Everyone is talking about GenAI, everywhere you read about the benefits that the new technologies can bring for companies. Where do you see the greatest opportunities?

I see the greatest advantages above all in the wider availability of GenAI, which is no longer reserved for experts alone, but also enables less tech-savvy users to develop innovative solutions. In addition, GenAI contributes significantly to increasing process efficiency and supports decision-making processes through real-time analysis and actionable insights. Finally, GenAI enables tasks to be completed faster and to a higher quality, giving companies a decisive competitive advantage. 

What is the actual implementation status in companies?Are there any industries or areas that you perceive as pioneers?

The implementation status of GenAI varies greatly between companies. Many need time to fully understand the topic. Some are starting pilot projects, but large-scale use is often still lacking. Tech companies are more open due to their affinity with technology, while there is great interest in the healthcare and automotive sectors, but there is often a lack of maturity. Automotive companies, for example, are currently investing heavily in advancing GenAI. In the healthcare sector, on the other hand, the data basis for comprehensive use is often still lacking, but there are areas, such as drug research, in which GenAI can already be used to good effect. One problem is that GenAI projects are often driven by the IT department and are also perceived as IT projects. However, the specialist departments, who know the application areas best, should be the driving force. Experience shows that projects are successful when the specialist departments take responsibility.

What are the biggest challenges?

The “last mile” – i.e. the transition from the pilot phase to day-to-day business – is crucial. The biggest challenges in the introduction of GenAI lie in scaling and integration into day-to-day business. Without this and the measurement of benefits, the use of GenAI will remain ineffective. A series of small, juxtaposed use cases will ultimately not create any significant impact. It makes more sense to focus on use cases that are scalable, i.e. that can be rolled out quickly throughout the company if successful. Companies often pay too little attention to these aspects and view them as purely technological processes. Managing expectations is also a challenge: there are two extreme poles between which companies fluctuate – either a sense of fear or the exaggerated expectation that AI can solve everything.

What advice would you give to companies that are starting from scratch?

They should start gaining experience immediately so that they don’t fall behind. It is crucial to take a comprehensive look at the topic and consider the potential of GenAI across all areas. Both the technology and what is feasible should be explored. A dual approach is advisable: take an exploratory approach and identify specific projects at the same time. Companies should first examine a broad catalog of topics and then concentrate on specific focal points. In doing so, companies should tackle two to three larger projects in order to understand what concrete benefits GenAI brings in the respective use case. The learning rate is crucial in order to be able to try things out as a team and find out what is possible.

Initially, multipliers should be involved across departments in order to involve as many employees as possible and gain their approval. Transparency within the company is crucial for the success and broad acceptance of “Colleague GenAI”.

What other factors are important for GenAI to become a real competitive advantage?

To turn GenAI into a real competitive advantage, companies should focus on larger, strategic issues. Efficiency and process optimization are important and must be done in order not to fall behind. But true game changers are innovative projects that are difficult to imitate and therefore superior to the competition. These differ depending on the industry. It is also important to find and retain experts and build up relevant skills in the company over the long term. Technology is becoming increasingly readily available, so companies need to build more than the standard offering. It is crucial to know which technologies should be developed internally and which can be sourced externally. Investment should be targeted where it will bring the most benefit.

What is your vision for the future? Where will companies be in 5 years’ time and what will be important in the future?

Given the rapid pace of technological development, it is difficult to predict exactly where companies will be in five years’ time. Nevertheless, I expect that we will reach a level where AI has human-like capabilities. AI employees could take on tasks independently and thus significantly change the labor market and regional structures.

In areas where a high level of empathy and human relationships are important, people will continue to work. However, where it is mainly about “doing”, AI co-workers will take over these tasks. This development should be positive, as it counteracts the shortage of skilled workers and supports companies: overall, the journey is moving towards “AI colleagues” who complement the workforce and relieve them of routine tasks.