What decision-makers should do nowHow generative AI is revolutionizing digitalization
There is currently a spirit of optimism in many SMEs: Generative AI (GenAI) is seen as a game changer in digital transformation. However, as is so often the case, technology alone is no guarantee of success – the right approach is needed.
In order to exploit the full potential of generative AI, decision-makers in their companies need to develop a clear strategy. The first step is to identify the specific areas of application in which GenAI can offer the greatest added value. These include the automation of processes, the improvement of customer experience and the development of innovative products and services. An interdisciplinary approach that brings together IT experts, specialist departments and managers is essential in order to question existing structures and open up new opportunities. This is the only way for companies to ensure that they not only keep pace with technology, but also actively use it to strengthen their competitive position.
The hard truth:Why many AI projects fail
According to Forrester (2025), many GenAI initiatives fail because companies underestimate how much work is required in advance. Data quality, process integration and change management are the most common stumbling blocks. The challenges of linking existing systems with new AI solutions are particularly great in the mechanical engineering, automotive and chemical industries.
In order to master the challenges, it is crucial to promote a culture of innovation and agility within the company. This means investing not only in technologies, but also in employee training. Training courses that provide a deep understanding of generative AI and its possible applications are essential. By taking a structured approach, they can not only minimize risks, but also gain valuable insights that can be used for future initiatives. This creates a dynamic process that enables companies to continuously adapt and evolve.
- Ensure data quality : AI is only as good as the data it uses. Companies should develop clear data strategies in advance and clean up outdated or unstructured data.
- Plan process integration : Before implementing GenAI, CIOs and supply chain managers should check which processes will benefit from it. The aim is to achieve seamless integration without media disruptions.
- Plan for change management: Managers must involve employees at an early stage and offer training. Resistance can be reduced through transparent communication and tangible examples of success.
The key to success lies in the run-up
In order to successfully implement generative AI, it is crucial to take a step-by-step approach. Entrepreneurs should start with pilot projects to not only test technological feasibility, but also to encourage employee engagement. These projects can act as learning labs where teams can experiment and gain valuable experience. The knowledge gained from these tests enables the gradual scaling of AI applications throughout the company. It is important to incorporate regular feedback loops in order to make adjustments and identify challenges at an early stage. This promotes an agile development culture in which innovation is not only expected, but also actively driven forward. In this dynamic environment, you not only remain flexible, but can also react to market changes at an early stage and make strategic decisions based on data.
Generative AI can leverage efficiency potential, drive innovation and create competitive advantages. Decision-makers who are not afraid of the “hard work” will reap the rewards in the end – and F&P is at your side as an experienced partner.
