Let’s talk about AI adoption in ITSM. In a recent webinar with SymphonyAI, I spoke about what our data is showing us regarding the current state of artificial intelligence (AI) adoption in IT service management (ITSM). This article shares some of the discussed points across IT support and service delivery.
In a recent webinar with @SymphonySummit, @StephenMann looked at what @ITSM_tools data is showing us regarding the current state of #AI adoption in #ITSM. This article shares some of the discussed points. Share on XThe changing face of AI interest and adoption in ITSM
The ITSM industry was first talking about AI adoption close to a decade ago. I participated in a Service Desk and IT Support Show (SITS) AI panel in 2017 (although I remembered it as 2016).
This was when ITSM professionals started to want to know more about what AI would mean to their roles and work. This was also reflected in the annual ITSM.tools ITSM content poll for 2018, with AI as the second-most requested content area (after ITIL).
But this was simply a sign of the initial interest in what was seen as a new technology (and potentially a “job killer”). AI adoption interest then dropped in 2019 before appearing in second place in 2020 and 2021. Interest dropped again for 2022 and 2023 before AI vaulted to the top spot in 2024 as more organizations started to use AI “in anger.”
There’s already a significant number of organizations using AI in ITSM, with our recent well-being in ITSM survey finding that 36% of respondents used corporate AI capabilities, and 66% used free AI tools such as ChatGPT. This is against a backdrop of three-quarters of ITSM tools having already added some form of AI capabilities (taken from our 2023 AI adoption in ITSM survey).
Finally, if AI adoption follows the adoption patterns we’ve found with enterprise service management and experience management, we won’t see the traditional trickle-down effect for ITSM trend adoption from the largest through mid-sized to smaller organizations. Instead, large enterprises and SMBs or SMEs will now be the early adopters, with mid-market organizations behind them.
What are the primary factors preventing companies from adopting generative #AI in #ITSM? This article takes a look. Share on XThe primary factors preventing companies from adopting generative AI in ITSM
Our 2023 AI adoption data highlighted the main AI challenges as:
- Lack of skilled people – 57%
- Competing priorities for resources – 44%
- Legacy IT issues – 43%
- Employee resistance to change – 40%.
However, the use of generative AI adds in a couple more AI adoption challenges:
- Data security issues, which are more likely when employees use free AI tools
- Inaccuracy, which is often described as “hallucination.”
AI adoption’s impact on employee well-being
I’d previously warned about the effects of helpful AI on the work mix for certain roles because AI adoption might take the easier tasks, leaving some people with the more demanding tasks. Plus, we’d been asked if we had any data on the impact of AI on employee well-being.
While well-being is impacted by far more than AI use, we thought it an opportunity to get a feel for the potential impact of AI on employee well-being while running our 2024 well-being in ITSM survey.
The survey showed that AI adoption and use – corporate and personal – has had a positive impact on 24% of survey respondents, no effect on 66%, and a negative impact on 10%. We have no granular details on this, so for the 10% in particular, the change might be caused by the fear of the impact of employment more than anything else.
What are the top three #AI for #ITSM use cases? Here @StephenMann takes a look. Share on XAI for ITSM use cases that organizations are adopting
The top three AI for ITSM use cases based on our AI adoption survey data are:
- Intelligent workflow automation – to better execute and manage processes, for example, for incident and service request management
- Virtual assistants for employees – think chatbots
- Virtual assistants for staff – the augmentation of people’s knowledge and skills with AI capabilities, perhaps through Copilots.
There are other ITSM opportunities, too, including:
- Problem management – identifying recurring issues or patterns and root causes, and predicting issues before they occur
- Change enablement – assessing the impact and risk of proposed changes by analyzing historical data
- Knowledge management – curating and maintaining the knowledge base and improving information retrieval
- Service level management, analytics, and continual improvement – monitoring service levels (from service level agreements (SLAs) and generating real-time reports, sending automated alerts and notifications, analyzing customer feedback for service quality insights, and suggesting areas for service improvement.
3 tips for making a compelling case for AI investments in ITSM
- Focus on the business need, not the technology; experience data can be a great source of insight here
- There’s a need to elevate the push for AI adoption from IT to the C-level – the ChatGPT media attention will help here
- Align the benefits with business priorities, whether related to efficiency, productivity, decision-making, employee or customer experience, growth, cost reduction, scalability, or something else.
4 tips for getting started on or mapping out your organization’s AI journey
- People need to understand that AI adoption is inevitable – it will happen whether people want it or not
- Make it a business, not an IT journey – from getting that C-level buy-in to framing the benefits of AI in line with business priorities (and get teams working together)
- Avoid looking at AI in isolation – it needs to connect with other ITSM inputs and trends, from people, through existing processes and technology, to enterprise service management and digital transformation, all with a focus on experiences and value
- Start now, no matter how small, if you haven’t already – given the speed of advancement, it will be a challenging area to play catch-up on.
If you want to watch the full AI adoption webinar recording, you can access it here.
Further Reading
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Stephen Mann
Principal Analyst and Content Director at the ITSM-focused industry analyst firm ITSM.tools. Also an independent IT and IT service management marketing content creator, and a frequent blogger, writer, and presenter on the challenges and opportunities for IT service management professionals.
Previously held positions in IT research and analysis (at IT industry analyst firms Ovum and Forrester and the UK Post Office), IT service management consultancy, enterprise IT service desk and IT service management, IT asset management, innovation and creativity facilitation, project management, finance consultancy, internal audit, and product marketing for a SaaS IT service management technology vendor.
