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Impact of Artificial Intelligence on Organizational Transformation


Impact of Artificial Intelligence on Organizational Transformation


Artificial Intelligence and Soft Computing for Industrial Transformation 1. Aufl.

von: S. Balamurugan, Sonal Pathak, Anupriya Jain, Sachin Gupta, Sachin Sharma, Sonia Duggal

173,99 €

Verlag: Wiley
Format: PDF
Veröffentl.: 31.12.2021
ISBN/EAN: 9781119710059
Sprache: englisch
Anzahl Seiten: 448

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Beschreibungen

<b>IMPACT OF ARTIFICIAL INTELLIGENCE ON ORGANIZATIONAL TRANSFORMATION</b> <p><b>Discusses the impact of AI on organizational transformation which is a mix of computational techniques and management practices, with in-depth analysis about the role of automation & data management, and strategic management in relation to human capital, procurement & production, finance, and marketing. </b> <p>The impact of AI in restructuring organizational processes is a combination of management practices and computational technology. This book covers the areas like artificial intelligence & its impact on professions, as well as machine learning algorithms and technologies. The context of applications of AI in business process innovation primarily includes new business models, AI readiness and maturity at the organizational, technological, financial, and cultural levels. The book has extensive details on machine learning and the applications such as robotics, blockchain, Internet of Things. Also discussed are the influence of AI on financial strategies and policies, human skills & values, procurement innovation, production innovation, AI in marketing & sales platforms. <p><b> Audience </b> <p>Readers include those working in artificial intelligence, business management studies, technology engineers, senior executives, and human resource managers in all types of business.
<p>Foreword xxiii</p> <p>Preface xxv</p> <p><b>1 Artificial Intelligence Disruption on the Brink of Revolutionizing HR and Marketing Functions 1<br /></b><i>Akansha Mer and Amarpreet Singh Virdi</i></p> <p>1.1 Introduction 2</p> <p>1.2 Research Methodology 4</p> <p>1.2.1 Research Objectives 4</p> <p>1.2.2 Data Collection 4</p> <p>1.3 Artificial Intelligence in HRM 4</p> <p>1.3.1 Recruitment 5</p> <p>1.3.2 Engaging the Applicants and Employees 5</p> <p>1.3.3 Orientation and Onboarding 6</p> <p>1.3.4 Performance Appraisal 6</p> <p>1.3.5 Training 7</p> <p>1.3.6 Compensation 7</p> <p>1.3.7 Employee Retention 8</p> <p>1.4 Artificial Intelligence in Marketing 8</p> <p>1.4.1 Creation of Customer Profiles/Market Segmentation 9</p> <p>1.4.2 Cognizance of Consumers Purchase Behavior/Intention 10</p> <p>1.4.3 Pricing 11</p> <p>1.4.4 Content/Product/Service Recommendations/Search Optimization 11</p> <p>1.4.5 Sales Prediction Based on Consumer’s Demographics 12</p> <p>1.4.6 Virtual Assistants/Real-Time Conversations 12</p> <p>1.4.7 Visual Searching 12</p> <p>1.4.8 CRM 13</p> <p>1.5 Discussion and Findings 13</p> <p>1.6 Implication for Managers 14</p> <p>1.7 Conclusion 15</p> <p>References 16</p> <p><b>2 Ring Trading to Algo Trading—A Paradigm Shift Made Possible by Artificial Intelligence 21<br /></b><i>Aditi R. Khandelwal</i></p> <p>2.1 Introduction 22</p> <p>2.2 Ring Trading 22</p> <p>2.3 Features of Generation 1: Ring Trading 22</p> <p>2.4 Generation 2: Shifting to Online Platform 24</p> <p>2.5 Generation 3: Algo Trading 28</p> <p>2.6 Artificial Intelligence 29</p> <p>2.7 AI Stock Trading 30</p> <p>2.8 Algorithmic (Algo Trading) Trading 31</p> <p>2.9 Conclusion 31</p> <p>References 32</p> <p><b>3 AI in HR a <i>Fairy Tale </i>of Combining People, Process, and Technology in Managing the Human Resource 33<br /></b><i>Jyoti Jain and Sachin Gupta</i></p> <p>3.1 Introduction 34</p> <p>3.2 Problem Recognition 35</p> <p>3.3 Journey of AI in HR “From Where