Artificial Intelligence is redefining the role of ITSM in data-driven business organizations. ITSM users expect new solutions to deliver on the promises of service excellence, instant and effective delivery of highly personalized ITSM capabilities. However, many CIOs continue to experience a disconnect between the marketing hype and real-world performance due to underoptimized technology enablement. In this article, we take this discussion to some of the leading industry experts, who weigh in on the best approach to deploy AI technology solutions to optimize ITSM delivery:
“In service management, the most obvious place to deploy AI is the self-service channel. Imagine the improvements to the service desk workload when automation can serve up exactly the right answer to your customers questions! But the answers don’t come preloaded, and if you’re like most enterprise IT teams I hear from, you don’t even have a working knowledge base for your own internal reference, let alone making that knowledge public through self-service. When you weave knowledge into your incident management process, by capturing the issue in the words the customer used and noting the steps to resolve it, that interaction can easily become the basis of a knowledge article. Before too long, you will have captured the most common issues into knowledge articles that be reused internally and served to customers with the help of AI’s suggestions. Remember the parable of the house built on sand? AI without knowledge management is unstable. If you build your intelligent self-service on a strong foundation, you and your customers will extract the value that AI was intended to deliver.”
” Too many think it’s too difficult or their organisation is not ready for AI – I’d advise not to wait! I’d recommend that you’ll have a clear view on what you want to achieve from the use of AI at the ITSM layer and what outcomes you want to drive – you can never be 100% on what you will get, but as a minimum they will get confirmation or correction on their perception, but insights to drive improvement nevertheless.
Finally, organisations have to stop treating IT and ITSM like the poor cousin! All organisations have massive amounts of data at the ITSM layer that tells a story and provides insights – many that are unlikely to be obvious, but can help to drive improvements in areas that they were not aware of as being an issue. There is no way that manual approaches to analysing data are going to aid the realisation of improvement at the speed and accuracy that an AI solution such as Swish.ai will, so orgs simply can’t afford to delay taking that 1st step. “
“Successful deployment of AI is not about technology. Successful deployment is all about the people.
Invest as much, if not more, in the adoption of change than the technology.
Stakeholder engagement, management commitment, communication, engagement, training, and readiness for change, are all critical aspects for the transition is to be a success.
There needs to be widespread understanding of why the deployment is necessary for organizational growth. Everyone has to understand the benefits it will bring to them as an individual, as well as their team. Effort has to be put into removing any fear – real or perceived – about the changes AI will bring about.
When there is enterprise buy-in and commitment to the change, you are far more likely to get your return on investment.”
One of the key tenets of ITSM is knowledge, however knowledge management is not an easy practice to master and can become more difficult as your organisation grows. Truly understanding your end to end customer journeys, the people. the technology, the processes, and everything else that has to work in synergy in order to support these journeys as well as co-creating value through service offerings is an art in itself. Knowing when these service offerings are in optimal working condition and where there is opportunity for improvement, that kind of knowledge and insight is worth its weight in gold. The key to unlocking this knowledge can be found in the data that a service organisation already holds or has access to.
The amount of data that has to be correlated to turn it into information, the amount of information that needs to be analysed to turn it into wisdom, the context and understanding that’s required in order to obtain wisdom. This is becoming more difficult for humans in a world where the pace of change is rapidly and endlessly accelerating, where there is no longer any time or appetite to achieve and maintain a status quo, where agility is king. We can’t cope because the quantity of our data is beyond our collective organisational grasp, never mind the ability to interpret and use that data to our advantage. We are drowning in data to the point where we are looking for needles in haystacks, sometimes without knowing what the needle looks or feels like; we’re seeking knowledge that’s just outside of our grasp and yet it’s all there, within our servers, our data centres, our data lakes. Our people have the right levels of intelligence but not the time nor the capacity to even skim the surface.
Imagine the world when AI tells you that there’s a problem in your network or in your software, where AI recognises that a change will fail due to some other activity that another team is doing but it just wasn’t visible to the whole organisation, or when AI spends all of about 3 seconds trawling through forums and message boards on the internet, what would take a human months or years to do, and gains all sorts of novel insights into potential opportunities to grow, transform, or to simply stay relevant. What about when AI can ingest all of the data that your organisation has been collecting since its inception and not only reads it, but learns from it, identifies patterns and contextualises the data, and is then able to present this as knowledge and insight. How powerful a position would that be in which to find yourself. AI will learn and grow and with it we and our organisations will learn and grow in a symbiotic and beneficial relationship. How many organisations have that one individual whose head is so full of valuable information and knowledge yet we know that individual won’t be, can’t be there forever. AI will never leave, will never slow down with age, in fact the opposite is true. AI will become an integral and indispensible member of the organisation and will enrich the services that you create, deliver and support.
