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DB Systel GmbH
Transportation Made Smarter
Artificial intelligence (AI) is concerned with the automation of intelligent human behavior in machines and computers. Intelligence in this case, is the behavior of a machine that humans consider to be intelligent. Even for a company in the transportation sector, like Deutsche Bahn, the possibilities AI offers seem to be endless.
Cognitive technologies such as recognition, identification, reasoning, problem-solving and language processing let machines become a little more like ourselves. Of course, we do not want them to replace our species but make our lives more comfortable and add value to existing operations. What AI does is contributing towards speeding up processes and redefining them when necessary.
AI can reduce the need for excessive cognitive effort in many ways. For example, when train drivers learn how to efficiently drive on new routes they have never been on before, AI can support them during their training. Thanks to machine learning and previously produced data, a decision-making AI system can recommend or even carry out the most efficient way of driving. AI deals with data very effectively – and not just in trains, of course.
Just imagine how the generation of timetables for public transport can be made smarter with the use of completely new datasets that have never been used in correlation before, e.g., weather data or historic data from previous events.
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But how can your company become a part of the AI-induced digital transformation? One of the key factors supported by AI is customer engagement. Getting to know more about your customers and creating stronger engagements will make decisive differences. Even today, more than 80 percent of customers are using AI services–most of them without knowing about it. Many people still feel unsure about interacting with machines in a naturally human way through new interfaces. More than two-thirds of customers are using AI services in some way and most of them enjoy it if it makes life easier. Therefore, it is all about transparent communication and getting rid of prejudices. Customers will be less skeptical as soon as they see the value for themselves.
Thanks to machine learning and previously produced data, a decision-making AI system can recommend or even carry out the most efficient way of driving
The time for companies to adapt to new surrounding situations is shrinking. When the S&P 500 index first started out in the early 1950s, the average lifespan of a company listed in the S&P 500 index was 67 years. Currently, it is below 15 years, and in the 2020s, only 25 percent of today’s companies will still be in the index. Therefore, we need to continuously optimize operations and become more flexible to adapt to new market environments easily.
Along with the transformation and optimization of operations, new business models must be implemented. Emerging technologies allow the creation of new products and services from scratch to better suit new customer requirements. Machine learning and analytics let us gain new insights in the data accumulated over the years.
What does this mean for companies offering AI services? Reusability of modular AI services seems to be a suitable way of making solutions adapt to different customer requirements. The focus during the implementation process must lie on improving the satisfaction level of customers and employees, user experience, and service quality.
