SAP balance of innovation and risk management
Over the past two decades, advancing digitalization has already made a significant contribution to automating manual and repetitive tasks. For example, AI can independently recognize patterns and trends in enormous amounts of data and make these findings available to specialists for support.
In industry, for example, predictive maintenance is a field of application for AI. If a machine works with predictive maintenance technology, it can inform specialists before a fault occurs that a certain component is worn and will soon need to be replaced. In the insurance industry, the use of AI, particularly in the field of natural language processing (NLP), makes it possible to analyze patterns and trends in data and compare documents at content level, for example. These activities can now be supported by machines so that complex documents can be automatically analyzed and compared at a semantic level in order to significantly reduce effort and errors.
In the area of customer communication, large language models (LLMs) offer the possibility of a highly automated and at the same time hyper-personalized customer approach. In chats, well-trained LLMs can respond even more individually to the customer. Personalized emails, for example, can also be made even more individual and needs-oriented using SAP CDP and SAP Emarsys in conjunction with ChatGPT.
With the emergence of Large Language Models, we are experiencing a disruption of previous developments. ChatGPT and other generative LLMs are showing highly exciting and impressive results in the field of text generation and other creative tasks. Not only can existing processes be optimized, but completely new areas and activities can also be automated or decisively supported.
Companies that make data-driven decisions and implement innovative applications can gain a significant competitive advantage. However, these advances are accompanied by ethical challenges, particularly in the area of data protection and fairness of AI applications. For example, AI hallucinations are a well-known phenomenon when using generative language models such as ChatGPT. In addition, new generative AI applications such as ChatGPT also raise unresolved challenges with regard to data protection and privacy rights and compliance with the General Data Protection Regulation (GDPR), which are currently being examined by the European data protection supervisory authorities.
AI as an intelligence amplifier
After machines as “power amplifiers” for humans, AI is now an “intelligence amplifier”. AI applications therefore provide support, but the use of AI is limited when it comes to business-critical decisions, be it with regard to questions about promotions, accounting and controlling processes or claims settlement in the insurance sector. In such critical or sensitive use cases, decisions cannot be left to AI systems alone; human experience and expertise are still required.
The integration of AI not only marks a technological advance, but also an ethical obligation. This balance of innovation and risk management is key to the successful integration of LLMs into the digital transformation. This technology not only offers opportunities, but also requires a strategic approach and an examination of ethical and regulatory issues in order to maximize its potential.
