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Raphael ThysAt the beginning of every year, large technology companies and research firms analyze the current trends and forecast further development areas and prospects over the next 5–10 years.
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One of the areas Gartner suggests exploring in 2022 is Generative AI. As a Machine Learning method, Generative AI creates original content from the already existing patterns the system has spotted before. Hence, it is a promising solution that allows covering many tasks connected with text, audio, video, images, etc.
This technology might be pretty handy when it comes to creating new software codes, targeting advertising, image-to-image translation, and drug development. Another interesting point is that Gartner expects Generative AI to account for 10% of all the data produced by 2025, over 10 times greater than today.
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The demanding nature of the decision-making makes it one of the most challenging areas of company operations and a significant source of competitive advantage, which would be further embraced by 1/3 of large organizations with the help of Decision Intelligence (DI) in the next 2 years, according to Gartner.
Traditional business decision-making is a complex procedure that requires a long analytical process that usually engages many departments and operations. Apart from the complexity of its system, traditional decision-making is becoming less effective in a modern business climate.
The basic premise is that our decisions are based on our understanding of how actions contribute to outcomes. Decision intelligence analyzes this chain of cause and effect and represents this chain in a visual language called decision modeling. By augmenting traditional decision-making science with AI-powered technology, social and data sciences, decision intelligence can transform business analytics into a more efficient system.
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The No-Code and Low-Code AI applications will become more and more popular and more accessible to non-experts and the ‘entire knowledge workforce’. In fact, the IT company HPE (Hewlett Packard Enterprise) believes that no-code and low-code platforms mark the rise of the citizen developer.
Low-code/no-code platforms are not just meant to speed app development within IT. Proponents say it democratizes technology across the enterprise and enables employees, sometimes referred to as citizen developers, to build code to solve their own business challenges especially at a time when IT professionals are in short supply.