Rising ticket volumes, complex system landscapes and high user expectations are pushing many service organisations to their limits. AI-powered service desks promise to ease the burden – provided that processes, data and knowledge are organised effectively. Find out how intelligent support can transform service processes in IT, business units and customer service.
One of the most common reasons for dissatisfaction with support is not necessarily the time it takes to resolve an issue – but rather a lack of transparency. Users want to know what is happening with their enquiry, who is working on it and when they can expect a response.
Questions such as ‘Where is my ticket at the moment?’ or ‘Is it normal that I haven’t heard anything for two weeks?’ are part of everyday life in many service desks. If such questions remain unanswered, the impression quickly arises that issues are disappearing into the system or are not being given sufficient priority. To many users, this quickly comes across as unprofessional and not very customer-focused – and can permanently undermine trust in the service organisation.
At the same time, another area of tension is evident in many organisations: the focus is often heavily on achieving the fastest possible response times. However, speed alone does not determine the quality of a service. A quick but unhelpful response rarely solves the actual problem. For users, a precise and solution-oriented response is far more valuable – even if it takes a little longer to arrive. What matters, therefore, is not just how quickly a ticket is answered, but whether the response actually helps.
Digital service agents can play an important role here. They act as the first point of contact for users and are available round the clock. Users receive an immediate initial response, can check the status of their tickets or provide additional information. In many cases, initial solutions can even be provided straight away – for example, through automatic access to relevant knowledge articles or known solutions.
Such systems can also provide valuable support for service desk staff themselves. Whilst simple and standardised enquiries – such as those relating to known issues or frequent service requests – can increasingly be answered automatically, staff benefit particularly from AI support when dealing with more complex issues.
AI-powered search functions analyse incoming enquiries, compare them with existing tickets and suggest relevant knowledge articles or solutions. This makes it possible to identify relevant information more quickly, and even less experienced staff can familiarise themselves more easily with complex topics and provide well-informed answers.
Another challenge facing many service organisations is the high proportion of standard enquiries. Password resets, access authorisations and simple configuration issues are part of day-to-day operations and often account for a large proportion of the ticket volume. Individual enquiries of this kind can be dealt with quickly. Taken together, however, they result in a considerable workload. Service desk staff spend a great deal of time on recurring routine processes, whilst more complex issues remain unresolved.
This situation often leads to a constant tension: on the one hand, there is a feeling of constantly working through tickets; on the other hand, there is a lack of capacity for sustainable problem-solving or root-cause analysis. In some cases, short-term workarounds therefore become permanent solutions – simply because there is no time for fundamental improvements.
Even without the use of AI, automation and intelligent ticket management can already provide noticeable relief here: modern service desk systems automatically analyse incoming enquiries and forward them directly to the relevant contact persons. Furthermore, AI-powered agents can independently handle certain routine tasks – such as processing standardised service requests or documenting solutions. This has a twofold effect: processing speed increases, whilst at the same time support teams gain more time for complex tasks.
Many major incidents do not arise suddenly. They often show early warning signs – such as unusual error messages, a rise in the number of tickets relating to a specific issue, or recurring problems in individual systems. In the day-to-day running of a service desk, however, such patterns often go undetected. Staff focus on processing individual tickets and have little time to analyse broader contexts.
This is where AI can demonstrate its strengths in pattern recognition. By analysing monitoring data, ticket content and communication histories, anomalies can be identified at an early stage. If similar problems occur frequently, the system can automatically provide alerts or trigger an escalation. This enables the service desk to become increasingly proactive.
Instead of merely reacting to incidents, support teams can identify potential problems at an early stage and take action before they have a major impact on users. Users also benefit from this: if an incident is already known, users can be informed directly. In some cases, this can even prevent new tickets from being created in the first place.
However great the potential of AI in the service desk may be, in practice the transformation rarely begins with technology alone. A key prerequisite for the successful deployment of intelligent systems is a robust data foundation. Knowledge articles must be up to date and clearly worded, service catalogues must be clearly structured, and ticket information must be documented consistently. Only when data and processes are reliably established can AI systems provide well-founded recommendations or automate tasks.
That is why it is often worthwhile for organisations to start by carrying out a thorough assessment: How are the existing service processes structured? What data is already available? And where do delays or data disconnects currently occur? This often reveals that even optimised processes or traditional automation steps can deliver significant improvements – even before AI is deployed on a large scale.
The principles of a modern service desk are no longer confined to IT. More and more companies are extending these structures to other service areas – such as HR departments, facility management or financial services. As part of enterprise service management, centralised service platforms are being created through which staff can submit a wide variety of enquiries via a single point of access. The service desk thus becomes a central hub for service requests across the entire organisation.
Furthermore, similar structures can also be applied to external customer processes. Whether it’s customer hotlines, support portals or digital service platforms – wherever enquiries need to be received, categorised and processed, automated processes, knowledge bases and intelligent assistance systems can improve service quality.
Many organisations are currently grappling with the question of how to develop their service structures in a way that is fit for the future. This is less about the introduction of individual technologies and more about the strategic development of the entire service organisation.
Materna supports organisations in holistically analysing and developing these structures – from the traditional IT service desk through to internal service departments and customer-focused support processes. Using structured analysis frameworks, existing processes, data structures and service workflows are examined to identify opportunities for automation and AI support.
Depending on the initial situation, the path may lead from initial process optimisations through pilot projects to the introduction of comprehensive AI-supported service structures. The aim is always to align technology, processes and organisation in such a way that the workload on staff is sustainably reduced, whilst users benefit from faster and more transparent services. After all, it is not the technology used alone that determines the success of a service desk – but the interplay between people, processes and knowledge.
Find out more about the AI-supported service desk.
