Year: 2025
Type: article
Abstract: Artificial intelligence is undergoing a paradigm shift, evolving from rule-based systems into autonomous agents capable of end-to-end task execution and complex decision-making. This transformation represents what industry leaders call the "third wave" of enterprise automation, where AI systems become active participants in business processes. Modern AI agents combine large language models with multi-agent frameworks that enable specialized functions, self-optimization through feedback loops, and autonomous learning. These agents excel in real-time decision-making across multiple data sources, generative capabilities that create content across modalities, and industryspecific applications in healthcare, finance, and data management. Despite their potential, adoption barriers persist, including trust gaps around data privacy, output accuracy, and ethical alignment, along with operational risks in handling complexity and adapting to dynamic environments. The future landscape will likely be shaped by industry specialization with vertical-specific solutions, evolving regulatory frameworks requiring enhanced transparency, and human-AI collaboration where complementary capabilities create superior outcomes compared to either autonomous systems or traditional workflows alone.
Author: Rajeshkumar Rajubhai Golani
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409395535