11 A survey of AI in industry: from basic concepts to industrial and business applications
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S. P. Sreekala
, S. Revathy , S. Rajeshwari and B. Girimurugan
Abstract
Artificial intelligence (AI) has the potential to revolutionize nearly every industry, and is already making a significant impact on many. AI in the enterprise has proven to be a major influence on the way products and services are developed, delivered, and sold. AI has helped to automate mundane manual processes, as well as enable companies to provide personalized customer experiences. In the manufacturing industry, AI has enabled robots to replace manual labor, resulting in increased output and improved efficiency. In the retail sector, AI is being used for product recommendations, increased customer personalization, and predictive analytics for inventory management. AI is also being used in the healthcare industry to improve patient diagnosis, predict medical outcomes, and analyze images for potential anomalies. AI has made many areas of industry more efficient and has opened up the possibility of many more advancements.
Abstract
Artificial intelligence (AI) has the potential to revolutionize nearly every industry, and is already making a significant impact on many. AI in the enterprise has proven to be a major influence on the way products and services are developed, delivered, and sold. AI has helped to automate mundane manual processes, as well as enable companies to provide personalized customer experiences. In the manufacturing industry, AI has enabled robots to replace manual labor, resulting in increased output and improved efficiency. In the retail sector, AI is being used for product recommendations, increased customer personalization, and predictive analytics for inventory management. AI is also being used in the healthcare industry to improve patient diagnosis, predict medical outcomes, and analyze images for potential anomalies. AI has made many areas of industry more efficient and has opened up the possibility of many more advancements.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- List of authors IX
- About the editors XIII
- 1 Introduction to artificial intelligence 1
- 2 AI technologies, tools, and industrial use cases 21
- 3 Classification and regression algorithms 53
- 4 Clustering and association algorithm 87
- 5 Reinforcement learning 109
- 6 Evaluation of AI model performance 125
- 7 Methods of cross-validation and bootstrapping 145
- 8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies 167
- 9 AI: issues, concerns, and ethical considerations 189
- 10 The future with AI and AI in action 213
- 11 A survey of AI in industry: from basic concepts to industrial and business applications 233
- 12 The intelligent implications of artificial intelligence-driven decision-making in business management 251
- 13 An innovative analysis of AI-powered automation techniques for business management 269
- 14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications 287
- 15 Utilizing AI technologies to enhance e-commerce business operations 309
- 16 Exploring the potential of artificial intelligence in wireless sensor networks 331
- 17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining 345
- 18 Exploring the potential of artificial intelligence for automated sentiment 361
- 19 A novel blockchain-based artificial intelligence application for healthcare automation 373
- 20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions 387
- Index 401
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- List of authors IX
- About the editors XIII
- 1 Introduction to artificial intelligence 1
- 2 AI technologies, tools, and industrial use cases 21
- 3 Classification and regression algorithms 53
- 4 Clustering and association algorithm 87
- 5 Reinforcement learning 109
- 6 Evaluation of AI model performance 125
- 7 Methods of cross-validation and bootstrapping 145
- 8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies 167
- 9 AI: issues, concerns, and ethical considerations 189
- 10 The future with AI and AI in action 213
- 11 A survey of AI in industry: from basic concepts to industrial and business applications 233
- 12 The intelligent implications of artificial intelligence-driven decision-making in business management 251
- 13 An innovative analysis of AI-powered automation techniques for business management 269
- 14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications 287
- 15 Utilizing AI technologies to enhance e-commerce business operations 309
- 16 Exploring the potential of artificial intelligence in wireless sensor networks 331
- 17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining 345
- 18 Exploring the potential of artificial intelligence for automated sentiment 361
- 19 A novel blockchain-based artificial intelligence application for healthcare automation 373
- 20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions 387
- Index 401