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The topic of “Artificial Intelligence (AI)”—including its applications and uses—is something that interests me both personally and professionally. I’m also very interested in the current state of research and future prospects. So the“F.A.Z. Conference on Artificial Intelligence #2”in Frankfurt came at just the right time.
In a very well-organized format featuring presentations, use cases (e.g., SAP & Elastic), and panel discussions with high-profile guests such as Richard Socher (CEO of you.com and former Chief Scientist at Salesforce), Hamidreza Hosseini (CEO of Ecodynamics), and Prof. Dr. Holger Schmidt (Head of the FAZ Editorial Department and professor at TU Darmstadt), the event provided a good overview of where we currently stand in the AI era and where the journey might lead with new agents and models.
As abstract as much of AI research may seem, many use cases are very real. Agents are capable of reliably taking over workflows and thus fully automating them, for example in industry. The pace of development is rapid, and yet, throughout all the presentations, I can’t help but feel uneasy that we in Europe—and especially in Germany—are still unprepared for this revolution in many areas.
At a time when there is a shortage of skilled workers and overall productivity is declining, AI could be a solution for efficiently deploying the skilled workers we still have.
A good example of this was provided by our colleagues at Elasticsearch in their use case with Miles & More, which is part of Lufthansa. They use Elastic for fraud detection to identify patterns and anomalies in their frequent flyer programs with the help of AI. Using data from the logs of various systems, agents can be trained to act independently or filter events. This reduces the workload on employees in fraud detection. It saves Miles & More a significant amount of money on prevention and allows them to deploy skilled staff more efficiently.
Much of this is not new. Elastic has long been capable of processing and visualizing large volumes of data, and we also used by us in customer projects. What is new, however, is that automated responses and the training of agents using AI are now possible.
In well-established and already digitized companies, AI can be implemented quickly. However , for many companies—especially small and medium-sized enterprises—this digitization is still in its infancy.
Often, data is either not available at all or only partially digitized. As a first step, this data must be digitized and, above all, structured so that the great potential of AI can be realized. As an agency specializing in the digitization of SMEs, we know how difficult it can be to get started here.
Nevertheless, this step must be taken; otherwise, a company risks falling behind competitors who have embraced AI-driven digitalization in the future. After the conference, I’m even more convinced of this than I was before.
Larger companies can rely on solutions—such as those from SAP—and use SAP Joule Studio and the SAP Business Cloud to create their own agents that can access all SAP data. A very engaging presentation by Martin Guther of SAP Germany demonstrated this by showing how to easily create an agent for tender processing, which significantly reduces the time required to prepare the necessary documentation. However, data structure—and above all, data quality—remain critical factors here as well. The presentation was titled“Garbage In, Garbage Out—Data as the Key to AI Transformation” —it couldn’t be more fitting.
This is exactly where the mixed feelings come in. It’s perfectly clear what needs to happen for European and German companies to compete successfully on the global stage. Instead, however—even at the political and regulatory levels—there is a very strong focus on the risks of this new technology. These risks must, of course, be taken into account, but they also threaten to slow down innovation and create uncertainty regarding investments in digitalization and AI.
Especially in economically challenging times, digitalization must not be put on the back burner for small and medium-sized enterprises. Otherwise , there’s a risk of a rude awakening. During the Industrial Revolution, it was the steam engine; later, the internet; and now it’s AI that’s turning our world upside down. What a time to be alive!
