Emerging Trends in Generative AI and Machine Learning for Enterprise Intelligence
Keywords:
Generative AI, Large Language Models, Enterprise Intelligence, Retrieval-Augmented Generation, Agentic AI, Business Intelligence, Fine-Tuning, AI GovernanceAbstract
Generative artificial intelligence (AI), driven by advances in large language models (LLMs) and multimodal foundation models, has rapidly transitioned from a research curiosity to a central pillar of enterprise information technology strategy. Organizations across industries are integrating generative AI into knowledge management, customer engagement, software development, and operational decision-making, giving rise to the broader concept of enterprise intelligence: the systematic use of AI-driven insight generation, automation, and reasoning to enhance organizational performance. This paper presents a comprehensive review of emerging trends in generative AI and machine learning for enterprise intelligence, covering the evolution from traditional business intelligence and predictive analytics to generative and agentic AI paradigms, the architectural building blocks that enable enterprise-grade deployment — including retrieval-augmented generation (RAG), fine-tuning and parameter-efficient adaptation, and multi-agent orchestration — and representative enterprise application domains spanning knowledge management, customer service, software engineering, marketing, and enterprise decision support. The review further examines critical open challenges, including hallucination and factual reliability, data governance and privacy, integration with legacy enterprise systems, cost and computational overhead, and organizational change management. Finally, the paper outlines emerging research and practice directions, including agentic multi-step workflows, enterprise-grade retrieval and grounding architectures, small and domain-specialized language models, and governance frameworks for responsible enterprise AI adoption. This review is intended to serve as a consolidated reference for researchers and practitioners navigating the rapidly evolving landscape of generative AI-driven enterprise intelligence.
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