Tomorrow’s users must be highly flexible in the future. They therefore demand the same user experience in the workplace that they are accustomed to from their private environment. Artificial intelligence can do this and will enter service management – whether companies are prepared for it or not.
The workplace of the future wants to be equipped with technologies and services based on artificial intelligence (AI). Assistants like Amazon Alexa, Apple Siri, Samsung Bixby and vehicle safety systems are faster and faster in our private lives. The same applies to AI-based translators like DeepL and Google Translate. They all have one thing in common: they make a whole new experience and make use of complex services easier and more natural than ever. But innovation is already on the rise in industry, logistics and the financial sector – and wants to be decisive in the competition over the next few years.
According to Gartner , artificial intelligence is one of the key investment priorities for 30 percent of CIOs by 2020. Although it is rather unlikely that robots a la Ex-Machina will be able to mount their own hardware on their own, the preparation for AI technologies should nevertheless be on the agenda of every CIO and IT manager.
In IT Service Management (ITSM) or Enterprise Service Management (ESM), Artificial Intelligence is primarily used to automate routine tasks that have been performed by technicians so far. The technology offers new opportunities for IT teams: they are relieved of regularly recurring activities and can concentrate more on strategic tasks than before. This includes, for example, training AI-driven technologies to serve a greater variety of service requests and to make the technique “more human”.
However, many companies are not yet prepared for AI applications and will not be able to leverage their benefits in the near future. The reasons for this are diverse, ranging from shadow IT and data silos, legacy ITSM platforms and tools to rigid service desk processes. In addition, there is a wait-and-see or even critical attitude of many IT teams, for whom the concrete realization of AI applications often seems a long way off. As the pace of AI innovation picks up, a significant number of companies will lag behind competitors economically.
The good news is that future-oriented organizations can still prepare for the next generation of AI technologies across industries. So what can CIOs and IT leaders do today to lay the foundations for a successful launch? You should first of all deal with the following topics and push ahead with appropriate planning as quickly as possible.
In the field of Service Management, Artificial Intelligence is basically “just” another means of automating self-service: users can create incidents and service requests – and receive an appropriate response within a very short time. KI can improve service processes, provide the right answers even for complex queries, and even assist employees in their professional re-start.
However, in order for such solutions to be adopted, users need to be confident that their requests will be answered reliably even without the classic calls to the service desk . It is important to not simply implement self-service on a functional level, but to specifically promote its broad acceptance throughout the company. Managers should therefore create a culture of self-determination. They have to succeed in having employees include portals in their self-organization and independently looking for a solution (self-responsibility).
For this to succeed, employees of all departments must be convinced that a few clicks in a self-service portal usually lead to much faster success than long phone calls or emails. To achieve this, the IT teams are also in great demand. Only when all users independently request services, track the status of incidents, and receive answers to frequently asked questions will AI initiatives succeed in the area of ??service management.
Expert Tip: IT teams who have already implemented a self-service portal can already experiment with Artificial Intelligence by selecting use cases where end users log in and interact with a simple chat bot or virtual agent to solve problems. To encourage engagement on the part of the user, companies can create incentives for departments to further improve the bot by using known scenarios.
The situation is serious: analysts at Gartner still believe that by 2020 about 99 percent of AI initiatives will fail due to a lack of knowledge. So this knowledge base is the first key piece of any AI-driven technology or service. Therefore, not too frugal collection of meaningful data and their consistent storage is already required today, so that they can be processed in the future by AI algorithms.
In the Service Desk area, these consist primarily of well-documented solutions to specific problem scenarios. This information should be kept as central as possible so that AI algorithms can interpret it later and provide users with the appropriate solutions. Ergo: Artificial intelligence is forcing a shift in the way knowledge is developed, collected and shared across organizations. The necessary change process is not to be underestimated and requires a lot of time and commitment.