Till What” 36</p> <p>3.4 Work Methodology of AI in HR 39</p> <p>3.5 Branches of AI in HR 39</p> <p>3.5.1 Machine Learning 39</p> <p>3.5.1.1 Variance Detection 39</p> <p>3.5.1.2 Background Verification 40</p> <p>3.5.1.3 Employees Abrasion/Attrition 40</p> <p>3.5.1.4 Personalized Content 40</p> <p>3.5.2 Deep Learning 40</p> <p>3.5.2.1 Important Use of Deep Learning in HR Context 40</p> <p>3.5.3 Natural Language Processing 41</p> <p>3.5.4 Recommendation Engines 41</p> <p>3.6 Implication Stages of AI in HR 41</p> <p>3.6.1 Automate 42</p> <p>3.6.2 Augment 42</p> <p>3.6.3 Amplify 42</p> <p>3.7 Process Model of AI in HR 43</p> <p>3.8 Key Roles of AI in HRM 44</p> <p>3.9 Broad Area of Uses of AI in HR 45</p> <p>3.9.1 Recruitment 46</p> <p>3.9.2 Interviews 46</p> <p>3.9.3 Reduction in the Human Biases 46</p> <p>3.9.4 Retention 47</p> <p>3.9.5 AI in Learning and Advancement 47</p> <p>3.9.6 Diminish Gender Bias Equality 47</p> <p>3.9.7 Candidate Engagement 48</p> <p>3.9.8 Prediction 48</p> <p>3.9.9 Smart People Analytics 48</p> <p>3.9.10 Employee Experience 48</p> <p>3.10 Dark Side of AI 50</p> <p>3.10.1 Technical Requirements and Acceptance 51</p> <p>3.10.2 Cost Involvement 52</p> <p>3.10.3 Machine Biases 52</p> <p>3.10.4 Job Losses 52</p> <p>3.10.5 Emotional Turmoil 53</p> <p>3.10.6 Fake Identity 53</p> <p>3.10.7 Having an Audit Trail 53</p> <p>3.10.8 Question on Decisions 54</p> <p>3.11 Conclusion 54</p> <p>References 55</p> <p><b>4 Effect of Artificial Intelligence on Human Resource Profession: A Paradigm Shift 57<br /></b><i>Jyoti Dashora and Karunesh Saxena</i></p> <p>4.1 Introduction 58</p> <p>4.2 Evolution of Artificial Intelligence 59</p> <p>4.2.1 Phases of Artificial Intelligence 61</p> <p>4.3 Changing Role of Human Resource Professionals 61</p> <p>4.4 Effect of Artificial Intelligence on Human Resource Profession 63</p> <p>4.4.1 Symbiotic Relationship Between Artificial Intelligence and Human Resource Profession 67</p> <p>4.5 Limitations of Artificial Intelligence in HRM 68</p> <p>4.6 Conclusion 69</p> <p>References 70</p> <p><b>5 Artificial Intelligence in Animal Surveillance and Conservation 73<br /></b><i>Devendra Kumar and Saha Dev Jakhar</i></p> <p>5.1 History 74</p> <p>5.2 Introduction 74</p> <p>5.3 Need of Artificial Intelligence 75</p> <p>5.4 Applications of AI in Animal Surveillance and Conservation 76</p> <p>5.4.1 In Livestock Monitoring 77</p> <p>5.4.1.1 Chip and Sensor (RFID) 78</p> <p>5.4.1.2 Microchip (GPS Tracker) 79</p> <p>5.4.1.3 Mobile Application 79</p> <p>5.4.1.4 Drone With Thermal Camera 79</p> <p>5.4.2 In Wildlife Animal Monitoring 80</p> <p>5.4.2.1 Motion Sensor Camera 80</p> <p>5.4.2.2 GPS Base Animal Tracker 81</p> <p>5.4.2.3 Smart Camera (Thermal Camera) 82</p> <p>5.4.2.4 Satellite Base Tag (Ringing, Callers) 82</p> <p>5.4.2.5 Acoustics/Sound Monitoring 82</p> <p>5.4.2.6 Radio Transmitter (Transponder) 83</p> <p>5.5 Some Other Tools of Artificial Intelligence 84</p> <p>5.5.1 Computer Software and Application 84</p> <p>5.5.1.1 Wildbook Comb (Bot) 84</p> <p>5.5.1.2 Betty 84</p> <p>5.5.1.3 Sensing Clues 84</p> <p>5.5.2 Resolve’s Trail Guard 84</p> <p>References 85</p> <p><b>6 Impact of Artificial Intelligence on Digital Marketing 87<br /></b><i>Giuseppe Granata and Vincenzo Palumbo</i></p> <p>6.1 Introduction 88</p> <p>6.2 The Impact That AI Has on Marketing 89</p> <p>6.2.1 The Data of Artificial Intelligence in Marketing 90</p> <p>6.2.1.1 The Audience: Highly Targeted Marketing Segmentation 92</p> <p>6.2.1.2 Journey to: The Customer’s Road 92</p> <p>6.2.1.3 Offer to: Advice-Based Behavioral Marketing 92</p> <p>6.2.2 Number of Efficiency Powered by the Al Global Consumer Statistics 94</p> <p>6.2.3 Cloud Computing: How it Interfaces to Marketing Thanks to Big Data 95</p> <p>6.2.4 AI World is Made Also With BOT. Exactly What Are BOT? 98</p> <p>6.2.5 The Chatbot: Service Robot as Support of Customer Care 