AI in Business: A Guideline for Managers

The revolution starts now! The transformation of the economy and society through AI is in full swing. From advertisement copy, videos, and images generated at the click of a button to the automated monitoring of machines and tools to prevent bank and insurance fraud. There are countless examples of AI use in corporate business. As anyone who has ever dealt with a stammering chatbot on a customer portal will gladly confirm, many such applications are still in need of refinement or hardly provide any benefit (yet). But that will (have to) change soon!

Artificial Intelligence in Business: It’s Not About the If, It’s About the How

The outcome is clear: AI will prompt many industries to reinvent themselves, make work processes leaner or even redundant, increase productivity, and handle administrative tasks. This is a reason for hope but also for anxiety. Just think of data protection, ethics, and the future of many jobs.

Business leaders no longer think about whether they should use AI – this question has long been answered – the question is when and how solutions can be implemented. ChatGPT, the AI-driven language model from US company OpenAI, has thrown a spotlight on the use of AI in business. AI has long been used in many industries, for example for personalized product suggestions, image processing or medical diagnostics. But it is ChatGPT’s ability to write coherent texts and sound like a real person, that must be lauded for making the public aware of how far AI development has advanced.

How Can Businesses Effectively Leverage the Benefits of AI?

But how can businesses respond to the development of AI? “We believe the best way to approach this is not to view it as a competition between humans and machines but to see AI as a tool that can provide valuable services to people.” says Konrad Holleis, who, together with his team, has developed the compact AI Transforming Business program at the WU Executive Academy. The target group are employees and middle managers of small and medium-sized companies looking to integrate AI into their business processes.

AI expert Amir Tabakovic is among the program’s lecturers. The founder of Experiens AI, a consulting company advising clients on questions related to AI and data protection, has worked in the fields of machine learning and artificial intelligence since 2012 and has, among other topics, explored how to monetize data in digital banking. “Currently, two aspects are particularly relevant when we are looking at AI. We have to think about, for one thing, how to translate business problems into digital data problems. And for another, how businesses can use AI technologies effectively to tackle these challenges,” Amir Tabakovic explains. “And it’s exactly this expertise that participants acquire in our new program at the WU Executive Academy.”

Top 10: FAQs on the Implementation of AI in Businesses

Executives are now called upon to set the course for the successful implementation of AI tools in their companies. The following questions are of central importance to them in connection with AI:

1. What Is ChatGPT Actually Capable of?

Chatbots such as ChatGPT help people use AI in various fields of application. This can be analyzing or summarizing texts or coming up with precise answers to questions. The application of ChatGPT is based on Generative AI, i.e., systems that create new content. ChatGPT is by far not the only or most important AI application. In fact, viewing it as the be-all and end-all of AI can lead users astray, Amir Tabakovic warns. AI applications with the largest economic potential frequently do not rely on Generative AI but classic AI methods, which are based on training applications on an organization’s own data.

2. What is Important for AI Implementation in Businesses?

When used in real business practice, the precision and reliability of AI applications are often key. This is, e.g., the case for financial services providers using AI to assess a client’s credit rating or spot fraud attempts. But not every AI technology is equally suitable for every task. While Generative AI offers valuable support in many contexts, it is not sufficient for crucial tasks such as the question of whether customers should be granted a loan. “In such use cases, we still cannot do without the classic AI methods,” Konrad Holleis states.

3. Will AI Introduce a Paradigm Shift in Business?

“Artificial intelligence is a transformative force, going far beyond the changes brought about by the internet and e-mail a long time ago,” Amir Tabakovic says. This is the case because AI is not just about communication and digital networks. It has the potential to revolutionize almost every industry and task currently completed by humans.

For example, in the engineering field, this could mean that AI might be used to provide precise forecasts on when certain components will need to be exchanged. AI can also be used to optimize construction planning, proposing the most efficient sequence of events and resource allocation based on real-time data and prognostic analyses.

