Using AI, companies can predict future resource needs, which allows them to scale infrastructure proactively rather than scramble to address performance bottlenecks after they occur. Currently, only 35% of organizations use AI to optimize resource utilization. 

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How can you take action? 

Here’s what Corinna Fulton, Ivanti’s Vice President of Solutions Marketing, has to say. 

“IT leaders who are looking to balance short-term efficiency gains with long-term strategic gains through the implementation of AI within their service management processes should be thinking about a couple key things. The first off is that it really is about thinking beyond incident management. AI can strengthen your overall resilience by improving capacity planning. This is something that not a lot of organizations are actually doing today.  

In fact, our survey showed that only 35% of respondents are using AI to look at resource allocation. That's really a strategic view. How is your company not going to only perform today? What are the efficiency gains you can make today? But what does that mean in terms of how you best use your resources in the future? And that's going to allow you to better scale your infrastructure and be proactive there rather than focusing only on scrambling to address your performance bottlenecks today.” 

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Part two: IT teams welcome AI's impact 

IT professionals are “all in” on AI as a positive, transformative power. However, companies need to prioritize training to reap the benefits. 

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IT professionals are convinced of AI’s positive, transformational power in the workplace.  

  • 84% use gen AI at work (28 points higher than non-IT professionals).  
  • 83% say workplace AI tools will improve their productivity in the next 12 months.  

And the perceived gains from AI are not just related to efficiency. IT professionals also believe AI will improve the quality of their work life.  

  • 67% predict AI will free up their time to do more interesting or fulfilling work.  
  • 70% say the growing use of AI and automation will increase their job satisfaction.  

Despite all the upside, organizations are not doing enough to equip their employees to use AI effectively and safely. Among those whose organizations allow gen AI tools, 60% say their companies have not yet provided training in how to use gen AI for work-related tasks.  

This gap between AI adoption and training represents a critical missed opportunity. While IT professionals are eager to embrace AI and are confident in its potential, the majority are left to figure out these powerful tools on their own.  

This training shortfall is particularly concerning given a worsening IT skills gap. Even while record numbers of students graduate from university with tech degrees in fields like computer science, the AI environment is changing so quickly that these skills are not keeping pace with industry demand. Consider: 

Ivanti's own research finds that one in three organizations (33%) cite skills gaps as a significant barrier to adopting IT automation. 

Skills gaps will become even more consequential as AI fundamentally reshapes what IT work looks like. As AI and automation take over routine tasks, IT professionals will increasingly move into more strategic roles that focus on AI oversight, complex problem-solving, and business alignment. The talent evolution is already underway: More than half (55%) of IT pros report that implementing AI and automation has created entirely new roles and specializations within their organizations.  

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How can you take action? 

Here’s what Sterling Parker, Ivanti’s Senior Vice President of Global Technical Support, has to say: 

“The first thing that a leader needs to be doing when considering implementing any kind of AI strategy within their business and with the focus of work-life balance is identifying which tasks today need to be automated or can be automated versus those tasks that are enriching your team's ability at the end of the day. And so you've got to start by mapping out which workflows exist that help you distinguish between that repetitive, low value, low effort type of work. Versus those efforts that require creativity, that require problem solving and collaboration with your team, tasks and enrichment activities that your team benefit from. 

And then you have to really make sure that your time is creating and cultivating this mindset of just continuous learning. So, you've gotta entertain and organize those feedback sessions, and then provide coaching and support where you feel that it's necessary, just so you get that right adoption. And that then you continue to measure and reiterate and make changes as you need to make it so that the team is successful at the end of the day when they're adopting AI.” 

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Part three: Breaking down AI adoption barriers 

Despite proven use cases for AI and automation in IT-Ops, uptake of new methods and tools remains uneven. 

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Ivanti’s research reveals that while IT professionals are using AI for individual tasks, most organizations are still working to harness its full potential for transforming workflows. For instance: 

  • 67% of IT teams have automated ticket routing. 
  • 60% use automation for identity and access management. 
  • 58% have automated password resets. 

 However, adoption of more complex IT automation use cases is still moderate to low. Just 42% of IT professionals say they use automation for predictive IT maintenance, and only 28% use AI-powered root cause analysis. 

Companies so far have been cautious about embracing AI in IT-Ops environments — despite overwhelming enthusiasm among IT professionals — due to a combination of operational, technical and strategic barriers: 

AI depends on high-quality, well-structured data. Most IT organizations still struggle with fragmented or incomplete datasets, legacy systems that are hard to integrate and knowledge bases that are not consistently updated. 89% contend that siloed data negatively impacts their organization's IT operations. 

Integration with existing systems is costly and complex. Most companies still depend on legacy infrastructure that will require substantial investments to make AI-ready. More than 1 in 3 IT professionals (38%) cite tech complexity as among their organization’s biggest barriers to effective IT operations. 