99</p> <p>6.3 The Community Regulation “GDPE” and Artificial Intelligence: Here’s How Technology is Governed 101</p> <p>6.4 The Case Study Estée Lauder 103</p> <p>6.5 Conclusion 104</p> <p>References 105</p> <p><b>7 Role of Artificial Intelligence in Transforming the Face of Banking Organizations 109<br /></b><i>Shweta Solanki, MeeraMathur and BhumikaRathore</i></p> <p>7.1 Objectives 110</p> <p>7.2 Introduction 110</p> <p>7.2.1 Three Stages of Artificial Intelligence 111</p> <p>7.2.2 Different Types of Artificial Intelligence 111</p> <p>7.2.3 Trends and Need of Artificial Intelligence in Context of Indian Banking 111</p> <p>7.2.4 Uses and Role of Artificial Intelligence in Banks in the Opinion of 113</p> <p>7.2.5 Importance of Artificial Intelligence in Banking Practices and Operation 114</p> <p>7.2.5.1 Chat Bots 115</p> <p>7.2.5.2 Analytics 115</p> <p>7.2.5.3 Robotics Process Automation 115</p> <p>7.2.5.4 Generating Reports 115</p> <p>7.2.6 Impact of AI in Banking Operations 116</p> <p>7.2.6.1 Front Office Operations/Customer Centric 116</p> <p>7.2.6.2 Middle Office/Operation Centric 116</p> <p>7.2.6.3 Back Office/Decision Centric 116</p> <p>7.2.7 Future of Artificial Intelligence in Banks 116</p> <p>7.3 Existing Technology 117</p> <p>7.4 Methodology 117</p> <p>7.4.1 Search Process 118</p> <p>7.4.2 Selection Criteria and Review Process 118</p> <p>7.5 Findings 118</p> <p>7.6 Conclusion 119</p> <p>7.7 Suggestions 119</p> <p>References 120</p> <p><b>8 Artificial Intelligence and Energy Sector 123<br /></b><i>Oum Kumari R</i></p> <p>8.1 Introduction 123</p> <p>8.1.1 Increase in the Emission of Greenhouse Gases 124</p> <p>8.1.2 Increase in the Financial Burden 124</p> <p>8.1.3 Huge Power Deficit 124</p> <p>8.1.4 Water Scarcity 124</p> <p>8.2 Challenges of Indian Power Sector 125</p> <p>8.2.1 Global Warming 125</p> <p>8.2.2 Depletion of Coal 125</p> <p>8.2.3 Huge Financial Stress 126</p> <p>8.2.4 Power Crisis 126</p> <p>8.2.5 Health Issues 127</p> <p>8.2.6 Plant Load Factor 127</p> <p>8.2.7 Transmission and Distribution (T&D) Losses 128</p> <p>8.3 Artificial Intelligence for Energy Solutions 128</p> <p>References 129</p> <p><b>9 Impact of Artificial Intelligence on Development and Growth of Entrepreneurship 131<br /></b><i>Pooja Meena, Ankita Chaturvedi and Sachin Gupta</i></p> <p>9.1 Introduction 132</p> <p>9.2 Entrepreneurship 133</p> <p>9.3 Artificial Intelligence 133</p> <p>9.4 Artificial Intelligence and Entrepreneurship 134</p> <p>9.5 Process of Entrepreneurship 135</p> <p>9.5.1 Entrepreneurial Recognition 135</p> <p>9.5.2 Human Capital 136</p> <p>9.5.3 Technology Requirements and Idea Generation 136</p> <p>9.5.4 Opportunity Recognition Phase 136</p> <p>9.5.5 Opportunity Development 136</p> <p>9.5.6 Resource Requirements 136</p> <p>9.5.7 Entrepreneurship 137</p> <p>9.5.8 Financial Resources 137</p> <p>9.5.9 Opportunity Exploitation 137</p> <p>9.5.10 Knowledge Networks 137</p> <p>9.5.11 Validation of the Product 137</p> <p>9.6 The Need of Artificial Intelligence for Business Development 138</p> <p>9.6.1 Consumer Satisfaction 138</p> <p>9.6.2 Cybercrime Protection 138</p> <p>9.6.3 CRMs 139</p> <p>9.6.4 AI-Based Analytics 139</p> <p>9.6.5 Demand and Supply Management 139</p> <p>9.6.6 Improved Maintenance and Better Equipment Safety 139</p> <p>9.6.7 Searching Capable Employees 140</p> <p>9.6.8 Virtual Assistance for Sales 140</p> <p>9.6.9 Improvements With Self-Driven Technologies 140</p> <p>9.7 Some Important Facts About AI 141</p> <p>9.8 Opportunities for Artificial Intelligence in Business 141</p> <p>9.8.1 AI in the Field of Marketing 141</p> <p>9.8.2 For Track Competitors 142</p> <p>9.8.3 Make Less Work of Huge Data 142</p> <p>9.8.4 AI as Customer Support System 142</p> <p>9.8.5 Artificial Intelligence in CRMs 143</p> <p>9.9 Further Research Possibilities 144</p> <p>9.10 Conclusion 144</p> <p>References 145</p> <p><b>10 An Exploratory