Impact of Artificial Intelligence on Organizational Transformation E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Artificial Intelligence and Soft Computing for Industrial Transformation
- Sprache: Englisch
IMPACT OF ARTIFICIAL INTELLIGENCE ON ORGANIZATIONAL TRANSFORMATION 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. 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. Audience 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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Veröffentlichungsjahr: 2022
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Table of Contents
Cover
Title page
Copyright
Foreword
Preface
1 Artificial Intelligence Disruption on the Brink of Revolutionizing HR and Marketing Functions
1.1 Introduction
1.2 Research Methodology
1.3 Artificial Intelligence in HRM
1.4 Artificial Intelligence in Marketing
1.5 Discussion and Findings
1.6 Implication for Managers
1.7 Conclusion
References
2 Ring Trading to Algo Trading—A Paradigm Shift Made Possible by Artificial Intelligence
2.1 Introduction
2.2 Ring Trading
2.3 Features of Generation 1: Ring Trading
2.4 Generation 2: Shifting to Online Platform
2.5 Generation 3: Algo Trading
2.6 Artificial Intelligence
2.7 AI Stock Trading
2.8 Algorithmic (Algo Trading) Trading
2.9 Conclusion
References
3 AI in HR a
Fairy Tale
of Combining People, Process, and Technology in Managing the Human Resource
3.1 Introduction
3.2 Problem Recognition
3.3 Journey of AI in HR “From Where Till What”
3.4 Work Methodology of AI in HR
3.5 Branches of AI in HR
3.6 Implication Stages of AI in HR
3.7 Process Model of AI in HR
3.8 Key Roles of AI in HRM
3.9 Broad Area of Uses of AI in HR
3.10 Dark Side of AI
3.11 Conclusion
References
4 Effect of Artificial Intelligence on Human Resource Profession: A Paradigm Shift
4.1 Introduction
4.2 Evolution of Artificial Intelligence
4.3 Changing Role of Human Resource Professionals
4.4 Effect of Artificial Intelligence on Human Resource Profession
4.5 Limitations of Artificial Intelligence in HRM
4.6 Conclusion
References
5 Artificial Intelligence in Animal Surveillance and Conservation
5.1 History
5.2 Introduction
5.3 Need of Artificial Intelligence
5.4 Applications of AI in Animal Surveillance and Conservation
5.5 Some Other Tools of Artificial Intelligence
References
6 Impact of Artificial Intelligence on Digital Marketing
6.1 Introduction
6.2 The Impact That AI Has on Marketing
6.3 The Community Regulation “GDPE” and Artificial Intelligence: Here’s How Technology is Governed
6.4 The Case Study Estée Lauder
6.5 Conclusion
References
7 Role of Artificial Intelligence in Transforming the Face of Banking Organizations
7.1 Objectives
7.2 Introduction
7.3 Existing Technology
7.4 Methodology
7.5 Findings
7.6 Conclusion
7.7 Suggestions
References
8 Artificial Intelligence and Energy Sector
8.1 Introduction
8.2 Challenges of Indian Power Sector
8.3 Artificial Intelligence for Energy Solutions
References
9 Impact of Artificial Intelligence on Development and Growth of Entrepreneurship
9.1 Introduction
9.2 Entrepreneurship
9.3 Artificial Intelligence
9.4 Artificial Intelligence and Entrepreneurship
9.5 Process of Entrepreneurship
9.6 The Need of Artificial Intelligence for Business Development
9.7 Some Important Facts About AI
9.8 Opportunities for Artificial Intelligence in Business
9.9 Further Research Possibilities
9.10 Conclusion
References
10 An Exploratory Study on Role of Artificial Intelligence in Overcoming Biases to Promote Diversity and Inclusion Practices
10.1 Introduction
10.2 Research Gaps Identified
10.3 Experiential Work
10.4 Synthesis of the Study
10.5 Managerial Implications and Conclusion
References
11 Artificial Intelligence: Revolutionizing India Byte by Byte
11.1 Introduction
11.2 Objectives of the Chapter
11.3 AI for India’s Transformation
11.4 Economic Impact of Artificial Intelligence
11.5 Artificial Intelligence and its Impact on Various Sectors
11.6 SWOT Analysis of Artificial Intelligence
11.7 Conclusion
References
12 AI: A New Strategic Method for Marketing and Sales Platforms
12.1 Introduction
12.2 Objectives of the Chapter
12.3 Importance of Artificial Intelligence
12.4 Research Methodology
12.5 AI: The Ultimate B2B Growth Accelerator
