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AI Transformation within the German Economy – more cultural than technological barriers?

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In an increasingly data- and AI-driven world, companies must be able to react quickly to large amounts of data in order to remain competitive. The question of support from AI is therefore of great importance in the company and requires a systematic approach.

Since we do not have an industry nor a use case focus, we as a company and also as AI consultants are in a situation that allows us to talk to various industries and stakeholders on a daily basis. As different as the use cases are (ranging from  text mining and imaging classification for customer reviews to optimizing logistic and supply chain processes sizes or analyzing customer behavior), we have made an interesting observation: We found that one key challenges companies face is  less  the technical infrastructure setup and more in the interdisciplinary nature of the transformation processes, addressing new challenges in the life cycle of learning systems, and trust-building communication, lack of competencies and value orientation. (We already posted an article on the fear for change and the importance of cultural transformation here)

According to a recent survey (shorturl.at/nzHL0), companies are making steady progress in adopting AI initiatives. 77.8% of companies report using AI capabilities, up from 65.8% the year before; only 4.1% say they don’t use AI applications.

Let’s dig deeper why the transformation is rather handicapped due to non technical reasons:

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1. Lack of competencies

Successful AI transformation within an organization requires a combination of three skills:

  1. a team with knowledge of artificial intelligence;
  2. business people believing in the potential and with a talent for good internal advertisement;
  3. technical engineers who can manage & process a huge amount of data.

 

In order to deploy intelligent AI systems at scale, most companies need to find technical talent, develop skills and/or find third parties. Putting together the perfect team is no easy task. Especially if you already have an established role system for existing employees in the company and need to integrate AI projects into it.

A Gartner study supports this point, revealing that of the companies that decide to launch AI projects, only 53% move from prototyping to adoption.

Initially, you may need to define new roles, recruit staff, or upskill the existing ones. Also, due to the complex current skills shortage, finding artificial intelligence experts is complicated, so it may take some time.

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2. Traditional mindset

New technologies require significant changes in business processes, which in some cases can initially create concerns and fears.

It cannot be denied that the world of work will be changed significantly by AI technologies in the future. However, the aim is not to make employees superfluous, but to support employees and relieve them of routine tasks. It is empathy, cognitive thinking and emotional intelligence that make humans superior to robots.

AI aims to reduce the effort involved in repetitive tasks, thereby complementing humans, not eliminating them. It’s crucial to understand this and promote this idea among employees. Without this understanding and acceptance of the team, introducing AI technologies is almost impossible.

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3. Fear of new technologies

New technologies often come with a high level of confusion and the necessity to step out of the comfort zone. This is something people are naturally resisting in the first impulse. Following the aforementioned steps to take, we have observed that through making new technologies comprehensible and through explaining the logic behind them, this fear can be overcome. Also through a close collaboration and integration of people that in the end are supposed to work with these technologies trust can be established up to a point where they are not seen as an opponent but rather as an aid or assistance.

All in all, Empathy is key to handle cultural barriers. A company can have a perfectly well functioning AI algorithm in place but if it is not used by the people whom it is supposed to help then the technology itself loses its raison d’être. 

What do you think about this topic? Feel free to comment below! 

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