Study on Role of Artificial Intelligence in Overcoming Biases to Promote Diversity and Inclusion Practices 147<br /></b><i>Bhumika Rathore, Meeera Mathur and Shweta Solanki</i></p> <p>10.1 Introduction 148</p> <p>10.1.1 Objectives of the Study 149</p> <p>10.1.2 Background of the Study 149</p> <p>10.1.3 Relevance and Scope of the Study 149</p> <p>10.2 Research Gaps Identified 150</p> <p>10.3 Experiential Framework 150</p> <p>10.3.1 Hypothetical Research Model 151</p> <p>10.3.2 Methodology 151</p> <p>10.3.3 Search Process 152</p> <p>10.3.4 Selection Criteria and Review Process 152</p> <p>10.3.5 Systematic Representation of Literature Review 153</p> <p>10.3.6 Understanding Workforce Diversity 154</p> <p>10.3.7 Benefits and Challenges of Workforce Diversity 155</p> <p>10.3.8 Biases as Obstacles in Diversity and Inclusion Practices 157</p> <p>10.3.9 AI as a Tool to Prevent Bias and Promote D&I Practices 159</p> <p>10.4 Synthesis of the Study 161</p> <p>10.5 Managerial Implications and Conclusion 161</p> <p>References 163</p> <p><b>11 Artificial Intelligence: Revolutionizing India Byte by Byte 165<br /></b><i>Priyanka Jingar, Anju Singh and Sachin Gupta</i></p> <p>11.1 Introduction 165</p> <p>11.2 Objectives of the Chapter 166</p> <p>11.3 AI for India’s Transformation 167</p> <p>11.4 Economic Impact of Artificial Intelligence 169</p> <p>11.5 Artificial Intelligence and its Impact on Various Sectors 170</p> <p>11.5.1 AI in Healthcare 171</p> <p>11.5.2 AI in Banking and Finance 172</p> <p>11.5.3 Artificial Intelligence in Education 173</p> <p>11.5.4 Artificial Intelligence in Agriculture Sector 175</p> <p>11.5.5 Artificial Intelligence in Smart Cities and Infrastructure 176</p> <p>11.5.6 AI in Smart Mobility and Transportation 177</p> <p>11.6 SWOT Analysis of Artificial Intelligence 178</p> <p>11.6.1 Strength 178</p> <p>11.6.2 Weakness 179</p> <p>11.6.3 Opportunity 179</p> <p>11.6.4 Threat 180</p> <p>11.7 Conclusion 181</p> <p>References 181</p> <p><b>12 AI: A New Strategic Method for Marketing and Sales Platforms 183<br /></b><i>Ravindar Meena, Ashmi Chhabra, Sachin Gupta and Manoj Gupta</i></p> <p>12.1 Introduction 184</p> <p>12.2 Objectives of the Chapter 184</p> <p>12.3 Importance of Artificial Intelligence 185</p> <p>12.4 Research Methodology 186</p> <p>12.5 AI: The Ultimate B2B Growth Accelerator 187</p> <p>12.5.1 AI Can Help Get Better Leads 187</p> <p>12.5.2 Predictive Analysis Improves Pitches 188</p> <p>12.5.3 Better Upsell Opportunities 188</p> <p>12.5.4 AI is an Excessive Digital Assistant 188</p> <p>12.5.5 AI and Improved Customer Conversations 188</p> <p>12.6 The Existing Methods of Marketing and Sales 189</p> <p>12.6.1 Being Lazy About Self-Promotion 189</p> <p>12.6.2 Avoiding Networking 189</p> <p>12.6.3 Bridging the New Product Launch Gap 190</p> <p>12.7 AI Will Shape Marketing Strategies of Startup in the Future 190</p> <p>12.7.1 Winning the Loots of Artificial Intelligence 192</p> <p>12.7.2 The Control of Artificial Intelligence and Recorded Data 192</p> <p>12.7.3 Artificial Intelligence the Game Changer for Small Businesses 192</p> <p>12.7.4 AI Selling and Marketing for E-Commerce 192</p> <p>12.7.5 Marketing Computerization to Modified Knowledge 193</p> <p>12.8 Artificial Intelligence is Shaking up the Job Market 193</p> <p>12.9 The Role of Artificial Intelligence and Machine Learning on Marketing 195</p> <p>12.9.1 Traditional and Modern Marketing 196</p> <p>12.10 Conclusion 197</p> <p>References 198</p> <p><b>13 Brain and Behavior: Blending of Human and Artificial Minds Toward Stress Recognition and Intervention in Organizational Well-Being 201<br /></b><i>Manisha D. Solanky and Sachin Gupta</i></p> <p>13.1 Introduction 202</p> <p>13.2 Research Methodology 203</p> <p>13.3 Fundamentals of Stress 203</p> <p>13.3.1 Stress at Workplace 205</p> <p>13.3.2 Symptoms and Outcome of Stress 206</p> <p>13.4 Embracing AI Opportunity