Harnessing the power of AI will be as momentous as when we first learned to control fire. It will be remembered as one of the pivotal points in our history and our evolution as a species, setting us on a path of discovery towards a new chapter, a new dawn, and we’ll never look back.
״ ITSM, unjustly, has a bad reputation. It was introduced in a variety of practices (ITIL, COBIT, VeriSM®, IT4IT and more) to help organizations create, deliver and support services and products enabled by technology. Instead, it is perceived as slowing down innovation or being too costly to help organizations welcome the Digital Age.
When I was a CIO, I made it a habit to go to the Service Desk 3 times a week. Why? Because this is where customers (internal and external) told us how good we were doing in servicing their needs (requests for our products) or how bad we were doing (incidents and complaints). Over the years we became attuned to this information to help us adopt and adapt technology to make things better and safer, whether it was how staff performed their duties or in new services.
AI is a game changer. No longer do we have to wait for a report or download a lengthy file which is then read by a script to tell us the truth. AI provides us with real-time information: performance, security, usage, gaps, issues, requests and more. AI learns from our applications how they are normally used and if needed, adds more capacity based on unanticipated demand. Without AI, this would be manual coding and testing, but AI simplifies this task. With AI acting as our eyes and ears of IT, the IT teams can concentrate in value innovation. I strongly suggest that leaders allow AI to be introduced and blended with cloud-based services. It will be the only way to survive the pandemic and enter the digital economy. support of services. The pandemic has moved (forced) the world to use the internet as a network in bridging organizations to customers. Welcome to the Digital Age! ״
״ I have spent 30 years in the IT service and support industry, as a consultant, speaker, and author. When I began my career, front-line help desk agents were mere message takers. Today, they are some of the most highly skilled professionals in IT. This transformation was necessary as the demands of the job required ever more skilled professionals to meet the needs of an increasingly complex IT environment.
AI has, and will continue to be a disruptor in the industry. Initially it will eliminate the need for agent-based commodity support – think Microsoft Office, Windows, password resets, and other easily resolved problems. But as machine learning makes each deployment of AI progressively more intelligent, even the most complex support provided by today’s customer facing agents will be replaced by more intelligent bots. Yet the majority of agents see AI and automation as a good thing because it will transform careers for the better.
Much like today’s auto industry assembly line workers are engineers monitoring computer screens while robots actually build the cars, the support technician of the future will become a support engineer who monitors, coordinates, and directs the efforts of the AI bots. For the best and most talented in the industry, the future of IT service and support has never been brighter! ״
3 steps for an effective AI deployment in your IT service desk in 2021
“AI is the new electricity,” said Andrew HG, founder and CEO of Landing AI. And true to his statement, over the last few years, AI has made its effects felt across industries, including IT service management (ITSM). But like any technology, the success of AI initiatives and their application in IT service desks depends on multiple factors. The key success factors of any AI deployment are:
When set right, these three factors can lead to an effective AI model that continuously improves itself over time, leading to better outcomes. Below are the steps that will help ITSM teams fix these critical success factors.
1. Invest in the right AI capabilities
Thanks to the efforts of various ITSM vendors and AI startups, the application of AI in everyday ITSM processes has become more democratized. Most ITSM vendors today offer some level of AI capability, ranging from conversational virtual agents to intelligent automations. It is important that IT decision makers define the expected outcomes of their AI initiatives and then choose a solution that aligns with their objectives rather than make FOMO-driven investments.
2. Onboard more users into your IT service desk
Once the right ITSM software with the right AI process is set in place, either through native capabilities in the ITSM solution or through value-added AI integrations, the second step is onboarding more users into the ITSM solution. Data is the core of any AI model, and without enough people accessing and using the IT service desk, the AI algorithm won’t have enough data to be trained on. It’s important to make the IT service desk more accessible to end users by integrating the ITSM solution or the AI-enabled ITSM virtual assistant with the company’s digital workspaces or intranet portals.
3.Organize your ITSM data
The effectiveness of any AI model depends on the quality of the data it is trained on. Doing the first two steps right means the organization has enough users generating enough IT service desk data to train the AI model, be it an automated categorization algorithm or the responses of the virtual ITSM support agent to users’ conversational commands. But the success of these models depends on the reliability and accuracy of the data. IT service desk teams should document proper ticket parameters, organize their solutions appropriately, and have enough asset information populated in their ITSM solution.
These three steps can help ITSM teams realign their existing AI deployments and launch new AI initiatives in 2021 that are effective and help optimize the organization’s IT service delivery and IT service management processes.
Want to know more about ITSM optimization? Check out Swish.ai’s Economic Impact Report analyzing data from 400 enterprise companies, with insights, statistics, and solutions to reduce ITSM cost and ticket volume while increasing customer satisfaction and efficiency.