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Artificial Intelligence in the Real World: How AI Is Changing Industry, Business and Everyday Life
Paperback
Series: AI Without Myths, Book 4
Technology & EngineeringGeneral Computers
Publisher: Independently Published
Published: Jul 10 2026
Pages: 206
Weight: 0.56
Height: 0.52 Width: 6.00 Depth: 9.00
Language: English
Artificial intelligence is no longer a future concept. It is already used in factories, hospitals, vehicles, power systems, banks, warehouses, smartphones, and digital services.
But what does AI actually do in practice? Where does it create real value, and when is traditional automation still the better solution?
Artificial Intelligence in the Real World explains how modern AI is applied across industry, business, public services, and everyday life. Instead of focusing on science fiction or exaggerated predictions, the book examines AI as it currently exists: a practical tool for prediction, classification, analysis, optimization, recommendation, and decision support.
The book explores real applications including:
Predictive maintenance and equipment monitoring
Machine vision and automated quality inspection
Industrial robots and intelligent production systems
Energy forecasting and power management
Healthcare diagnostics and patient monitoring
Transport, logistics, and route optimization
Banking, finance, and fraud detection
Cybersecurity and anomaly detection
Agriculture and precision farming
Education and personalized learning
Smart cities and public infrastructure
Entertainment and digital recommendation systems
Space research and autonomous exploration
AI tools used in everyday products and services
Each major application is explained through a practical structure: the real problem, the traditional solution, the AI-based approach, the expected benefits, the limitations, and the conditions required for successful implementation.
Readers will understand why prediction is the foundation of many useful AI systems, how machine-learning models identify patterns in data, and why the quality of the result depends heavily on the quality of the information used to train and operate the system.
The book also explains where AI fails.
An AI system may produce unreliable results when data is incomplete, biased, outdated, incorrectly labeled, or collected from an unstable process. A model can drift as machines, markets, environments, or human behavior change. False alarms, missed events, poor integration, excessive cost, and unnecessary complexity can turn an impressive demonstration into a failed project.
Special attention is given to the continued importance of traditional engineering. PLC logic, PID control, fixed rules, protection relays, interlocks, and deterministic systems remain the correct choice whenever predictable behavior, rapid response, explainability, or safety is more important than statistical flexibility.
AI should not replace a reliable conventional solution simply because it is newer.
Readers will learn how to evaluate whether an AI project is useful, affordable, maintainable, and safe. The book examines the transition from prediction to decision and explains why human responsibility must remain present when AI affects machines, finances, health, safety, or public infrastructure.
This book is written for:
Engineers and industrial technicians
Managers and business owners
Automation and maintenance specialists
Students and educators
Technology professionals
Readers who want a realistic understanding of AI
Artificial intelligence is powerful, but it is not magic. It does not automatically understand context, guarantee correctness, or remove responsibility from the people who design and use it.
Artificial Intelligence in the Real World provides a balanced and practical guide to what AI can achieve, where it creates measurable benefits, where it introduces risk, and how human expertise and intelligent technology can work together effectively.
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