What stage have companies reached in using Generative AI?
The brand-new Lünendonk study in collaboration with KPS provides comprehensive insights.
According to the study*, 47% of surveyed CIOs already see Generative AI as highly relevant in 2024. Looking ahead to 2027, this number rises to 60%, with many anticipating a significant business impact, particularly in areas such as IT operations, document processing, and knowledge management. The study also thoroughly examines the risks associated with implementing Generative AI, emphasizing the importance of clear guidelines and responsible practices to prevent data breaches and security issues.
The Lünendonk study further explores the implementation strategies of the surveyed companies and provides a cross-industry comparison. It highlights that future competitiveness will largely depend on the ability to recognize and leverage the potential of Generative AI.
*The survey included 150 IT and business leaders from German-speaking companies and authorities. The surveyed industries include manufacturing, retail, energy sector, healthcare, automotive industry, banking, insurance, and the public sector. The examined companies consist of 12% medium-sized businesses (50-250 million euros in revenue), 50% upper mid-sized businesses (250 million to 1 billion euros in revenue), and 38% large enterprises (over 1 billion euros in revenue).
The results of the market analysis highlight the following key topics:
Generative AI: From Innovation to Market Maturity
Topics in Focus:
- Status of Generative AI: Many Experiments but High Potential
- The Danger of Shadow AI
- Impact of the EU AI Act
- Tools Used and Implementation Strategies
The State of Generative AI: Numerous Experiments with High Potential
Generative AI is already being applied across various fields, but for most companies, the technology remains in its early stages of adoption. Only three percent of surveyed companies have fully integrated Generative AI into their production processes, while 34% are still in the testing phase.
The most common areas of application include conceptual work (85%), data analysis and forecasting (80%), digital services (71%), and chatbots (68%). Companies anticipate significant potential for Generative AI in the coming years, particularly in external information research and in research and development.
The push for implementing Generative AI is primarily driven by IT departments, followed by management and marketing teams.
The Risk of Shadow AI
Unclear user rights assignments often give rise to what's known as "shadow AI," which brings with it significant risks related to data protection and the integrity of outcomes. In fact, one-third of the companies surveyed permit unrestricted access to Generative AI tools for all employees. This can potentially lead to serious security concerns and data breaches.
Impact of the EU AI Act
A significant 71% of surveyed companies identify legal uncertainties and liability risks as key barriers to the wider adoption of generative AI. Currently, only one-third of these companies have established guidelines for AI usage, while 50% are still in the planning phase.
The introduction of the EU AI Act adds further challenges for many of these companies, as a substantial number are not yet ready to comply with the new regulations or are unable to fully assess how these rules will affect their business operations.
GenAI: Tools and Implementation Strategies
To successfully implement GenAI, selecting the right tools and frameworks is essential. Many organizations rely on open-source frameworks like TensorFlow and PyTorch, as well as cloud-based solutions from providers such as AWS, Google, and Microsoft. Notably, ChatGPT from OpenAI is the most widely used tool among the companies surveyed.
Security is a top priority for participants in the study, with 80% of companies incorporating security measures into their GenAI solutions from the outset. Additionally, employee training and pilot projects play a key role in the implementation strategy, along with distinguishing between power users and standard users.
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