in Stress Management Interventions 207</p> <p>13.5 Existing Technology for Stress Recognition 208</p> <p>13.5.1 Smart Detection Devices 209</p> <p>13.5.2 Stress Detection Through Physiological Signals 209</p> <p>13.5.3 Sensor-Based Detection 210</p> <p>13.5.4 Deep Learning Approaches for Stress Detection 210</p> <p>13.5.5 Stress Detection Through Biofeedback Systems 210</p> <p>13.5.6 Stress Detection Through Virtual Reality 212</p> <p>13.5.7 Stress Detection Through Keyboard Strokes 213</p> <p>13.5.7.1 Chatbots for Depression, Stress, and Anxiety 213</p> <p>13.5.7.2 WYSA Chatbot 214</p> <p>13.5.8 Stress Intervention Based on Human-Technology Interaction 214</p> <p>13.5.8.1 Individual Level of Intervention 215</p> <p>13.5.8.2 Organization Level Intervention 215</p> <p>13.5.8.3 Devices Supporting Stress Interventions 216</p> <p>13.6 Discussion and Findings 218</p> <p>13.7 An AI—Eye to the Future 220</p> <p>13.7.1 Implications to Managers 220</p> <p>13.7.2 Implication to the Entrepreneurs 221</p> <p>13.8 Conclusion 222</p> <p>13.9 Limitations of AI in Human Resource Management 223</p> <p>13.10 Conclusion 223</p> <p>References 224</p> <p><b>14 Alternative Financing 229<br /></b><i>Suhasini Verma</i></p> <p>14.1 Introduction 229</p> <p>14.1.1 Sources of Funds for Individuals 230</p> <p>14.1.2 Sources of Funds for Organizations 231</p> <p>14.2 Alternative Financing 231</p> <p>14.2.1 Features of Alternative Financing 231</p> <p>14.3 Models of Alternative Financing 235</p> <p>14.3.1 Peer-to-Peer Lending 235</p> <p>14.3.1.1 Peer-to-Peer Lending Types 235</p> <p>14.3.2 Crowdfunding 236</p> <p>14.3.2.1 Equity-Based Crowdfunding 236</p> <p>14.3.2.2 Profit Sharing Crowdfunding 236</p> <p>14.3.2.3 Reward-Based Crowdfunding 237</p> <p>14.3.2.4 Donation-Based Crowdfunding 237</p> <p>14.4 Scope of Alternative Financing in India 237</p> <p>14.5 Alternative Finance as a Tool of Financial Inclusion 241</p> <p>14.6 Regulation of Alternative Finance 241</p> <p>References 242</p> <p>Further Web Links 243</p> <p>Dissertation 243</p> <p><b>15 Application of Machine Learning in Open Government Database 245<br /></b><i>Shantanu P. Chakraborty, Parul Dashora and Sachin Gupta</i></p> <p>15.1 Introduction 246</p> <p>15.2 Literature Review 246</p> <p>15.3 Overview of Open Government Data 247</p> <p>15.4 Open Government Data in India 248</p> <p>15.5 How to Create Value from Data 251</p> <p>15.6 Artificial Intelligence 251</p> <p>15.7 Why AI is Important? 252</p> <p>15.8 Machine Learning 252</p> <p>15.9 Concerns About Machine Learning on Government Database 254</p> <p>15.10 Conclusion 255</p> <p>References 255</p> <p><b>16 Artificial Intelligence: An Asset for the Financial Sector 259<br /></b><i>Swati Bandi and Anil Kothari</i></p> <p>16.1 Introduction 259</p> <p>16.1.1 Phase I 1950–1983 Origin of AI and the First Hype Cycle 260</p> <p>16.1.2 II Phase 1983–2010 Reawakening of Artificial Intelligence 261</p> <p>16.1.3 III Phase 2011–2017 AI Domains Competing Humans 262</p> <p>16.1.4 The Present and the Future Phase (2018–2035) 264</p> <p>16.2 Types, Technology, and Application of AI 265</p> <p>16.2.1 Types of Artificial Intelligence 265</p> <p>16.2.2 Artificial Intelligence Technologies 265</p> <p>16.2.3 Applications of Artificial Intelligence 266</p> <p>16.3 Artificial Intelligence and Financial Services 268</p> <p>16.3.1 Artificial Intelligence and Insurance 269</p> <p>16.3.2 Artificial Intelligence and Stock Market 275</p> <p>16.3.2.1 From the History of Stock Exchange to the Development of Algo Trading in India 276</p> <p>16.3.2.2 What is Algorithmic Trading? 