Until now, artificial intelligence and machine learning have only been dreams of the future for many companies. But in 2022, the democratization of these important technologies will advance.
In many areas, artificial intelligence and especially the subfield of machine learning (ML) have become indispensable helpers. The amount of data available for AI learning divides the AI world into two: Platform giants collect unimaginably large amounts of data and use it to feed generalized AI methods available for generalized use cases. However, companies can only use these generalized models to a limited extent in the specific context of use. For optimal adjustment, they must train the artificial intelligence with the real data, which is only available in small quantities, and with regard to the respective, usually very specific context. Which three decisive developments in AI and ML will shape the year 2022.
1. Artificial intelligence: more focus on small data and wide data
For a long time, Big Data was mostly indispensable when it came to training artificial intelligence. The problem, however, is that in practice only a few companies and developers have access to sufficient amounts of training data. As a result, much of the business community is largely excluded from the technologies of tomorrow. New trends such as Small and Wide Data are therefore just in time to make AI and ML accessible to smaller companies.
Small Data approaches aim to extract value from smaller data sets with machine learning methods optimized for them using new analysis techniques. Wide Data is about creating synergies from a wide range of different data sources and types to improve the context for AI applications. With these approaches, companies are able to leverage their own treasure trove of data effectively and profitably. A study by the market research company Gartner shows just how interesting the new approaches are: according to this study, around 70 percent of all companies will shift their focus from Big Data to Small and Wide Data by 2025.
2. Intelligent document processing on the rise
The intelligent analysis of documents enables completely new working methods, as companies can digitize and partially or completely automate processes. In this way, processes can be optimized and implemented much more efficiently. Public authorities and large companies, in particular, have vast amounts of data, and new data is added every day. Often, several employees are entrusted with filtering the relevant information from documents that are required for further processing. This takes a lot of time, and the human factor makes for comparatively high susceptibility to errors. Intelligent Document Processing (IDP), i.e. the use of AI-based software for processing documents, is becoming increasingly important and at the same time enables the automation of workflows.
With IDP, companies and government agencies can automate their front- and back-office processes. In particular, application reviews, order acceptance, and updating customer and payment data are prominent application areas for this technology. In addition, IDP software helps with regulatory compliance or product tracking via supply chain systems in retail. Ultimately, the application areas include all text-based work processes.
3. Advances in conversational AI.
Anthropomorphism, the humanization of technology, has always been a major theme in the field of artificial intelligence. At the latest with Siri on the iPhone and Alexa on the smart TV, this phenomenon has become established in everyday life. Experts call these smart, AI-based voice assistants and other dialog systems conversational AI. They will become even more important in 2022.