Customer service is fueled by new technologies. With artificial intelligence (AI) and machine learning technologies, new rules of engagement are enabled to meet customer expectations from a service organization point of view.

New, simpler, and faster methods have already resulted from new technologies via digital disruptions. Now, customers can fulfill service needs almost anywhere, anytime, and ideally through any channel. Jens Trotzky, head of Artificial Intelligence Technology, Customer Success Services at SAP, explains whether AI-driven product services are simply undergoing an evolution or facing a paradigm shift, where service automation is today, and what to expect in the near future.

Q: Digital disruption does not stop for service organizations. Looking at changes in service and support technologies and tools, are we simply undergoing an evolution or are we facing a paradigm shift?

Trotzky: First of all, digital disruption is a great chance to rethink and redefine business processes and goals and to invent something completely new. This happens across industries and across lines of businesses. Due to new technologies and continuously changing customer expectations, service and support is fundamentally changing, and, to a certain extent, we need to reinvent ourselves. Therefore, I would no longer call this an evolution of what already exists. We are certainly experiencing a paradigm shift here.

Digital disruptors, like Amazon, have completely changed customer experience, engagement models, and customer expectations and behavior. Customers now want the same convenience with simple, fast, and easy-to-use access for their work environment.

With the goal of anticipating customer needs and providing solutions even before a question or problem occurs, AI and machine learning are also key when providing self-service tools and assisted self-services as part of a sustainable, fully-integrated service automation concept.

In product support, service automation seems like a buzz word to explain how and why vendors are improving processes, tools, and customer support. Where is SAP with service automation?

The idea of service automation is not really a new approach, but we now have the right technologies to offer a completely different bandwidth of automated services. With AI and machine learning technologies, we kicked off a new area in product support services and the journey has just started. According to Gartner, “The proportion of phone-based communication will drop from 41 percent to 12 percent of overall customer service interactions, [but] a human agent will still be involved in 44 percent of all interactions.”* For product support-related service interactions, I expect that in the very near future the majority of customer interaction for technical problems or questions will easily be solved in real-time using digital customer engagement models. This is possible because of AI and machine-learning technologies.

In the context of service automation this means that self-service offerings have a growing impact on a positive customer experience. Customers no longer want to reach out to a support engineer but prefer to help themselves. Therefore, self-service, in combination with assisted service, is increasingly important. Of course, the tools need to be simple, easy to access, and backed by the right technologies in the backend to deliver a service automation at its best.

If the majority of the engagement will be digital, what happens to the remaining non-digital interactions?

There will still be a need for human-to-human interaction and direct engagement with a support engineer, especially if a very complex problem or question cannot be answered by a chat bot. And, as estimated by Gartner, I would predict that in product support the involvement of agents in overall interactions, regardless if they are digital or human-to-human, will hardly drop under 35 to 40 percent.

Nevertheless, service automation frees up more time for support engineers to focus on more complex and demanding issues, which is also very beneficial for customers.

If customers cannot find the right answer themselves through self-service tools, like SAP Knowledge Base Articles or via a chat bot, they will still want to be able to reach out to support or a service engineer right away. Most importantly, customers expect a completely seamless transition from automated, unassisted services to assisted service and human-to-human interaction without the need to switch channels or the risk of losing any information along the process.

In addition to all this, the role of service and support experts will also change over time, becoming more and more like a trusted advisor for customers instead of only fighting the fire when it is already there.

What are the most important steps to meet customer expectations when taking service automation to the next level?

The customer needs to be at the center of the entire process. Even when developing new tools, vendors need to take an outside-in perspective, meaning not trying to tell the customer what is good for them but to transform customer needs and expectations into seamless, fast, and convenient service and support.

Vendors also need to understand that a purely cost-driven transformation to cut down service calls and with it the cost of service, is not the best approach to achieve sustainable change in service and engagement models. A cost-driven approach supports an inside-out perspective and does not put the customer at the center, most likely resulting in decreased customer satisfaction and customer success. In the end, this would have a negative impact on vendor business results.

Additionally, there needs to be a sustainable investment into new technologies, like AI and machine learning, to deliver on customer needs and expectations. At SAP, my team and I focus on AI-driven service and support solutions and features. This includes the development and rollout of AI-embedded service processes, chat bots, conversational UI’s, like in SAP’s built-in support functionality with virtual assistants like SAP CoPilot, and incident-solution matching based on machine learning for intelligent search.

Have AI and machine learning capabilities already been fully explored or will there be more to come in the near future?

Looking at what has already been achieved, it might seem that we have explored a lot of opportunities around what those technologies offer. But considering the fact that AI- and machine learning-based tools get better and better with the more data they can use, I would say we are still at the beginning of this journey.

Our goal is to build algorithms with advanced models for analysis and to transform AI insights into better customer service and improved service processes. More efficient service operations is a continuous innovation process.

With regard to service automation at SAP, we are currently testing automated ticket categorization and intelligent incident routing or scheduling to engage with field-service resources when needed to provide a predictive maintenance and service experience to our customers. In addition, our AI-driven process automation will also be leveraged for more complex case management and highly repetitive, service process workflows.

Do you have any predictions for the future of AI- and machine learning-driven service and support automation?

Looking into the near future, I believe that chat bots will remain the hottest topic. They will finally automate the entire customer interaction and even mimic human interaction.Customer-service interactions will be managed more and more by AI-driven tools and processes.

Processes in service and support will become faster, safer, more predictive, and, with regard to technical problems or questions, even preventive.

Sophia Stolze is communications lead of External Communication for Customer Success Services at SAP.
*Gartner: Plan Now for Critical Shifts in Customer Interaction Patterns