276</p> <p>16.3.2.3 Benefits of Algo Trading 277</p> <p>16.3.2.4 Algorithmic Trading Platforms 277</p> <p>16.3.2.5 Algo Trading Strategies 278</p> <p>16.3.2.6 Impact of Artificial Intelligence on Stock Market 280</p> <p>16.3.3 Artificial Intelligence and Mutual Funds 281</p> <p>16.3.3.1 Mutual Funds Use AI in the Following Ways 282</p> <p>16.3.3.2 Quantitative Fund’s Investment Process 282</p> <p>16.3.3.3 Quantitative Fund—Choosing Stocks Strategy 283</p> <p>16.3.3.4 The Other Way Around 284</p> <p>16.4 Conclusion 284</p> <p>16.5 Glossary 285</p> <p>References 286</p> <p>Bibliography 287</p> <p><b>17 Artificial Intelligence With Special Reference to Blockchain Technology: A Future of Accounting 289<br /></b><i>Ashish Porwal, Ankita Chaturvedi and Sachin Gupta</i></p> <p>17.1 Introduction 290</p> <p>17.1.1 Artificial Intelligence and Accounting 290</p> <p>17.1.2 Blockchain in Finance and Accounting 290</p> <p>17.2 Objectives 292</p> <p>17.3 Literature Review 292</p> <p>17.3.1 Janling Shi 292</p> <p>17.3.2 Nordgren <i>et al. </i>293</p> <p>17.3.3 Kiwilinski 293</p> <p>17.3.4 Ahmed Farah 293</p> <p>17.3.5 Odoh Longinus Chukwudi 294</p> <p>17.3.6 Potekhina and Rumkin 294</p> <p>17.4 Research Methodology 295</p> <p>17.5 Usage of Artificial Intelligence in Accounting 295</p> <p>17.6 Usage of Blockchain in Accounting 297</p> <p>17.6.1 Bitcoin 297</p> <p>17.6.2 Interbank Transactions 298</p> <p>17.6.3 Property Registry 299</p> <p>17.7 Impact of AI on the Field of HRM 300</p> <p>17.8 Challenges in Execution 301</p> <p>17.9 Conclusion 301</p> <p>References 302</p> <p><b>18 AI-Implanted E-Learning 4.0: A New Paradigm in Higher Education 305<br /></b><i>Garima Kothari and B.L. Verma</i></p> <p>18.1 Introduction 306</p> <p>18.2 Research Methodology 307</p> <p>18.2.1 Objective 307</p> <p>18.2.2 Research Approach 307</p> <p>18.2.3 Types and Sources of Data 307</p> <p>18.3 Progression of Web and E-Learning 307</p> <p>18.3.1 Some Relevant Definitions Distance Education 307</p> <p>18.3.2 E-Learning 308</p> <p>18.3.3 E-Learning 1.0–4.0 308</p> <p>18.3.3.1 Web 1.0 E-Learning 1.0 (Link to Anything): 1997 to 2003 308</p> <p>18.3.3.2 Web 2.0 E-Learning 2.0 (User Involvement): 2004 to 2006 308</p> <p>18.3.3.3 Web 3.0 E-Learning 3.0 (Existing Data Reconnected): 2007 to 2011 308</p> <p>18.3.3.4 Web 4.0 (Read/Write/Execute/Concurrency From 2012) 309</p> <p>18.4 Artificial Intelligence in Learning 313</p> <p>18.4.1 What is Artificial Intelligence? 313</p> <p>18.4.2 AI En Routed the Learning 314</p> <p>18.4.2.1 Smart Learning Content 314</p> <p>18.4.2.2 Intelligent Tutoring Systems 315</p> <p>18.4.2.3 Virtual Facilitators and Learning Environments 315</p> <p>18.4.2.4 Content Analytics 315</p> <p>18.4.2.5 Paving New Learning Pathways in the Coming Decade 316</p> <p>18.5 Impact of Artificial Intelligence in Education (AIEd) 316</p> <p>18.5.1 Will AI Take Over From Humans? 316</p> <p>18.5.2 AI-Implanted E-Learning 317</p> <p>18.5.2.1 Avatars 317</p> <p>18.5.2.2 Hyper-Reality 318</p> <p>18.5.2.3 The Hyper Class in Virtual Universities 318</p> <p>18.5.2.4 JITAITs 319</p> <p>18.5.3 Recommendations to Help Unleash Intelligence 319</p> <p>18.5.3.1 Pedagogy 320</p> <p>18.5.3.2 Technology 320</p> <p>18.5.3.3 System Change 321</p> <p>18.6 Conclusion 321</p> <p>Concise Summary 322</p> <p>References 322</p> <p><b>19 Artificial Intelligence in Banking Industry 327<br /></b><i>GarimaKaneria</i></p> <p>19.1 Introduction 327</p> <p>19.2 Banking on Artificial Intelligence 329</p> <p>19.3 Role of Artificial Intelligence in Shaping Indian Banking Industry 330</p> <p>19.3.1 Detection of Anti-Money Laundering Pattern 330</p> <p>19.3.2 Chatbots 330</p> <p>19.3.3 Algorithmic Trading 331</p> <p>19.3.4 Fraud Detection 332</p> <p>19.3.5 Customer Suggestions 332</p> <p>19.3.6 Personalized Banking 332</p> <p>19.3.7 Digital Payments 333</p> <p>19.3.8 Robo Advisors 334</p> <p>19.4 Influence of Artificial Intelligence on Indian Banking Industry 334</p> <p>19.5 Reasons Behind Elongated Adoption of Artificial Intelligence in Banking Industry 336</p> <p>19.5.1 Cut-Throat Competition in Banking Sector 336</p> <p>19.5.2 Push for Process-Driven Services 336</p> <p>19.5.3 Introduction of Self-Service