12.6 The Existing Methods of Marketing and Sales
12.7 AI Will Shape Marketing Strategies of Startup in the Future
12.8 Artificial Intelligence is Shaking up the Job Market
12.9 The Role of Artificial Intelligence and Machine Learning on Marketing
12.10 Conclusion
References
Website
13 Brain and Behavior: Blending of Human and Artificial Minds Toward Stress Recognition and Intervention in Organizational Well-Being
13.1 Introduction
13.2 Research Methodology
13.3 Fundamentals of Stress
13.4 Embracing AI Opportunity in Stress Management Interventions
13.5 Existing Technology for Stress Recognition
13.6 Discussion and Findings
13.7 An AI—Eye to the Future
13.8 Conclusion
13.9 Limitations of AI in Human Resource Management
13.10 Conclusion
References
14 Alternative Financing
14.1 Introduction
14.2 Alternative Financing
14.3 Models of Alternative Financing
14.4 Scope of Alternative Financing in India
14.5 Alternative Finance as a Tool of Financial Inclusion
14.6 Regulation of Alternative Finance
References
Further Web Links
Dissertation
15 Application of Machine Learning in Open Government Database
15.1 Introduction
15.2 Literature Review
15.3 Overview of Open Government Data
15.4 Open Government Data in India
15.5 How to Create Value from Data
15.6 Artificial Intelligence
15.7 Why AI is Important?
15.8 Machine Learning
15.9 Concerns About Machine Learning on Government Database
15.10 Conclusion
References
16 Artificial Intelligence: An Asset for the Financial Sector
16.1 Introduction
16.2 Types, Technology, and Application of AI
16.3 Artificial Intelligence and Financial Services
16.4 Conclusion
16.5 Glossary
References
Bibliography
17 Artificial Intelligence With Special Reference to Blockchain Technology: A Future of Accounting
17.1 Introduction
17.2 Objectives
17.3 Literature Review
17.4 Research Methodology
17.5 Usage of Artificial Intelligence in Accounting
17.6 Usage of Blockchain in Accounting
17.7 Impact of AI on the Field of HRM
17.8 Challenges in Execution
17.9 Conclusion
References
18 AI-Implanted E-Learning 4.0: A New Paradigm in Higher Education
18.1 Introduction
18.2 Research Methodology
18.3 Progression of Web and E-Learning
18.4 Artificial Intelligence in Learning
18.5 Impact of Artificial Intelligence in Education (AIEd)
18.6 Conclusion
Concise Summary
References
19 Artificial Intelligence in Banking Industry
19.1 Introduction
19.2 Banking on Artificial Intelligence
19.3 Role of Artificial Intelligence in Shaping Indian Banking Industry
19.4 Influence of Artificial Intelligence on Indian Banking Industry
19.5 Reasons Behind Elongated Adoption of Artificial Intelligence in Banking Industry
19.6 Indian Banks Using Artificial Intelligence
19.7 Pros and Cons of Artificial Intelligence in Banking Sector
19.8 Intelligent Mobile Applications Drive Growth in Banking
19.9 Conclusion
References
20 The Potential of Artificial Intelligence in Public Healthcare Industry
20.1 Introduction
20.2 The Future of Artificial Intelligence in Healthcare
References
21 Banks to Lead Digital Transformation With Artificial Intelligence
21.1 Artificial Intelligence
21.2 Artificial Intelligence History Timeline
21.3 Why Artificial Intelligence in Banks
21.4 Goal of Artificial Intelligence
21.5 Artificial Intelligences Used by Different Banks
21.6 Implementation of Artificial Intelligence in Banking
21.7 Path Ahead Chatbots in Banking
21.8 Advantage of Artificial Intelligence in Banking Sector
21.9 Types of Risks and Threats Associated With Banking
21.10 Nature of Risks in Wireless Banking
21.11 Advent of Information Technology in Indian Banking Sector
21.12 Future Scope of AI
21.13 Conclusion
References
22 Effectiveness of E-HRM Tools Using the Functionalities of Artificial Intelligence During Remote Working in Lockdown Period
22.1 Introduction
22.2 Literature Review
22.3 Objective of the Study
22.4 Research Methodology
22.5 Impact and Efficiency of AI-Enabled EHRM Tools in Work From Home Scenario Under Lockdown
22.6 Conclusion
Reading List
Index
Also of Interest
End User License Agreement
Guide
Cover
Table of Contents
Title page
Copyright
Foreword
Preface
Begin Reading
Index
Also of Interest
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1 Benefits of Artificial Intelligence. Source: Deloitte 2017.