IT teams should therefore start building knowledge management competencies in a timely manner and working with the departments to develop firm-specific best practices. Failure to do so will make organizations 99 percent owned by Gartners and unable to make meaningful use of Artificial Intelligence in service management.
Artificial intelligence also requires a high degree of experimentation and optimization within IT. However, traditional ITSM approaches usually do not support the sometimes huge and iterative changes to networked systems. The ITSM ITIL framework has proven to be very effective in the past, especially when it comes to helping IT manage easy-to-understand applications and systems. However, it is considered too rigid for IT environments that need to go through rapid evolutionary stages.
The key to overcoming such challenges lies in the introduction of agile or lean frameworks like DevOps . The methods contained therein can circumvent experiments, explorations and even uncertainties. They pursue an iterative innovation approach that enables smaller, more frequent and less risky changes in IT infrastructures. Approaches of this nature will be essential in the introduction of next-generation AI technologies. Gartner also estimates that by 2020, more than 50 percent of companies will completely replace the tools they have previously used to support the core IT Operations Management (ITOM) functions with those originally used by DevOps teams.
Employees of the future will no longer distinguish between inquiries to IT and inquiries to departments such as human resources, law or institutions. They expect a uniform system – regardless of whether they apply for leave, report a problem with the building services or want to order a new PC. Currently, the various service requests are usually handled via a central enterprise service management portal. The ITSM platform acts as a hub and the IT department configures automated workflows that support both the front-end experience and the back-end business processes.
Artificial Intelligence will take this enterprise self-service portal to the next level and provide users with a much more engaging, personalized and “smarter” front-end experience. CIOs can leverage their employees’ existing experience: IT teams that have proven their worth in implementing service management outside of core IT have the necessary know-how and should therefore be involved in the strategic planning and implementation of appropriate AI technologies be included in every case.
Find a specialist department with a high contribution to the added value of the company, which requires a portal, automation and reporting. Offer to automate their processes and workflows with your existing ITSM solution. If it does not adapt, it may be time to look for a sustainable alternative.
Artificial intelligence relies on the availability of relevant information from a variety of sources. This is especially true if it is to be used to predict events or automate service processes outside of IT. In mature IT infrastructures, however, data is often stored in separate individual systems that use very different standards. Information should therefore be concentrated in one central location – for example, in a data warehouse (DWH) or a service management platform. This central solution will allow future AI applications to access quickly and securely.
Companies will continue to use applications from various manufacturers in the future. A central core element of modern solutions are standardized interfaces (APIs) that connect them to one another. They also enable the direct exchange of information with AI solutions and can provide users with the desired results very quickly. Gardener predicts in its strategic architecture roadmap that by 2020, integration work to build a digital platform will account for 50 percent of the time and cost. IT managers should therefore check the degree of integration before purchasing a new business application and introduce it as a new decision-making criterion for tenders. In addition, it is advisable to examine existing and future ITSM platforms for their integration capability. They also need to be quick and easy to integrate with third-party solutions. Only in this way can executives ensure that in the medium term all users can benefit from the use of artificial intelligence.
Artificial intelligence is not just a hype but a serious trend that will also fundamentally change the service desk. Some critics see (not without reason) many jobs in IT departments at risk, but AI offers companies and their IT staff, above all, new opportunities: While routine tasks are processed automatically, they can concentrate more on strategic tasks than before – and the actively promoting much-discussed digitization within the company. However, CIOs should not forget: users in IT and specialist departments are already very demanding today and will remain the actual service customers in the future – without broad acceptance, the company-wide introduction of artificial intelligence can hardly succeed. As a result, executives not only have to create the technical prerequisites for AI, but also have to be prepared to embark on something new. Only when all employees are ready to go this way together will the introduction of AI-based service desk solutions be successful. Themes such as self-determination, knowledge management, enterprise service management, the use of agile methods and interoperability with third-party applications should therefore already be on the agenda of every CIO – and be integrated into the ESM roadmap in the medium term.