at Banks 336</p> <p>19.5.4 Customer Demand for More Customized Solutions 336</p> <p>19.5.5 Creating Operational Efficiencies 336</p> <p>19.5.6 Increasing Employee Productivity 337</p> <p>19.5.7 To Help Focus on Profitability and Compliance 337</p> <p>19.5.8 Use of Robotics Software 337</p> <p>19.5.9 To Reduce Fraud and Risk Associated With Security 337</p> <p>19.5.10 To Manage Large Information and Derive Value Insight 337</p> <p>19.5.11 To Bring in Effective Decision-Making 338</p> <p>19.6 Indian Banks Using Artificial Intelligence 338</p> <p>19.6.1 State Bank of India 338</p> <p>19.6.2 Bank of Baroda 339</p> <p>19.6.3 Allahabad Bank 339</p> <p>19.6.4 Andhra Bank 339</p> <p>19.6.5 YES Bank 339</p> <p>19.6.6 Housing Development Finance Corporation (HDFC) 339</p> <p>19.6.7 Industrial Credit and Investment Corporation of India (ICICI) 340</p> <p>19.6.8 Axis Bank 340</p> <p>19.6.9 Canara Bank 340</p> <p>19.6.10 Punjab National Bank 340</p> <p>19.6.11 IndusInd Bank 340</p> <p>19.6.12 City Union Bank 341</p> <p>19.7 Pros and Cons of Artificial Intelligence in Banking Sector 341</p> <p>19.7.1 Pros 341</p> <p>19.7.1.1 Tracking of Transactional and Other Data Sources 341</p> <p>19.7.1.2 Identification of Pattern Which May Be Eluded by Human Observers 341</p> <p>19.7.1.3 Risk Assessment 341</p> <p>19.7.1.4 Secure and Swift Transaction 342</p> <p>19.7.1.5 Protection of Personal Data 342</p> <p>19.7.1.6 Hedge Fund Trading and Management 342</p> <p>19.7.1.7 Quick Transaction 342</p> <p>19.7.1.8 Reduce Cost and Time 342</p> <p>19.7.1.9 Upgraded Personnel Effectiveness and Customer Observation 342</p> <p>19.7.1.10 Enhanced Banking Services 343</p> <p>19.7.2 Cons 343</p> <p>19.7.2.1 High Cost 343</p> <p>19.7.2.2 Bad Calls 343</p> <p>19.7.2.3 Distribution of Power 343</p> <p>19.7.2.4 Unemployment 343</p> <p>19.8 Intelligent Mobile Applications Drive Growth in Banking 344</p> <p>19.8.1 Investment 344</p> <p>19.8.2 Accounting 344</p> <p>19.8.3 Banking Apps 345</p> <p>19.8.4 Digital Wallet Apps 345</p> <p>19.9 Conclusion 345</p> <p>References 346</p> <p><b>20 The Potential of Artificial Intelligence in Public Healthcare Industry 349<br /></b><i>Megha Shrivastava and Devendra Kumar</i></p> <p>20.1 Introduction 350</p> <p>20.1.1 Drug Discovery 350</p> <p>20.1.1.1 The Main Stages of Drug Discovery Might Take Several Years in Completion 351</p> <p>20.1.1.2 Companies or Startups Used AI Techniques for Drug Discovery 351</p> <p>20.1.2 Medical Imaging 352</p> <p>20.1.2.1 Areas of Medical Imaging 352</p> <p>20.1.2.2 Some Applications for AI in Medical Imaging Are at Present Applied in General Healthcare 353</p> <p>20.1.3 Disease Prevention 354</p> <p>20.1.3.1 Areas of Disease Prevention, Supported by AI System 354</p> <p>20.1.3.2 Some Recent Software Used for Disease Prevention 354</p> <p>20.1.4 Medical Diagnosis 355</p> <p>20.1.4.1 Categories of AI Tools for Disease Diagnosis 355</p> <p>20.1.4.2 Software Developed for Disease Diagnosis 356</p> <p>20.1.4.3 Making Smartphone as Powerful Diagnostic Tools 357</p> <p>20.1.5 Robotic AI 357</p> <p>20.2 The Future of Artificial Intelligence in Healthcare 358</p> <p>References 359</p> <p><b>21 Banks to Lead Digital Transformation With Artificial Intelligence 361<br /></b><i>Lavika Jaroli, Sachin Gupta and Parul Dashora</i></p> <p>21.1 Artificial Intelligence 362</p> <p>21.1.1 Human Versus Artificial Intelligence 363</p> <p>21.1.2 Difference Between AI, NLP, NN, ML, or DL 363</p> <p>21.1.3 Types of Artificial Intelligence 365</p> <p>21.1.4 Innovations in Indian Banking Through IT 366</p> <p>21.1.5 A Short History of Artificial Intelligence 366</p> <p>21.2 Artificial Intelligence History Timeline 367</p> <p>21.2.1 Objectives 367</p> <p>21.2.2 Scope 367</p> <p>21.2.3 Methodology 369</p> <p>21.3 Why Artificial Intelligence in Banks 369</p> <p>21.4 Goal of Artificial Intelligence 370</p> <p>21.4.1 Innovations in