How AI will shape the service management landscape: trends and challenges
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How AI will shape the service management landscape: trends and challenges
Marietta Protonotariou
6th September, 2024
7 min read
Marietta Protonotariou
6th September, 2024
7 min read
AI technologies have become part and parcel of our lives, lets delve into the trends and challenges to understand the AI impact on our service management practices and delivering value to customers.
AI technologies have become part and parcel of our lives and are applied in a range of ways by different industries and business functions. For example, Generative AI (gen AI) is already shaping how services are delivered across the enterprise.
"A Gartner® poll finds that 70% of organisations are currently in exploration mode with Generative AI ¹"
Gartner
But how is AI helping ITSM and ESM, where is it headed, and what are the big challenges that organisations are forced to tackle? Here, we answer these questions and consider the benefits and limitations of this unstoppable technology through a service management lens.
What is the difference between AI and Generative AI?
Before we delve any deeper, let's understand the differences. According to Forbes², traditional Artificial Intelligence (AI) pulls information from existing data available to it, such as information on a customer service desk request. However, gen AI goes further because it can create something new based on the information or data you input. This means it could provide context, respond to complex questions, and advise on your response to the customer, for example.
Where is AI heading in the service management space?
With the launch of OpenAI’s ChatGPT in 2022, there has been a huge focus on AI, causing organisations to discover how they can leverage it, leading to higher expectations of ITSM platforms.
McKinsey³ estimates that current gen AI, alongside other technologies, has the potential to automate 60-70% of the tasks currently taking up employees’ time. Nowhere is this more apparent than in the automated provision of key services through service management like IT and HR. The need for reskilling is very real. Leveraging AI in this way allows IT teams to focus on more complex issues, leading to increased efficiency and reduced costs.
It will be interesting to observe how companies take that next step. Will generative AI plateau around the 50% mark like other AI technologies? Its promise is leading companies to increase their AI investments, with the knowledge that a more comprehensive understanding is the way to best harness its potential. But in doing so, there are a number of unavoidable challenges to face, including identifying opportunities, implementing governance, managing third parties, and understanding the impact on your people and other tools around your service management solution.
However, as AI becomes increasingly popular and continues to evolve at a colossal rate, it poses a significant threat to job losses in IT. Let’s examine what you should also be aware of when considering AI.
Is AI a silver bullet to service management success? Not exactly.
The excitement is palpable, but businesses should have a realistic outlook to better navigate what they’re getting into with AI. Let’s take a closer look at some of the challenges and limitations gen AI poses when incorporated into ITSM and ESM solutions.
Data accuracy
With gen AI, its performance is subject to the data you feed it or that it has access to. Although generative AI is leaps ahead, it still requires data input. However, there’s good news! AI can be a valuable tool for managing your knowledge bases by grouping complex information from assets to processes, making it more accessible, better managed, and kept up to date.
Regulations and compliance
Understanding if it is possible to comply with industry regulations if AI is part of their service management solution is a big question for organisations in heavily regulated industries. We recognise that gen AI is potentially too powerful and that individual organisations cannot be expected to regulate themselves, but are we prepared for the variety of regulations worldwide, and the impact on work where these tools are already becoming commonplace? This could pose challenges for organisations that are considering using AI to analyse sensitive customer data to improve service management processes.
Low adoption rate — the skills gap
When it comes to ITSM specifically, Forbes reports⁴ that while there’s a growing demand for AI and Machine Learning (ML) skills, many ITSM practitioners are not familiar with these technologies and don’t have the knowledge and training needed to implement them.
It’s clear that even with this skills gap, there’s a notable lack of training to get employees up to speed. While businesses are using AI to plug skills shortages, reduce manual workloads, and carry out repetitive tasks, they’re not reskilling employees to leverage these tools for greater efficiency. For example, using gen AI to summarise a complex issue during incident resolution, resulting in faster MTTR.
ITSM maturity
Finally, organisations looking to benefit from AI in the service management sphere will struggle if their ITSM solution is not at a high level of maturity. Adoption of gen AI tools requires a high level of service management maturity of processes and workflows, with fully digitised services being fulfilled using modern platforms. This allows gen AI tools to access the data to provide advanced content personalisation. Appropriate data governance, data quality, and data architecture, alongside robust data management, need to be in place for any real impact.
Key considerations to get you started
To summarise, we know there is a lot to be aware of with the rapid evolution of artificial intelligence, so here are a few key takeaways to get you started:
- 70% of organisations are already exploring gen AI, and so should you. For many organisations, AI cannot be applied to their service management solution overnight. Start your research now to understand what you need to do to be better positioned to get the most out of AI.
- Get your data and knowledge management in order. Consider using AI to help get your data and information on processes, customers, etc. in order first, before advancing to using gen AI. Having a low ITSM maturity means the effort vs value added by AI functionality will be negatively outweighed.
- Mind the skills gap! Having an AI-powered ITSM solution is well and good, but you must have the internal skills to manage and operate it. So, bring your team along on this journey because this is also a great way to build your AI champions!
Unlock insights on how AI can make service management smarter.
Now you know the theory of AI lets go deeper and apply it from a service management perspective, and which frameworks AI may best support.
Written by
Marietta Protonotariou