4. Who’ll Call the Shots in the End: Human or Machine?

For Konrad Holleis, it’s a done deal. If human decision-making is involved, AI will play a role in this field in the future. Whether that means full automation or the use of AI to support human staff members will largely depend on the specific context. “We are already able to fully automate many tasks today, but there are some that depend on human discernment.” This delineation between automation and human decision-making will gradually be pushed towards automation. This will particularly concern industries such as financial services and IT, both of which are highly suitable for automation and enhancing existing services through AI already.

5. Which AI Applications Are Already Popular with Businesses?

The use of AI in businesses, for example, in the form of chatbots, is already widespread and usually works smoothly. However, there are also cases where AI technology is not implemented optimally, which can lead to problems. Just one example: an airline was held liable because a customer received poor advice due to the company’s own chatbot. “Today, it’s not enough to just use a disclaimer excluding any kind of liability and try to shun responsibility this way,” Amir Tabakovic warns.

Speed can, in fact, kill. In the past, AI projects were meticulously prepared, with much care going into the preparation of historic data. Generative AI technologies don’t need to be fed your own data as much to produce acceptable outcomes, but they pose challenges regarding control and reliability. This means that in later stages of AI development projects, a lot of time and effort must be invested to ensure that the final version meets high quality standards.

6. What Added Value Does AI Offer Businesses?

“AI can accelerate capabilities and should be viewed as ‘extended human intelligence,” Konrad Holleis advocates. “If you own high-quality data, it can form the basis for effective in-house AI solutions that can replace rigid, human-made rules,” Amir Tabakovic adds. What managers need to do now is adapt corporate culture to meet new requirements. “They have to make sure that the implemented AI solutions comply with the applicable legal regulations and also satisfy ethical standards.”

7. What Is the Role of Governance in AI Systems?

There is absolutely no way around AI governance when AI is used, and that’s not only due to legal stipulations such as the AI Act in the EU.

Amir Tabakovic outlines some questions that managers must answer in connection with the topic of "AI governance":

• Who is responsible for monitoring and controlling AI systems?
• What is done to ensure compliance with ethics guidelines and legal stipulations?
• How transparent are decision-making processes based on AI, and how can they be traced?
• Which measures are taken to ensure a high quality of data and the security of the AI systems used?
• What kind of risks are there in terms of undesirable consequences arising from users’ interactions with AI systems, and how are these risks minimized?
• Which measures are taken to prevent AI systems from exacerbating existing biases?

8. What Should Be the First Steps when Using AI in Business?

Konrad Holleis’ advice is to start out with small projects to minimize risks (particularly those related to data protection) while still being able to gain a wealth of experience. Acknowledging that no AI solution is perfect also goes a long way. Against this backdrop, adopters should think about which goals they want to reach through AI use. And also which costs could be incurred for the company in the event the AI application takes a wrong turn.

9. What Opportunities Do SMEs Have to Make Profitable Use of Artificial Intelligence?

The good news for small businesses: there are opportunities to use AI that large companies do not enjoy. Small businesses usually only have limited data and fewer experts to develop their own AI solutions. Nevertheless, they should consider using artificial intelligence. They can put AI to good use by relying on applications developed by external service providers or software partners. “For this, they must be able to adjust AI solutions to their needs and integrate them into their systems,” Amir Tabakovic explains.

Companies can, for example, add AI functionalities to their existing CRM solutions. In this way they draw conclusions about when which customer needs to be addressed with which message. Even freelancers working by themselves can use AI. “The high degree of automation made possible by AI can increase their productivity to match a small company with a handful of employees in some cases.”

10. What Kind of Employees Do I Need to Make My Business Fit for AI?

“The communication between data science teams and various business segments is often quite challenging in daily business practice” Amir Tabakovic shares. The newly created role of an analytical translator can ensure that technical teams and the various business units speak the same language and are thus able to communicate effectively. “This is also the reason why our new program aims at training analytical translators, who will then be able to staff these essential positions at the interface between AI and other business segments,” Konrad Holleis concludes.

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