Indian Banking Through IT 370</p> <p>21.4.2 Innovation in Indian Banking Sectors 370</p> <p>21.5 Artificial Intelligences Using by Different Banks 372</p> <p>21.6 Implementation of Artificial Intelligence in Banking 375</p> <p>21.7 Path Ahead Chatbots in Banking 377</p> <p>21.8 Advantage of Artificial Intelligence in Banking Sector 379</p> <p>21.9 Types of Risks and Threats Associated With Banking 380</p> <p>21.10 Nature of Risks in Wireless Banking 380</p> <p>21.11 Advent of Information Technology in Indian Banking Sector 383</p> <p>21.12 Future Scope of AI 384</p> <p>21.13 Conclusion 384</p> <p>References 384</p> <p><b>22 Effectiveness of E-HRM Tools Using the Functionalities of Artificial Intelligence During Remote Working in Lockdown Period 387<br /></b><i>Nidhi Saxena and Aditi R. Khandelwal</i></p> <p>22.1 Introduction 388</p> <p>22.1.1 Artificial Intelligence in Electronic HR Management 389</p> <p>22.1.1.1 Prospective Employee Engagement and Development 389</p> <p>22.1.1.2 Employee Training 390</p> <p>22.1.1.3 Candidate Selection for Recruitment 390</p> <p>22.1.1.4 Development Needs of Employees 390</p> <p>22.2 Literature Review 390</p> <p>22.3 Objective of the Study 391</p> <p>22.4 Research Methodology 392</p> <p>22.5 Impact and Efficiency of AI-Enabled EHRM Tools in Work From Home Scenario Under Lockdown 392</p> <p>22.6 Conclusion 395</p> <p>Reading List 396</p> <p>Index 399</p>
<p><b> S. Balamurugan, PhD,</b> SMIEEE and ACM Distinguished Speaker, received his PhD from Anna University, India. He has published 57 books, 300+ international journals/conferences, and 100 patents. He is the Director of the Albert Einstein Engineering and Research Labs. He is also the Vice-Chairman of the Renewable Energy Society of India (RESI). He is serving as a research consultant to many companies, startups, SMEs, and MSMEs. He has received numerous awards for research at national and international levels.</p> <p><b>Sonal Pathak, PhD</b> is an associate professor at the Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India. <p><b>Anupriya Jain, PhD</b> is an associate professor at the Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India. <p><b>Sachin Gupta, PhD</b> is at the Department of Business Administration, Mohanlal Sukhadia University, Udaipur, Rajasthan, India. <p><b>Sachin Sharma</b> is an assistant professor at the Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India. <p><b>Sonia Duggal, PhD</b> is an assistant professor at the Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India.
<p><b>Discusses the impact of AI on organizational transformation which is a mix of computational techniques and management practices, with in-depth analysis about the role of automation & data management, and strategic management in relation to human capital, procurement & production, finance, and marketing. </b></p> <p>The impact of AI in restructuring organizational processes is a combination of management practices and computational technology. This book covers the areas like artificial intelligence & its impact on professions, as well as machine learning algorithms and technologies. The context of applications of AI in business process innovation primarily includes new business models, AI readiness and maturity at the organizational, technological, financial, and cultural levels. The book has extensive details on machine learning and the applications such as robotics, blockchain, Internet of Things. Also discussed are the influence of AI on financial strategies and policies, human skills & values, procurement innovation, production innovation, AI in marketing & sales platforms. <p><b> Audience </b> <p>Readers include those working in artificial intelligence, business management studies, technology engineers, senior executives, and human resource managers in all types of business.

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