Person in Neon-beleuchteter Umgebung

04.01.2022 | News These three trends will shape the AI year 2022

Until now, artificial intelligence and machine learning were only a distant vision of the future for many companies. But in 2022, the democratization of these technologies will move forward, predicts enterprise search and AI specialist IntraFind.

In many areas, artificial intelligence and especially the subfield of machine learning (ML) have become important and indispensable helpers. The amount of data available for AI learning divides the AI world into two subsectors: Platform giants are collecting unimaginable amounts of data and using it to feed generally available 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 AI with the real data, which is only available in small quantities, and with regard to the respective, usually very specific context. IntraFind predicts how the situation around AI will develop in the coming year based on the following three trend analyses.

1. 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 techniques optimized for them using new analytics techniques. Wide Data is about creating synergies from a wide range of different data sources and types to improve 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 and consulting 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

Intelligent document analysis enables completely new working methods, as companies can digitize and partially or fully 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 a 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 as well as 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 areas of application include all text-based work processes.

3. Advances in Conversational AI

Anthropomorphism, the humanization of technology, has always been a major topic in the field of artificial intelligence. At the latest with Siri on the iPhone and Alexa on the TV, this phenomenon has crept into everyday life. Experts call these smart, AI-based voice assistants and other dialog systems conversational AI. They will become even more important in 2022.

This technology is a real asset, especially in customer service. In order for chatbots and question answering systems as virtual assistants to be of real help to customers and thus also to companies, a number of challenges must be overcome. The AI must correctly interpret, "understand," and provide answers to customer queries, as well as rely on a human expert as infrequently as possible. To make this experience as natural as possible, Natural Language Processing (NLP) is used.

The better the conversational AI system works, the more customer inquiries companies can process automatically. This not only saves employee resources, but also makes customers less dependent on business hours.

"Artificial intelligence and machine learning will increasingly arrive at companies in 2022," predicts Franz Kögl, CEO at IntraFind. "New methods are democratizing technology and enabling more and more companies to reduce costs through automation. Customers will also benefit from this development, because intelligent searches, chatbots and voice assistants also improve the user experience."

Related Articles


AI is shaping the future of the data economy

Data has long been traded as a valuable economic asset; from a company's point of view, it is the driver of innovation and growth. But it is only with the help of artificial intelligence that the increasing mountains of data can be used profitably. Companies of all sizes need to raise their awareness of the possibilities of intelligent data use, believes Franz Kögl, CEO of IntraFind.
Read article

AI for everyone? Transfer learning is a first step

Transfer learning is often hailed as a miracle cure for bringing artificial intelligence to market. The learning method uses already trained models as a starting point and can thus deliver results faster. As a result, transfer learning has the potential to accelerate AI deployment in companies, says Franz Kögl, CEO of IntraFind.
Read article