AIGC Text Generation: Technological Evolution, Application Scenarios, and Future Challenges

Artificial Intelligence Generated Content (AIGC) refers to technology that uses artificial intelligence to automatically or semi-automatically generate digital content such as text, images, audio, and video. In recent years, generative AI technologies such as large language models (LLMs) based on the Transformer architecture and diffusion models have rapidly developed, driving the widespread application of AIGC in the field of text generation. This article provides a systematic review of the technological evolution, key applications, evaluation methods, and challenges of AIGC text generation. First, it outlines the development trajectory of AIGC technologies, from rule-based and statistical methods to large language model-based approaches. Next, it analyzed its application scenarios and effects in fields such as education, journalism, and cultural creativity; then, it summarized a multi-dimensional evaluation system, including automatic evaluation, human evaluation, AI-generated text detection, and watermarking technology, and explored the AIGC content labeling solutions that have emerged to address abuse risks and their effectiveness; Finally, the paper discusses the challenges of AIGC in terms of technical reliability, bias and fairness, ethical compliance, and social impact, and provides an outlook on future research directions. This article aims to provide a systematic reference for the research and practice of AIGC text generation.