ASPIRING INNOVATION: THE IMPACT OF AI ON BUSINESS IN GERMANY

Stephan MAUER Managing Partner

www.mauer-wpg.com

In 2024, the business world is in a constant state of change, characterised by technological advances and societal transformation. Artificial intelligence (AI) will not only remain a key enabler of innovation, but will also play a significant role in supporting crucial issues such as corporate sustainability. AIis not only potentially revolutionising business processes, but also fulfilling an important part in overcoming future-oriented challenges. However, a critical examination of the potential risks and challenges associated with the use of AI is also essential for a comprehensive view.

Go further and know the limits

As the business world continues to evolve, AI has established itself as a key driver of innovation. In 2024, the importance of generative AI will continue to grow: generative AI is an advanced form of AI that is able to independently generate new data, content or information. Companies that implement a clear and convincing Generative AI Strategy position themselves as pioneers in their industry, as generative AI not only enables the automation of customer experiences, but also revolutionises internal business processes.

Companies can use intelligent automation to create personalised interactions, i.e. through chatbots in customer service or personalised recommendations on e-commerce platforms. However, the influence of generative AI extends far beyond customer-facing applications. Internally, it can optimise processes, from automated data processing to intelligent resource allocation.

For example, using AI-based automation can improve supply chain workflow, predict inventory levels and increase production efficiency.

Companies can also encounter difficulties when using AI, as the implementation of such systems is complex and can be particularly challenging for small companies with limited resources. In addition, relying solely on AI in business processes can pose a high risk, as there is the possibility of technical failures, security vulnerabilities or malfunctions. Companies must consider these aspects when implementing AI systems and develop strategies and guidelines to solve potential problems or avoid them in the first place.

AI as a part of the solution for the skills shortage

The shortage of skilled employees in Germany affects all sectors and is expected to increase further in the coming years. Especially the healthcare, industrial and construction sectors are facing serious challenges. The lack of qualified specialists in these sectors is leading to shortages in filling available positions and threatening the competitiveness of companies.

To counter this problem, companies are increasingly turning to AI, for example in the form of “skills management”. This approach combines targeted recruitment practices with increased training and aims to develop existing employees in a targeted manner. It not only creates an efficient solution to the skills shortage, but also promotes the continuous development of the workforce.

AI also offers the potential to automatise or optimise certain professional activities. For instance, it can support doctors in the healthcare sector by analysing image data and help generate a diagnosis or analyse data sets to speed up research processes. This redistribution of tasks can help to reduce the need for skilled labour and therefore contribute to counteracting the shortage of skilled workers. At the same time, it can increase efficiency in the affected sectors.

Support with reporting requirements on sustainability

In Europe, the first part of regulation requiring more companies to provide more detailed reporting on sustainability is enforced this year .AI is now proving to be an accomplice on the path to sustainability and the fulfilment of these reporting requirements.

Through advanced data analytics and machine learning, AI is enabling more accurate measurement of environmental impacts. Companies can use AI-based systems to optimise their supply chains, reduce resource consumption and minimise their environmental footprint. This also leads to economic benefits through efficiency gains.

With the increasing requirements for transparent reporting, particularly as a result of the Corporate Sustainability Reporting Directive (CSRD), the German Supply Chain Due Diligence Act (LkSG) and the future EU Corporate Sustainability Due Diligence Directive (CSDDD), companies are facing challenges. Some of the data required for comprehensive sustainability reporting is not available, which makes it difficult to create accurate and informative reports. In addition, a proper materiality assessment is time-consuming as it requires a precise assessment of which aspects are crucial for the company, its stakeholders and the environment. Furthermore, the inclusion of specific expertise, for example with regard to the impact on biodiversity, requires additional effort. Here, AI-supported systems come into play: They enable the precise aggregation of data and the automated analysis of business processes. For the materiality analysis it can make initial suggestions based on a company’s respective business activities as to which aspects of sustainability are most likely to have a significant impact. Thus, companies can not only extract relevant information, but also identify potential risks and opportunities that are material to their business practices.

The CSRD significantly expands the circle of companies affected by the reporting obligations, while the German LkSG sets out clear due diligence obligations to ensure compliance with human rights and environmental aspects in global supply chains. The forthcoming European Supply Chain Act CSDDD, will further increase the importance of these laws, as they will be binding throughout Europe. AI offers opportunities for improved compliance and the identification of relevant sustainability aspects in complex global supply chains. In addition, AI can help companies to continuously improve their reporting and respond flexibly to changes in legal requirements.

However, there are also critical aspects to consider when using AI in sustainability reporting. Data protection and data security play a central role, as companies process sensitive information. There is also a risk of bias in the algorithms if sufficiently diverse data sources are not included. These aspects emphasise the need to develop and implement AI-supported systems with a clear focus on ethical principles to ensure that these technologies are used transparently and responsibly.

The role of AI will continue to grow in the business world in 2024. It plays a crucial role in transforming business processes, mitigating the skills shortage and optimising sustainability reporting. However, ethical considerations and risks regarding the implementation of AI systems are also present, as there are concerns about algorithm bias, data privacy issues and the reliability of AI decisions. Nevertheless, companies that integrate AI responsibly and ethically have the opportunity to drive innovation and sustainability and position themselves for long-term success.