Security and privacy risks are also top concerns. Deploying AI often means processing sensitive organizational data, triggering anxiety about vulnerabilities and data exposure. 42% of IT professionals cite security and compliance concerns when asked about barriers to IT automation; it’s the #1 cited challenge. 

AI projects require significant upfront investment. Leaders face pressure to demonstrate clear returns amidst uncertain benefits, especially when deploying more sophisticated use cases beyond basic automation. Add to that, building consensus for these types of deployments is a slow process, particularly in large organizations. 

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How can you take action? 

Here’s what Scott Hughes, Ivanti’s Senior Vice President of Revenue Operations and Corporate IT, has to say: 

“Most companies still have legacy infrastructure that is not designed for AI capabilities and can require substantial investments to upgrade or connect to. In fact, 30% of organizations cite technology complexity as among their organization's biggest barriers to effective IT operations. It should also be said, technical debt understanding is not a construct that should be exclusively held by the IT teams. It is critical for any IT organization to ensure that the business is also fully aligned with its infrastructures technical debt, as well as mapping any process and data gaps that exist throughout that infrastructure.  

Alignment between IT and the rest of the enterprise related to these gaps is therefore necessary as it will surface many challenges those LLMs may encounter up front. Then therefore setting the stage then for better rationalization of the P&L expectations or goals from that AI during the decision making process. Once aligned, then it is a matter of assessing built by partner techniques to best serve those decisions and goals, factoring IT and business resource capability constraints, time and cost, as well as overall employee maturity related to AI.” 

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Part four: What’s next for AI in IT? 

AI is already delivering predictive insights and streamlining ITSM workflows. The breakthrough use cases are yet to come. 

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What’s next on the horizon? Deploying AI across the IT organization, both to replace routine tasks and to drive more sophisticated, future-looking applications. 

Today, AI is already handling many of the routine tasks that consume IT teams' time. 

One example is routine IT automation: Analysts estimate the average cost to resolve an IT ticket ranges from $15 to $17, and multiples higher for escalated requests. HDI research finds that companies are using AIs to resolve high-volume requests like password resets or system restarts in seconds, shaving millions off annual service costs in large enterprises. Currently, 58% of organizations use AI for password resets, and 52% use it for employee onboarding. 

Another example is self-service AIs: Deploying intelligent chatbots and virtual agents within ITSM platforms allows employees to resolve common IT issues themselves, accelerating support and freeing up IT professionals for higher-value tasks. Office workers increasingly prefer this route. 36% say they would choose an automation or chatbot to solve their IT problems — up five points in one year. Here, AI ITSM is a win-win, empowering employees to manage their technology the way they prefer to. 

A third example is proactive monitoring and self-healing: AI systems continuously monitor infrastructure, predict failures and automatically remediate issues without human intervention, translating to higher uptime, improved business continuity and a better employee experience. 

The next phase will see AI agents working together on complex, multi-step processes. 

For example, agentic automation: Autonomous, collaborative AI agents will take on complex workflows — from cybersecurity incident response to software deployment — working together with minimal human oversight to resolve incidents, provision resources and ensure compliance. 

Another example is end-to-end lifecycle management: AI agents will not only fix issues but also detect, diagnose and optimize IT systems from provisioning to retirement. 

Another example is sustainability algorithms: AI will optimize IT workloads for minimal energy use and hardware waste, automatically balancing workloads for maximum environmental and business benefit. 82% of IT professionals say sustainability and energy efficiency is important to their company leadership, but just 24% say their IT organization is “highly sustainable.” 

And a final example is resource monitoring: AI-driven monitoring helps CIOs spot over-provisioned cloud environments, underused licenses and redundant applications — issues that drain budgets. 

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How can you take action? 

Here’s what Sterling Parker, Ivanti’s Senior Vice President of Global Technical Support, has to say. 

“What strategies can organizations implement to ensure AI innovation leads to positive outcomes for both business performance and employee growth? I see this as you have to co-create your AI vision roadmap with stakeholders within the business. And this requires collaborative planning. You have to involve your employees, your managers, your business leaders when setting your AI priorities. Here at Ivanti, we have an AI intake committee. We also have an AI governance committee. We have ways that we force these silos to be broken down so that we're co-creating together and not creating this AI sprawl in other parts of the business..

That's why it's so important that you're combined as an entire organization around the AI vision roadmap and that you're clearly defining what that looks like. You have to make sure you're designing these AI solutions that are human-centric so that it's focused on the augmentation of the role and not the replacement of the role.” 

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You can read the report and see the rest of Ivanti’s research at ivanti, I-V-A-N-T-I.com/research. 

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