How Businesses Can Benefit from Artificial Intelligence

You would be hard pressed to find another topic as widely discussed as artificial intelligence. Many scholars are calling it the most important technological advancement of the 21st century thus far. The release of the ChatGPT chat bot at the end of 2022 allowed the greater public to experience the impressive abilities of AI in action with their own eyes. Even at that time, most people were already familiar with different AI applications such as voice-enabled virtual assistants like Apple's Siri or advanced driver-assistance systems in modern cars. But the rapid development and new uses that have resulted from it, such as text and image generation, were and still are astonishing.

Unlike classic software that follows man-made rules and algorithms, AI learns by analyzing data. This makes it capable of independently recognising patterns and making decisions, without needing to be explicitly programmed to do so. With the right training, AI models are able to adapt to new and changing conditions and improve with time – given they're fed high-quality, correct data. This effect can be observed in image generation tools such as Midjourney which delivers even more accurate and sophisticated results with each new version.

For companies, the important questions are which applications should be converted to artificial intelligence and what do they want to achieve with it? "We identify five different fundamental capabilities of AI: sensing, analysing, language comprehension, content generation, and optimization procedures", adds Andreas Liebl. Sensory AI is based on information from cameras, microphones, or sensors. It is used, for example, in quality assurance for production processes, or in autonomously driving vehicles. On the contrary, analytic AI is able to make sales and pricing predictions or predictively plan production and logistics processes, as well as maintenance intervals.

Currently, generative AI is causing quite the fuss. These are systems that independently generate content according to the user's input. "Here, we are already implementing RAG-based models for companies. RAG stands for Retrieval Augmented Generation," explains Liebl. "These are language models that analyse different information from internal data and databases that they have access to. This can help users to read handbooks, analyse contracts, or compile large amounts of customer data, for instance." Even chat bots, which independently answer customer questions on company websites, belong to this category.

The next step in development for artificial intelligence, according to Andreas Liebl, is what is called agent-based AI. "These systems, with the help of machine learning and language processing, will be able to completely automate even complex work steps," says the expert. In the future, this technology could autonomously manage entire supply chains, optimise processes in real time, and react to unexpected disruptions in a targeted manner. These types of models can even be used in development to independently write the code for new software. "This technology is still in the early stages of development," according to Liebl. "But it will soon have the potential to make the most diverse applications many times more efficient."

Increased productivity, fewer errors, lower costs, and more flexibility are all possibilities that AI promises to deliver for companies. Liebl knows that it is still, however, not guaranteed that companies will be able to immediately benefit from AI. "I like to compare it to a marathon. Just because I buy the best running shoes, that doesn't mean that I can immediately run the entire distance. I need to start small and systematically improve. It's exactly the same with AI. It's not enough to simply buy into an application. Instead, companies should view AI as a competency that needs to be developed, including the necessary culture, data infrastructure, and governance. Only then is a company ready to implement this technology in a meaningful way."