Agentic AI Strategies by Industry Experts
By Anand Vemula
Length1h 6m
About this audiobook
Agentic AI Strategies by Industry Experts explores the transformative role of autonomous AI agents across industries, highlighting how businesses can harness their power for innovation, efficiency, and decision-making. This book provides an in-depth analysis of AI-driven strategies in finance, healthcare, e-commerce, cybersecurity, marketing, education, smart cities, and beyond.
The book begins by defining Agentic AI and differentiating it from traditional AI models, emphasizing autonomy, adaptability, and context awareness. It then delves into the architecture of agent-based systems, covering single vs. multi-agent frameworks and their industry applications.
Industry experts share insights on AI-driven algorithmic trading, fraud detection, and financial advisory bots in banking, as well as AI-powered diagnostics, drug discovery, and virtual health assistants in healthcare. In e-commerce, readers discover how AI enhances personalized shopping, inventory management, and customer support. The book also explores how AI secures digital infrastructure through threat detection, anomaly detection, and autonomous cybersecurity agents.
Further chapters highlight AI’s impact on education, marketing, urban planning, and energy efficiency, showcasing how AI-driven solutions personalize learning, optimize city infrastructure, and drive engagement in digital commerce.
Audiobook details
GenreEducation and Learning, Self-Help
Length1 hr 6 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateMay 14, 2025
LanguageEnglish
Table of contents
11.Defining Agentic AI and Its Core Principles
22.Single vs. Multi-Agent Systems
33.AI-Powered Diagnostics and Patient Monitoring
44.Smart Factories and Predictive Maintenance
55.AI-Driven Threat Detection and Incident Response
Show all chaptersShow less
66.AI-Powered Lead Generation and Customer Engagement
77.AI-Driven Traffic Management and Public Transport Optimization
88.Leveraging LLMs for Decision-Making
99.Prompt Engineering and Fine-Tuning for Industry-Specific AI
1010.Implementing AI Agents for Real-World Business Use Cases
1111.AI Bias, Fairness, and Explainability
1212.Best Practices for Responsible AI Deployment
1313.The Rise of Self-Learning AI Agents
1414.AI-Augmented Workforce and Human-AI Collaboration
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