Challenges in the implementation of AI
As promising as AI is for corporate communications, its introduction brings with it numerous challenges. One of the biggest hurdles is to use the technology in a targeted and strategic way rather than just testing it selectively. Many companies are already experimenting with generative AI, but the transition to systematic use is proving difficult: according to the ZHAW Trend Study Switzerland 2024, 61 per cent of communication departments have so far used AI on a trial basis, while only 33 per cent are pursuing a broader application. Nevertheless, only 6 per cent have completely abandoned the use of GenAI.
A key problem is quality assurance: without the appropriate domain knowledge and human control, there is a risk that AI-generated content will appear generic or not match the brand identity. At the same time, data protection and ethical issues raise major uncertainties. According to a study by the Federal Statistical Office (2023), a lack of knowledge (72%), an unclear legal framework (51%) and data protection concerns (48%) are the most common reasons why companies are not yet making extensive use of AI.
In discussions with customers and in our webinars, we also repeatedly hear from participants that many companies are struggling to take the next step. Although initial AI tools have been tested, there is often a lack of a clear strategy and prioritisation of use cases. Integration into existing processes is particularly challenging.
Our recommendation is therefore: companies that want to implement AI in a targeted manner should start with a structured approach. Identifying relevant use cases, training employees and continuous optimisation are essential in order to exploit the full potential of AI.