Artificial Intelligence in Business: Trends, Opportunities, and Challenges

For companies still questioning whether AI is an option for them, now is the time to act. Anyone who immediately answers “yes” can still jump on board.

Artificial intelligence (AI) is becoming increasingly common in business. Businesses are increasingly exploring practical uses of AI. The trend is towards evidence- and data-driven automated decisions to optimise internal processes and external interactions. AI is thus becoming a business tool and is developing from a complex insider asset for an exclusive group of experts into a valuable tool for operational use. Pattern recognition in colossal data sets is becoming common knowledge and, when used correctly, leads to increased agility and improved business outcomes.

Established AI Applications and Emerging Trends

The growing use of AI has encouraged businesses to explore applications across different areas, from customer service to knowledge management. The big question now is what companies make of it. In addition to these classic areas, the AI landscape remains colourful and diverse. Beyond these established applications, businesses can use AI across a wide range of functions.

Edge AI is primarily responsible for this great potential, which will significantly change business processes. Edge AI enables intelligent systems and mobile devices previously dependent on central IT resources to carry out AI-based operations largely autonomously. Data collection, processing, and analysis, and the resulting action control, occur directly on site. This new capability and the peer-to-peer networking of such intelligent and self-learning peripheral systems create new business process architectures and opportunities.

AI Ethics, Regulation, and Responsible Use

Recently, there has been a lot of talk about ethical responsibility in connection with AI. The results of these discussions are initiatives such as the EU’s Coordinated Plan on Artificial Intelligence, the National AI Strategy in Great Britain, and the Federal Government’s Artificial Intelligence Strategy. They are intended to ensure that critical AI applications such as facial recognition or behavioural monitoring in public spaces are more strictly regulated. The EU AI Act establishes a risk-based framework for AI and includes requirements addressing areas such as high-risk systems, transparency, human oversight, and cybersecurity. However, ethics does not play an elementary role in these security or socially critical scenarios. It also applies, for example, to AI applications that have so far provided distorted results due to non-bias-free algorithms, for instance, in decision support systems.

One way to address these risks is to use bias testing and regular reviews to identify potentially discriminatory results. The NIST AI Risk Management Framework provides a voluntary framework for organisations to manage risks associated with AI and incorporate trustworthiness considerations into the design, development, use, and evaluation of AI systems. In general, the trend is towards stricter requirements, with standardized processes and transparent documentation that prevent both the misuse of AI and its negligent use in application development. AI can also support cybersecurity teams by helping them identify unusual patterns and potential threats. This creates space for more secure AI application fields and thus broader access to AI-supported services.

AI Is Becoming More Capable of Human-Like Interaction

Another feature of current AI supports this development: it is becoming more human. So far, AI has primarily been used to take over intellectual functions. AI systems are increasingly being used for tasks that involve generating content, understanding language, and supporting human interactions. For companies, the shift means the opportunity to better understand their customers and partners at this level and to be able to interact with them in a targeted manner. Transaction and service quality benefits from these developments. At the same time, the possible uses of AI are expanding, for example, in socially essential fields such as healthcare and nursing. There, AI can support routine tasks such as documentation, alarm management, and inventory forecasting.

Beyond these “hidden” uses in the backend, AI-supported robots can also help fulfill one of the most critical social components in care and take over at least part of the human communication and interaction on the front. With the help of AI, care robots can imitate human gestures, facial expressions, and articulation. This can allow care robots to support certain forms of communication and interaction, although they are not a replacement for human care and emotional support.

These examples show how AI can support a wide range of tasks beyond traditional business operations. Artificial intelligence helps optimize customer interactions and improve social systems in practice.

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