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More and more companies are recognizing that AI is important to their future and that it can help to increase their revenue significantly. The PwC report “Sizing the Prize” estimates that Artificial Intelligence will generate $ 15.7 trillion in additional revenue by 2030 for businesses across all industries.


One would assume that companies would make the investment in development of AI technologies a top priority. However, the implementation is still slow in many companies.


Today, we’d like to look at the most common challenges that companies are facing when implementing AI and show you possible solutions.



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1) Anti-innovation culture


The corporate culture is a crucial factor when it comes to the success of establishing a new technology. After all, the introduction of technologies inevitably means a change in the company. In most cases, this creates concerns and fears such as AI making a lot of human work redundant.


There is no doubt, that the future of work will be heavily influenced by AI technologies. However, it’s not about making people dispensable, but to improve processes and to take over repetitive tasks.


These changes must be addressed and understood by all employees. Without this understanding and acceptance of the whole team, the introduction of AI technologies is almost impossible.



Deadlocked decision-making processes can also become an obstacle. Often, only projects that promise a clear ROI in advance can be implemented. For many AI technologies, however, it is necessary to find out by experimenting what the potential use cases are and how they can be implemented. Unfortunately, there is no room for iterative approaches in many companies. It is important to overthink established processes and make space for more iterative approaches as well.



2) Lack of expertise


Ideally, AI processes should be mostly automated, but training the algorithms and interpreting the results requires experts who are familiar with these topics. Furthermore, the issue of security also raises concerns among many companies. Especially since the new data protection guidelines came into force, the topic of data security has become even more important for many companies.


No matter whether it is about setting up AI processes, data analysis or security, companies often lack the necessary knowledge. Especially in the field of AI, the required knowledge is changing at a rapid pace. Therefore, it is necessary that employees get the chance to learn these new skills continuously.



3) Lack of imagination


Although the subject of AI is already extensively discussed, the discussions are usually so varied and superficial that it is difficult to derive concrete use cases from them.



In addition, AI is often seen more as a technological advancement rather than as a technology that can transform businesses from scratch. It is important to talk with the entire team about the topic and, if necessary, to offer suitable workshops to develop how it can be used within the company.


What can AI do and how can it be used for your business? These questions can best be answered together with your team. That way, employees will be involved in the decision-making process on AI topics directly and possible fears and uncertainties will be reduced.




4) Thin Data Basis


The foundation of all AI technologies is a solid database. Only if the necessary data is available AI can be used in a meaningful way. In many cases, however, data is collected that does not provide real value to the business.



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However, if the data has been collected, it can exist in many different systems, often without any connections. Another problem can be the IT infrastructure, for example, if you use outdated software that is incompatible with AI technologies.


In order to remove these obstacles, it is necessary to understand what data is needed, which data is already collected and in which systems it is available. Once you have gathered this information, you can initiate the necessary changes.



The use cases of voice assistants and chatbots are endless. Onlim is here to help you design and develop your very own solution that caters to your specific needs.


Stefan Rehm

Stefan Rehm

Key Account Manager

[email protected]


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4 Challenges Companies Should Be Ready For When Implementing AI In Their Processes