ARTIFICIAL INTELLIGENCE

AI Systems: How New Technology Is Changing IT Professions

AI systems will change the professional world and the fields of activity of the IT specialists themselves. AI will take over routine activities and even the programming of algorithms. Industry knowledge and consulting skills will be in demand in the future. This also has an impact on the training and further education of young professionals.

AI systems will change the professional world and the fields of activity of the IT specialists themselves. AI will take over routine activities and even the programming of algorithms.  Industry knowledge and consulting skills will be in demand in the future. This also has an impact on the training and further education of young professionals.

Artificial intelligence, or AI for short, is gaining greater public awareness in the corona pandemic. Not only did an artificial intelligence system, the Canadian health platform BlueDot, warn of viruses of unknown origin in the Wuhan area before the WHO was officially informed. Evaluations of lung recordings, tracking processes for the spread, or monitoring distances in the logistics area are just a few possible uses. The ideas and possible applications are incredibly diverse. Several research projects are currently ongoing in the area of ​​drug discovery alone.

AI Systems: Moving Into Everyday Life

The corona crisis can therefore prove to be a motor for the further development of artificial intelligence. The subject is, of course, not new. Learning algorithms have long since found their way into everyday life – in the form of navigation systems, voice assistants, or vacuum robots. Comfortable in daily life, they are much discussed, linked to the highest expectations, and feared as job killers. In any case, the time is ripe for applications of artificial intelligence. Because, unlike in the past, the storage and computing power required for this is now available. Enabling scalable storage capacities through cloud platforms and high processing speeds also makes AI economical for companies.

“Many potential users first think of process optimization, here the boundaries are often fluid between digitization and the use of artificial intelligence,”. Automation alone can replace many routine processes, repetitive and tiring activities for humans. However, AI can do much more: Through machine learning, the generation of knowledge from experience, the algorithms can deal with unknown data, find patterns, and independently derive actions. Chatbots, for example, which are increasingly used in customer service, get better and better over time with supported learning.

Deep Learning Enables Forecasts Based On Complex Relationships

Deep learning based on neural networks enables forecasts based on very complex relationships. Well-known applications can be found in the area of ​​predictive maintenance or in predicting customer behavior. A crucial aspect of AI comes into play: Uncovering previously unknown relationships lead to new insights and thus promises real added value.

But how can companies use artificial intelligence systems to add value? To recognize and use their potential, IT users need development and implementation services and comprehensive advice. Because the use of AI elements is not comparable to the introduction of new software, for example. Instead, very different technologies and approaches are summarized under the term artificial or artificial intelligence, also AI. The best known include speech and image recognition or data analysis. A Bitkom project on the periodic table of AI offers detailed information and an overview, But it also illustrates how complex this topic is.

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Knowledge Of AI Systems And Industry Knowledge Is Becoming More Critical

This results in a comprehensive spectrum of specializations and specialist knowledge for the developers and programmers of AI models. “IT consultants and business analysts will also need an appropriate background to familiarize potential users with the possibilities of artificial intelligence.

The next step is to jointly find specific use cases in the company and design a suitable model for them. Companies need support in analyzing the options and estimating the costs: What amounts of data are required, and is it available in sufficient quality? If not, how much effort would it take to prepare the data? How much time should be planned for “training” the chatbot? 

AI Systems: IT Knowledge Alone Is Not Enough

The AI ​​model must also fit the application. Sub-symbolic processes such as neural networks are compelling, they are suitable for image recognition, for example, but their decisions are not understandable for people. So when it comes to traceability and documentation, they would not be suitable. IT know-how alone is not enough, who has worked in the banking sector for many years, explains: “To provide competent advice and to be able to speak to users on an equal footing, IT specialists also need knowledge of the specifics Processes, the business environment and the legal requirements in the respective industry.”

At the same time, rule-based routine activities in the IT area will also be taken over by AI algorithms in the future.  Google Brain reported a corresponding success in 2017 with the development of speech recognition software using an AI system. IT experts will be best able to support companies on the subject of AI if they acquire background knowledge of the possibilities and AI systems, have consulting and problem-solving skills, and specific industry knowledge.

IT Young Talent Promotion: Future-Oriented Education And Training

However, specialists with this profile are likely to be rare. Companies are, therefore, primarily dependent on external support. Promoting young talent would often be the better alternative in the long term. Still, many companies lack the resources to train IT career starters or internal trainee programs.

The Digital Workforce Group has developed a holistic model to bring young professionals and companies together. Tailor-made support concepts and mentoring, project assignments, and internalization are the cornerstones. The personalized training is supplemented by offers of expert lectures and regular TechTalks. Workshops together with companies offer platforms for discussion and the exchange of experiences.

“AI is one of our main topics. With special project labs, we allow young IT talents to implement their developments, for example, with humanoid robots, and thus further develop their skills in the field of AI,”. After all, independent learning drives people and moves them forward – the template on which AI was developed in the first place. 

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