Figure 1.2 ANN for market segmentation.
Figure 1.3 Martec’s Law.
Chapter 3
Figure 3.1 The wastage of time in the duplication of work.
Figure 3.2 Use of AI in HR. Oracle AI usage in different business functions, sho...
Figure 3.3 Need of AI in HR. https://www.aihr.com/blog/ai-in-hr-impact-adoption-...
Figure 3.4 Branches of AI in HR and its uses. Source: Mckinsey Global Institute ...
Figure 3.5 Implication stages of AI in HR. Source: https://www.cmswire.com/digit...
Figure 3.6 Process model of AI in HR. https://www.aihr.com/blog/ai-in-hr-impact-...
Figure 3.7 Use of AI in HR.
Chapter 4
Figure 4.1 Evolution of Artificial Intelligence.
Figure 4.2 Phases of Artificial Intelligence.
Figure 4.3 The role of AI in Human Resource.
Figure 4.4 Effect of AI on Human Resource management.
Figure 4.5 Forecasting of Human Resource Professional.
Chapter 5
Image 5.1 John McCarthy (4 Sept. 1927-24 Oct. 2011).
Figure 5.1 Specifications of Artificial Intelligence.
Figure 5.2 Use of Artificial Intelligence in animal surveillance.
Image 5.2 RFID ear tag.
Image 5.3 Honey bee with radio chips.
Image 5.4 GPS tracker microchip.
Image 5.5 Drone with thermal camera.
Image 5.6 Motion sensor camera.
Image 5.7 Telemetry system [6].
Image 5.8 Bird ringing [10].
Image 5.9 Audio moth [11].
Image 5.10 Transponder [12].
Image 5.11 Trail guard.
Chapter 8
Figure 8.1 Increase in the demand for power since 1996 to 2018. Source: Annual R...
Figure 8.2 Growth in installed capacity during planning period. Source: Central ...
Chapter 9
Figure 9.1 Benefits and challenges of artificial challenges. Source: Artificial ...
Chapter 10
Figure 10.1 Hypothetical research model for the study.
Figure 10.2 Flow diagram of literature selection process. Source: compiled by re...
Figure 10.3 Diversity iceberg.
Figure 10.4 Benefits of diversity.
Figure 10.5 Ensuring responsible AI.
Chapter 11
Figure 11.1 What is Artificial Intelligence. Source: NITI Aayog Discussion Paper...
Figure 11.2 The branches of Artificial Intelligence. Source: Syam and Nguyen, 20...
Figure 11.3 India’s GVA in 2035. Source: The Financial Express, 2018 [4].
Figure 11.4 Relevance of AI in the healthcare industry. Source: NITI Aayog Repor...
Figure 11.5 Benefits from robotic process automation. Source: Asian Banker Resea...
Figure 11.6 AI in education. Source: Johnson, 2019 [7].
Figure 11.7 AI benefits in agriculture sector. Source: Revanth, 2019 [8].
Figure 11.8 Applications of AI to various sectors. Source: Syam and Nguyen, Ever...
Chapter 12
Figure 12.1 Marketing automation. Source: https://senitih.com [9].
Figure 12.2 AI inbuilt Robot. Source: Alex Knight | Unsplash.
Figure 12.3 Scoring in different sector. Source: McKinsey.
Figure 12.4 Growing and declining sectors. Source: https://www.weforum.org/agend...
Figure 12.5 Ranking of AI usage globally. Source: https://www.weforum.org/agenda...
Figure 12.6 Artificial Intelligence & Machine Learning. Source: https://www.graz...
Figure 12.7 AI marketing strategies. Source: https://www.grazitti.com/blog/the-i...
Chapter 13
Figure 13.1 Relationship of performance and stress. Source: www.psychology.stack...
Figure 13.2 Biofeedback detection system. Source: www.frontiersin.org/journals/i...
Figure 13.3 Empatica sensor-based wrist device. Source: https://tatourian.blog/2...
Chapter 14
Figure 14.1 Alternative finance over the years. Source: https://www.jbs.cam.ac.u...
Figure 14.2 Alternative finance’s market in India. Source: https://www.jbs.cam.a...
Figure 14.3 Changes in business model and product innovation in India. Source: h...
Chapter 15
Figure 15.1 Open government data principles. Source: http://resource.org/8_princ...
Figure 15.2 Seven characteristics for measuring the openness of data [Source: Je...
Figure 15.3 Data transformation in Open Government Databases page. Source: http:...
Figure 15.4 Illustration: Dispersion of dataset of hypothetical citizen X across...
