Examples include general-purpose text-generation AI like ChatGPT and Gemini, as well as image-generation AI like Stable Diffusion and DALL-E. In the future, this technology is expected to evolve in two directions: a more comprehensive approach that integrates various functions and a specialized approach that focuses on a single function.

When used correctly, Generative AI can boost business efficiency and streamline creative tasks. For instance, it is often used for automatically generating meeting minutes, summarizing long texts, and drafting emails. By providing high-quality information, it can also be used to create new value aligned with customer needs, customize product development, and enhance sales and marketing practices, ultimately strengthening a company's competitiveness.

Despite its potential, the practical use of Generative AI faces several challenges. These include the risk of intellectual property infringement in generated content, the potential for factual errors or misinformation, and security concerns such as cyber risks and misuse.

Recognizing these issues and implementing thorough countermeasures is crucial for the sustainable use of Generative AI. To use it safely, securely, and effectively, organizations must strive for proper operational management and stay updated on the latest technological trends.