Artificial Intelligence: 3 Key Trends For 2022

So far, artificial intelligence and machine learning have only been a future dream for many companies. But in 2022, the democratisation, of these essential technologies will advance. Artificial intelligence and especially the sub-area of ​​machine learning (ML) have become indispensable helpers in many areas. The amounts of data available for training AI divide the AI ​​world into two areas: The platform giants collect unimaginably large amounts of data and feed them to generally available AI processes for generalised use cases.

However, companies can only use these generalised models in a specific context to a limited extent. For an optimal adjustment, they have to train the artificial intelligence with accurate Data that is only available in small quantities and concerning the respective, usually extraordinary context. Which three key developments in AI and ML will shape the year 2022.

Artificial Intelligence: More Focus On Small Data And Comprehensive Data

For a long time, big data was primarily indispensable for training artificial intelligence. However, the problem here is that in practice, only a few companies and developers have access to sufficient amounts of training data. The result: a large part of the economy is largely excluded from the technologies of tomorrow. New trends such as small and comprehensive data are therefore just right to make AI and ML accessible to smaller companies.

Small data approaches aim to create value from smaller amounts of data with machine learning methods optimised using new analysis techniques. Comprehensive 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 can use their data treasure effectively and profitably. A study by the market research company Gartner shows how attractive the new approaches are: According to this, around 70 percent of all companies will shift their focus from big data to small and comprehensive data by 2025.

Intelligent Document Processing On The Rise

The intelligent analysis of documents enables completely new working methods, as companies can digitise processes and partially or fully automate them. In this way, processes can be optimised and implemented much more efficiently. Authorities and large companies, in particular, have vast amounts of data, and new ones are added every day. Several employees are often tasked with filtering the relevant information from documents required for further processing. This takes a lot of time, and the human factor makes for a comparatively high error rate. 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 workflows to be automated.

With IDP, companies and government agencies can automate their front and back-office processes. Above all, application checks, order acceptance, and updating customer and payment data are prominent areas of application for this technology. In addition, IDP software helps with regulatory compliance or product tracking through retail supply chain systems. The areas of application ultimately include all text-based work processes.

Advances In Conversational AI

Anthropomorphism, the humanization of technology, has always been an essential topic in artificial intelligence. This phenomenon has established itself in everyday life at the latest with Siri on the iPhone and Alexa on the television. Experts call these intelligent, AI-based language assistants and other dialogue systems Conversational AI. In 2022, they will again gain importance.

This technology is a real benefit, especially in customer service. For chatbots and question-answering systems as virtual assistants to be of real help to customers and thus also to companies, several challenges need to be mastered. The AI ​​must correctly interpret, “understand,” and provide answers to customer inquiries and as little as possible resort to a human expert. Natural Language Processing (NLP) is used to make this experience realistic. The better the conversational AI system works, the more customer inquiries companies can process automatically. This saves employee resources and makes customers less dependent on business hours.

New Methods Democratise Artificial Intelligence

“Artificial intelligence and machine learning will increasingly reach companies in 2022. New methods are democratising technology and enabling more and more companies to reduce costs through automation. Customers also benefit from this development because intelligent searches, chatbots, and language assistants also improve the user experience”.

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