Figure 15.5 Data processing (Source: www.sas.com).
Figure 15.6 Machine learning concept. Source: https://towardsdatascience.com/mac...
Figure 15.7 Data management (Source: www.sas.com).
Chapter 16
Figure 16.1 History of Artificial Intelligence. Source: Compiled by author.
Figure 16.2 Subfields of AI. Source: Compiled by author.
Figure 16.3 Impact of AI on Organisation. Source: Compiled by author.
Figure 16.4 Development of techniques of AI. Source: Compiled by author.
Figure 16.5 Types of insurance. Source: Compiled by author.
Figure 16.6 The transition of the insurance industry. Source: Compiled by author...
Figure 16.7 Insurance hardware devices. Source: https://marutitech.com/ai-in-the...
Figure 16.8 Investment process. Source: https://www.advisorkhoj.com/articles/Mut...
Figure 16.9 Stock Selection Strategy. Source: https://www.advisorkhoj.com/articl...
Chapter 18
Figure 18.1 Number of smartphone users worldwide from 2016 to 2021 (in billions)...
Figure 18.2 Cloud computing. Source: Researchers.
Figure 18.3 AIEd dimensions. Source: Researchers.
Chapter 19
Figure 19.1 Artificial intelligence and machine. Wohl, B. (2017, March 16). How ...
Figure 19.2 Reasons for AI-powered solution used in banking firms [2]. Source: h...
Figure 19.3 Anti-money laundering and AI. Ostos, G. F. A. A. R. (2020, August 27...
Figure 19.4 Automated chat system. E. (2021, March 10). Best 25 Raspberry Pi 4 P...
Figure 19.5 The rise of algorithm trading. Putnins, M. N. A. T. (2016, November ...
Figure 19.6 Fraud detection and AI.
Figure 19.7 Personalized banking and AI.
Figure 19.8 Digital banking. Agarwal, M. (2019, December 16). What Are The Most ...
Figure 19.9 Robo advisors for investments. Can Robo-Advisors change investment b...
List of Tables
Chapter 13
Table 13.1 Types of symptoms and outcomes.
Table 13.2 App-based interventions.
Chapter 14
Table 14.1 Traditional sources of finance.
Table 14.2 Conventional lending vs. alternative financing.
Table 14.3 Models of alternative finance.
Chapter 18
Table 18.1 Attributes of Web 1.0 to Web 3.0. Source: Dominic, M., Francis.
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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106
Artificial Intelligence and Soft Computing for Industrial Transformation
Series Editor: Dr S. Balamurugan ([email protected])
Scope: Artificial Intelligence and Soft Computing Techniques play an impeccable role in industrial transformation. The topics to be covered in this book series include Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Fuzzy Logic, Genetic Algorithms, Particle Swarm Optimization, Evolutionary Algorithms, Nature Inspired Algorithms, Simulated Annealing, Metaheuristics, Cuckoo Search, Firefly Optimization, Bio-inspired Algorithms, Ant Colony Optimization, Heuristic Search Techniques, Reinforcement Learning, Inductive Learning, Statistical Learning, Supervised and Unsupervised Learning, Association Learning and Clustering, Reasoning, Support Vector Machine, Differential Evolution Algorithms, Expert Systems, Neuro Fuzzy Hybrid Systems, Genetic Neuro Hybrid Systems, Genetic Fuzzy Hybrid Systems and other Hybridized Soft Computing Techniques and their applications for Industrial Transformation. The book series is aimed to provide comprehensive handbooks and reference books for the benefit of scientists, research scholars, students and industry professional working towards next generation industrial transformation.
Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])
Impact of Artificial Intelligence on Organizational Transformation
Edited by
S. Balamurugan
Sonal Pathak
Anupriya Jain
Sachin Gupta
Sachin Sharma
and
Sonia Duggal
This edition first published 2022 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA © 2022 Scrivener Publishing LLC For more information about Scrivener publications please visit www.scrivenerpublishing.com.
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-119-71017-2
Cover image: Pixabay.ComCover design by Russell Richardson
Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines
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10 9 8 7 6 5 4 3 2 1
Foreword
It gives me immense pleasure to write the foreword to this book. In choosing the impact of artificial intelligence on organizational transformation as their subject, the editors have selected a subject that has great contemporary relevance. Artificial intelligence is here to stay and will continue to flourish. It has come a long way since it was conceived a few decades back. Previously, its application was confined to automation in manufacturing only, but with the passage of time has expanded to cover almost every sphere of human activity.
