Data plays a central role in our society. It is not for nothing that it is often referred to as the oil of the 21st century - although the comparison is misleading. While natural resources will eventually run out, the raw material of the modern age is inexhaustible. This applies both to the data that is collected about us every day and to key figures and measurements in the corporate context. The rapid digitization of the economy and society is thus opening up numerous value creation options for companies. The value of the data economy in relation to gross domestic product has long since grown in dimension: The EU Commission, for example, expects the volume of the data economy - i.e., the direct, indirect and induced effects of the data market on an individual national economy - to rise to over 800 billion euros in the 27 member states by 2025.
However, inexhaustible raw materials obey completely different rules. The special feature of data is that it is only through the cross-linking of individual pieces of information that real added value is created. AI plays an important role here: it recognizes patterns, derives decisions based on them, and finds exactly the information you need in a huge mountain of data. While AI copes well with Big Data, the AI training process should be Small Data optimized. What do I mean by that? Most companies are not in regions where, say, Internet giant Google is. From self-driving cars from Alphabet subsidiary Waymo to its acquisition of U.K.-based specialists Deep Mind, which is advancing rapid analysis of protein structures as part of pharmaceutical research, among other things, to powerful AI as versatile as a human brain, Google keeps making billion-dollar bets on the technology. Now, most other companies do not have the money or the necessary volumes of data to do so. Modern AI methods must therefore be able to get by with very little training input. This is the only way they can be adapted to real, specific tasks in companies. This characteristic also strengthens the democratization idea of AI - as one of the cornerstones for close cooperation between technology and people.
Basically, the use of AI brings profitable benefits to almost any company, regardless of size. A good example is the freeing up of tedious, repetitive tasks. For example, automatically routing emails based on their content, checking applications for completeness, correctness and plausibility or even the complete data management in a company can be raised to a new level by AI. After all, it is only with AI that companies can realize intelligent linkage and intelligent data enrichment across their heterogeneous data and information, no matter where it resides - by using metadata and also generating it automatically. Faced with millions or even billions of documents, no company has the human resources necessary to implement this enrichment or information linkage with humans. However, both are indispensable in order to keep the necessary data ready for the constantly growing requirements in daily business operations.
The fact is, AI is shaping the future of our data economy. The question is rather how well companies are doing in the intelligent use of data. Only those that succeed in generating additional value from their mountains of data have a good chance of increasing their competitiveness and earnings through new business models, more efficient processes and optimally coordinated customer services.
