In a recent webinar with SymphonyAI, I discussed artificial intelligence (AI) adoption in enterprise service management (ESM) scenarios. This article shares some of the points we discussed on AI adoption in ESM, starting with how ESM has evolved in recent years.
A brief history of ESM
It’s hard to talk about AI adoption in ESM without first looking at what ESM is. Importantly, it’s not new. I was talking with IT service management (ITSM) tool vendors about something called ESM back in 2008.
Back then, it was very much a case of “lifting and dropping” the corporate ITSM tool into other business functions – such as human resources (HR) and facilities – to provide workflow automation and other ITSM tool capabilities that were absent from their tooling. It was pretty much a “forced fit,” but it still worked for the receiving business functions.
As far as I know, there’s still no agreed-upon definition of ESM in the ITSM industry. So, here’s one I started using a decade ago and have tweaked slightly in recent years:
“The use of ITSM capabilities by other business functions to improve their operational performance, services, experiences, and outcomes.”
So, ESM is all about better operations and outcomes across the organization rather than the forcing of ITSM capabilities onto other business functions. This is reflected in how ESM is now thought of and the enabling capabilities offered by ITSM tools.
What ESM really is
In the same way that ITSM adoption isn’t usually the use of all 34 practices in the ITIL (formerly known as the Information Technology Infrastructure Library) body of service management best practices. ESM is commonly the adoption of the service-desk-related practices or processes. It’s also potentially misnamed, with other business functions unlikely to seek enterprise service management. Instead, they want digital transformation, digital enablement, workflow automation, work optimization, or something similar that can bring about the better operations and outcomes mentioned earlier.
Hence, ESM is likely to be seen as a route to:
- Better service experiences and more consistent outcomes
- Improved process and people effectiveness
- Improved speed/efficiency and reduced costs
- Improved visibility into operations and performance
- Ongoing improvement
- A higher return on investment (ROI) for the corporate ITSM tool
- Standardization of service and support – services can be built around employee needs rather than what disparate service providers offer.
AI adoption in ESM scenarios amplifies these potential benefits.
How AI-powered Copilots amplify ESM opportunities
Generative AI (GenAI)-powered Copilots offer focused use cases to internal service providers such as HR, facilities, and legal (as well as IT). For example, high-level AI adoption in ESM opportunities are:
- An employee-focused Copilot can help employees self-help. This can include providing relevant knowledge articles, engaging with service-provider workflows, or task automation.
- A service-provider-focused Copilot can help service-provider employees to “work smarter, not harder.” This can be work prioritization, accessing relevant information, or creating new or updated knowledge articles.
- A leadership-focused Copilot can help leaders understand operational performance and make better, data-informed decisions. This can be via real-time insights and identifying patterns and trends that would otherwise be missed – facilitating improvement, forecasting, strategy-making, and time-critical operational activities.
These three use cases are already seen in IT through teh top three applications:
- Intelligent workflow automation – to better execute and manage IT processes, for example, for incident and service request management
- Virtual assistants for employees – to get quicker IT resolutions via self-help
- Virtual assistants for IT staff – the augmentation of people’s knowledge and skills with AI capabilities.
AI adoption through an ESM lens
ESM aims to extend ITSM capabilities to other business functions as needed. Hence, examples of AI adoption in ESM scenarios include:
- Knowledge management within an HR department being facilitated by Copilots. From the automatic creation of knowledge articles from case text to the automated presentation of the most relevant information to HR staff or employees seeking help.
- Workload management being improved within a corporate legal team by leveraging Copilot capabilities to manage work intake and the associated processes. For example, Copilot-based self-help capabilities can be embedded within corporate collaboration services such as Microsoft Teams and Slack.
- Facilities teams using communication-related capabilities to respond to employee requests or to create formal communications that articulate facilities policies, best practices, decisions, or anything else that needs to be distributed to employees.
- Finance teams using Copilot analytics capabilities to spot errors and irregularities, such as fraud. The capabilities can also help with scenario planning to support strategic decision-making and assess corporate compliance and governance positions.
Addressing nervousness about AI within business functions
As with anything new, there’s likely to be hesitancy over AI’s use. To help, people need to understand more about AI and tools such as Copilots in terms of how they work and what they are good at and aren’t. There’s also a need to be clear about the challenges organizations face when adopting AI-enabled capabilities. Our 2023 research showed the top challenges to be:
- Lack of skilled people – 57%
- Competing priorities for resources – 44%
- Legacy IT issues – 43%
- Employee resistance to change – 40%
When considering GenAI capabilities, data security issues and the potential for inaccuracy also come into play – especially with free AI tools. This is highly relevant, given that free GenAI tools such as ChatGPT are already rampant in the IT workplace. Our 2024 data shows that while 36% of IT respondents already use corporate AI capabilities, 66% use free AI tools such as ChatGPT. While making employees more productive, this also brings some unwanted risks.
People also need to be confident in the opportunities of AI adoption in ESM scenarios in order to sell the potential use cases to others. They also need transparency into how the capabilities work in order to convince themselves and others of the validity of outcomes.
Three key takeaways
My three AI Adoption in ESM takeaways were:
- Appreciate that the use of AI and Copilots within ITSM and ESM is inevitable—the technologies will continue to be embedded within ITSM tools, and employees and customers will expect experiences that require their use. So start now, no matter how small, if you haven’t already.
- While AI might be a technology “thing,” its use should be business-driven. Align the stated benefits with business priorities, whether related to efficiency, productivity, employee or customer experience, growth, cost reduction, decision-making, scalability, or something else.
- Avoid looking at AI opportunities in isolation – it needs to sit with ESM or digital transformation, and with a focus on experiences and value.
You can access the full AI Adoption in ESM webinar recording here.
Please use the website search capability to find more helpful articles on service management topics such as service delivery, recruiting incident managers, knowledge bases, customer service, ITSM processes, service catalog management, developing team members, user experience, improving business operations, service levels, enabling business processes, service portals, service management practices, developing IT support teams, designing products and services, meeting business goals, changing products or services, selling service offerings, automated workflows, and service operations.
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.