Organizational transformation does not happen overnight. One has to steadily and meticulously strive and work hard to achieve it. Artificial intelligence is definitely contributing in a big way towards the organizational transformation of both the manufacturing and service sectors. Against this backdrop, I am optimistic that the book will make for interesting reading. I extend my best wishes to the entire editorial team for this sterling academic endeavor.
Prof. (Dr.) Karunesh SaxenaVice Chancellor Sangam University Bhilwara, Rajasthan, India October 2021
Preface
The idea of a book on the impact of artificial intelligence (AI) on organizational transformation occurred to us almost simultaneously. Even though we realized putting together an edited volume on such an ever-evolving topic would not be an easy task, the capacity that AI has to significantly transform organizations is too important to ignore. Therefore, we started deliberating as to how to include scholarly research articles written by eminent academicians on the topic. The outcome of our deliberations can be seen in the quality of the chapters included in this book, which highlight the applications and interlinkages of artificial intelligence with HR function, and its application in the banking and finance sector, along with many other diverse sectors such as energy and sports. One of the chapters even discusses how AI is revolutionizing India byte by byte.
All of us are highly grateful to the authors for taking time to contribute to this book despite the tense situation caused by the lockdown due to the COVID-19 pandemic.
The EditorsOctober 2021
1Artificial Intelligence Disruption on the Brink of Revolutionizing HR and Marketing Functions
Akansha Mer1* and Amarpreet Singh Virdi2†
1Department of Commerce and Management, Banasthali Vidyapith, Rajasthan, India
2Department of Management Studies, Kumaun University, Bhimtal Campus, Uttarakhand, India
Abstract
Artificial Intelligence (AI) disruption is rapidly revolutionizing the various functions of HR, marketing, finance, etc. Before the advent of AI, several biases occurred on part of humans in terms of hiring, promotion, performance appraisal, compensation, etc. Similarly, in marketing, the customers’ needs and wants are of immense importance for marketers. Traditional marketing generally used feedback from consumers and also the managers had to rely on the market research to interpret the market trends, customers’ needs, tastes, and preferences. But now AI disruption has addressed the HR issues and made substantial improvements in the prediction of precise trends, customer purchase intention, and consumer behavior.
Thus, the paper attempts to unravel how AI is revolutionizing the various functions of HR and marketing. The study elucidates that AI has revolutionized the functions of HR by removing biases in recruitment and performance appraisal and is assisting the organizations in employee engagement and retention. It has made the orientation and onboarding process easy. AI has widely reduced the cost of the organizations with respect to hiring, training, etc. Similarly, in the field of marketing, the study also elucidates that with the advent of technological advancement during recent times (AI), a wealth of information about the consumers, their consumption patterns, and purchase behavior can be traced to a large extent. AI has opened an opportunity for marketers to enhance the effectiveness of the marketing campaigns which can be measured as a return on investment (ROI). AI is enhancing the marketing strategies for businesses. AI disruption is helping in quick and effective decisions. AI is optimizing the advertising and customer segmentation and is also helping companies with better product design to the delight of the customers.
Thus, the managers should look to AI as a tool for empowering and supporting their employees rather than replacing them. Since AI automates various process-oriented and administrative tasks, therefore managers should adopt AI so that they may shift their focus from administrative tasks to cross-functional reasoning tasks. Such a human-machine association will generate various new jobs and will pave way for innovation.
Keywords: Artificial intelligence, disruption, HR, marketing, chatbots, algorithms, machine learning
1.1 Introduction
Artificial Intelligence (AI) that was coined by McCarthy [3] is a branch of computer science encompassing areas such as machine learning (ML) and cognitive computing. AI can also be divided into the categories as strong AI, weak AI, and super intelligent AI. The strong AI or Artificial General Intelligence (AGI) refers to a system with logic, sensory and cognitive abilities that rely on the association of data to produce human brain-like decisions. The weak AI or Artificial Narrow Intelligence (ANI) is the system that focuses on a single task and work in a particular domain [34]. Super intelligent AI is a futuristic system that shall surpass the cognitive abilities and intelligence of human beings.
The study by Carbonell et al. has mentioned that ML is a basic requirement for the generation and development of AI [8]. The prominent ML tools are as follows:
a) Neural Network or Artificial Neural Network (ANN): It comprises of many interconnected nodes (like neurons in the brain) and works on the rules that define what kind of output to be generated based on input.
b) Support Vector Machine (SVM): It is used for predicting time series predictions.
c) Natural Language Processing (NLP): It consists of a) Natural Language Understanding (NLU) and b) Natural Language Generation (NLG). NLU converts the natural language into computer language; therefore, it is termed as Speech Recognition or speech to text conversion. It uses Hidden Markov Model (HMM).
According to Merriam Webster.com, “Artificial Intelligence is a branch of computer science dealing with the simulation of intelligent behavior in computers.”
According to John McCarthy, AI is “the science and engineering of making intelligent machines, especially intelligent computer programs” [22]. AI simulates intelligent behavior in computers. In ML, the machine learns on its own based on patterns and training data sets. It enables machines to process like the human brain.
It is revolutionizing various industries. The study conducted by Xaxis [35] concluded that AI will be the next industrial revolution. The economic impact of AI is estimated to reach 13 trillion dollars by 2030 [7].
A survey conducted by Deloitte on 250 executives on the benefits endowed by AI revealed that 51% of the executives were of the view that AI enhances the features, functions, and performance of the product, 36% of the employees were of the view that AI optimizes internal business operations, 36% of employees indicated that AI frees up the workforce to be more creative by automating tasks, 35% indicated that AI assists in making better decisions, 32% of the employees revealed that AI helps in creating new products, 30% of employees suggested that AI helps in optimizing external processes like marketing and sales, 25% of employees were of the view that AI helps in pursuing new markets, 25% revealed that AI helps in capturing and applying scarce knowledge where needed, whereas only 22% of employees indicated that AI reduced headcount through automation [9]. Figure 1.1 depicts the benefits endowed by AI on organizations. Thus, it can be seen that no aspect of management has been left untouched by AI. AI is gaining prominence in various managerial functions like HR, finance, and marketing. AI brings with it personalized experience.
A study carried by Oracle and human resources advisory and research firm, Future Workplace revealed that 80% of Asia Pacific (APAC) countries surveyed indicated that 50% of their employees are currently availing AI in some or the other form in their organization. The results also indicate that 77% of employees in China and 78% of employees in India have adopted AI which is more than double the 32% in France and 38% in the United Kingdom [23].
Figure 1.1 Benefits of Artificial Intelligence. Source: Deloitte 2017.
1.2 Research Methodology
The study is exploratory in nature. The researchers have explored various studies on the role of AI in the various functions of HR and marketing.
1.2.1 Research Objectives
To explore how AI disruption is revolutionizing HR functions.
To explore how AI disruption is revolutionizing marketing functions.
1.2.2 Data Collection
The study is based on secondary data, sourced from various databases like Ebsco, Google Scholar, and ProQuest.
1.3 Artificial Intelligence in HRM
Research suggests that biasness creeps in when humans are assigned the task of hiring, promotion, performance appraisal, compensation, etc. For instance, racial discrimination occurs when humans are assigned the task of hiring [29]. Another study conducted by Mckinsey and Leanln revealed that entry-level women faced discrimination during the promotion as against their male counterparts [20]. Employees also face discrimination during performance appraisal on grounds of their age [33]. Research also suggests that women face discrimination while receiving compensation and promotion [18]. AI helps in overcoming such biasness. AI is used in all the aspects of HRM like recruitment, engaging the applicants and the employees, orientation, onboarding, performance evaluation, training, compensation, and employee retention. These aspects are discussed below in detail.
1.3.1 Recruitment
As against the traditional recruitment process, recruiters are now using chatbots that are powered by AI (ML) [10]. Chatbots use natural language processing to facilitate real-time interaction with the applicants through skype, email, social media, etc. They are useful in gathering a pool of information from the applicants regarding their competencies, qualification, and experience and can even generate their profile, based on the information gathered. They are programmed in such a way that they can comprehend written and oral communication and can address routine queries of the applicants appropriately. Furthermore, these chatbots are efficient enough to even prescreen potential job applicants by matching their competencies, traits, experience, culture fit, etc., with the open positions and can schedule an interview for the applicants. With the advent of AI in recruitment, the hiring process has become faster as it can auto-screen thousands of resumes in a minute which are free from biases. Examples of various chatbots used by organizations are a) IBM Watson Recruitment, b) Jobs Intelligence Maestro of DBS Bank, which has successfully decreased the time involved in screening per candidate from 32 minutes to 8 minutes [26], and c) Mya, which provides 24/7 support.
1.3.2 Engaging the Applicants and Employees
Earlier, when AI was not introduced in HR, engaging the employees was time-consuming. Now, various software backed by AI like chatbots and Applicant Tracking System can engage the applicants by addressing their routine queries on a real-time basis and update them regarding their current status. The striking feature of these chatbots is that they become robust and smarter with every interaction. Example of engaging the applicants: IBM uses Watson Candidate Assistant (WCA) to engage its applicants in personalized conversation and also suggests the job positions that resonate with their competencies and experiences in which they can excel. Such engagement is a win-win situation for both the applicants and the organization. The applicants feel delighted and the organizations also become free from committing costly hiring mistakes.
Example of engaging the employees: AI-backed Amber chatbot, which is used by Oyo, Marico Ltd., and many more, is instrumental in identifying disengaged workforce in the organization. Thus, the organizations can take measures to engage the disengaged workforce.
1.3.3 Orientation and Onboarding
Organizations organize orientation programs for acquainting the new joiners regarding the organizational culture, rules and regulations, employee benefits, etc. According to Miller, nearly 90% of the new joiners tend to miss some or the other details during the orientation program [27]. The organizations can overcome this problem by using chatbots that can answer all the queries of new joiners which they might miss during the orientation program.
The AI-backed programs are enhancing onboarding programs as well. With the help of chatbots, the newly joined employees can get all the information regarding whom to report, their team members, what work is assigned to them, etc. Example: Amber is a chatbot that is used by Oyo, Marico Ltd., and many more. Mr. Amit Prakash, Chief HR Officer of Marico Ltd., emphasized the importance of Amber in the onboarding process in Marico Ltd. He said, “When employees join us at different locations, the supervision for onboarding employees has to be better. On the day of joining, the new members are taken out for lunch with the supervisor. For me to get into that detail is difficult. Amber helps to manage this information with little effort” [1].
1.3.4 Performance Appraisal
Performance appraisal deals with gathering, analyzing, and assigning numerical values and grades to the performance of the employees. The numerical values and scores assigned by human beings for evaluating the performance may not be precise. To overcome this issue, the fuzzy logic approach is used for evaluating the performance of the employees. A study which employed hierarchical fuzzy influence approach, indicated that reasoning based on fuzzy models are more accurate in evaluating the performance of employees [4]. Studies suggest that performance appraisal based on fuzzy logic helps in drawing definite results from ambiguous information [25].
Furthermore, various chatbots are used in the process of performance appraisal. Example: Engazify is used for performance appraisal as it gives real-time feedback and appreciation to its workforce [2]. Besides, data analytics and big data are also used to evaluate the performance of the employees, wherein the grades and the ratings are assigned on a scientific basis. The process begins by feeding the integrated performance metrics into the analytics software to determine the ranks of the employees. Such automated performance appraisal is free from biases that may occur by human beings while assigning grades or while ranking and brings transparency in the appraisal system.
1.3.5 Training
In this era of disruptions, the concept of one size fits all (same course content) for the learners cannot be applicable. Through AI, the learning material can be personalized in accordance with the learner’s requirements (skill gaps). With the help of AI, suitable content can be recommended to the learners, based on their past behavior. Besides, several content creation algorithms can be used to auto-generate content. AI gives the flexibility to the employees to learn at their own pace. Studies indicate that the robot training instructor can track the daily learning status of the learners and can even compute the average value of the learners’ attention [17]. Based on the learning objectives entered by the employees, the robot training instructor can automatically complete the course. Thus, AI facilitates personalized learning.
Furthermore, a qualitative study conducted by IBM Smarter Workforce Institute on senior HR executives of IBM revealed that their organization is enhancing skills inference technology internally. Consequently, employees of IBM have access to their real-time skill insights through an expertise management interface, which is more accurate. AI skill inference technology also helps IBM to analyze the skills of its employees relative to business needs and can also compare the skill profile of its employees with its competitors. This helps IBM to bridge the skill gaps of its employees [15]. Another example of an AI system as used in the military is intelligent tutoring systems [21, 30].
1.3.6 Compensation
Some of the prominent organizations like Google and Tesla use techniques like big data, predictive analytics, and ML techniques to monitor the talent of their employees, and thus, based on their performance, they remunerate their employees. These companies are following the recommendations of the AI-backed software and thus ensure that their employees are not under or overpaid. Example: IBM uses an AI-powered decision support system which helps in the compensation planning of front-line employees and thereby overcomes the issue of underweighting or overweighting the critical data points [15].
1.3.7 Employee Retention
AI helps in employee retention by satisfying the employees through ensuring unbiased performance appraisal. Algorithms can predict as to which employee is likely to leave the organization. AI software can predict the likelihood of employee turnover by tracking their browsing history and emails. Organizations are also using AI-based mood meters which help in tracking the sentiments of their employees and assist the organization in identifying the causes of employee turnover. The organizations are also using predictive statistical models that help in forecasting the employees’ intention to quit the organization and thus help in preventing employee turnover [13].
1.4 Artificial Intelligence in Marketing
The marketing concept comprises of 4Ps, namely, Product, Price, Place, and Promotion. This concept is all about making customer the king, i.e., satisfying the needs, wants, and desires of the customers. The customer satisfaction, over the period, graduated to customer delight. The organizations can delight the customers only when the tastes, preferences, and behavioral aspects regarding their purchase can be traced or known. With the advent of technological advancement during recent times (AI), a wealth of information about the consumers, their consumption patterns, and purchase behavior can be traced to a large extent. The database can be created for the information collected about consumers. The pattern analysis using data mining techniques can reveal homogeneity and heterogeneity. This shall reveal the basis for segmenting the markets into a precise group of consumers/customers. The latest technological innovations especially AI have opened an opportunity for the marketers to enhance the effectiveness of marketing campaigns which can be measured as a return on investment (ROI). The application of AI in marketing and sales has the highest potential value, with estimates up to 2.6 trillion dollars [7]. Earlier marketing was a one-way communication or push the product to inform, persuade, and remind with catchy slogans/jingles. With the advent of AI, consumers can buy/sell anything from any part of the planet anytime. The studies show that “consumers today search much less on brand names than they did 10 years ago. If someone wants to buy shoes on Amazon, they are five to six times more likely to search by category name than by brand name and follow the recommendations suggested by the Amazon algorithms” [32]. The industries where the customers are large in numbers and need to interact frequently with customers have a high potential for using AI. Since the interaction between the two generates a huge amount of data [10], customers perceive AI at a very high level [12]. Potential message from an AI application is convincing when it pertains to the usage of the product or service, instead of why that product or service should be used [19].
AI algorithms can perform pre-defined tasks, for example, automated email replies, blocking of debit/credit cards, etc., and also these AI algorithms can analyze the customer data which can be in various forms, viz., text, voice, and facial expression.
Marketing has become a two-way communication which means consumer searches/transacts with the seller. Some of the ways in which AI can be used for marketing are as follows.
1.4.1 Creation of Customer Profiles/Market Segmentation
The customers’ needs and wants are of immense importance for marketers. Traditional marketing generally used the feedback from consumers’ and also the marketers had to rely on the data provided by the market research firms. With the advent of AI and more people inclined to use the digital platform to search for their requirements, the marketers can now precisely segregate the customers for their product/service requirements. The technological advancement has let the marketers collect the customer’s data such as customer’s name, mobile, email, gender, search pattern, and so on. With this data, marketers can create customer profiles. Therefore, the customers can be segmented and targeted for personalized promotions. It can also help in retaining the customers. Studies indicate that VPSAs (Virtual Personal Shopping Assistants) can predict and optimize the tastes and needs of customers [11]. Lucy: it is created by Equals3 and is named after the granddaughter of IBM’s founder Thomas Watson. It can analyze structured and unstructured data. It helps in segmentation, planning, and interaction with humans in an easy way. SOFMs (self-organizing feature maps) are used for market segmentation, i.e., portioning of a large market into small homogeneous groups of consumers.
Hidden Layer
Figure 1.2 ANN for market segmentation.
The market segmentation for an organization provides translate the opportunity for not only optimally utilizing the resources but also, at the same time, ensuring high profitability. But it remains a big challenge to translate the market’s needs in a precise manner. The ANN provides the solution with several methods developed over a period of time. The SOM (self-organized feature maps), GKA (genetic K-means algorithm), and ART (adaptive resonance theory) are some of the methods used for clustering/segmentation.
An ANN can be constructed for segmenting the market, suppose the parameters for the customer are socio-economic factors, demographic factors, and so on (input layer). The organization aims to segment the market to two segments (output layer). The hidden layer contains the algorithms that result in an outcome. The same can be demonstrated as in Figure 1.2 [39].
1.4.2 Cognizance of Consumers Purchase Behavior/Intention
AI is helpful in comprehending the behavioral aspects of the customers. AI not only helps in understanding customer loyalty but also customer engagement. AI precisely predicts the CLV, i.e., customer lifetime value. This enables the organizations to maintain a better and attractive customer relationship with high valued customers. AI and ML can provide accurate recommendations to organizations on product features and display by pattern analysis of the behaviors of customers purchasing. This helps to improve the customer’s experience. AI is now able to analyze and understand human emotions such as delight, sadness, and anger. Ampsy uses hyper-local geo wall/fence to store publically shared content. This content is analyzed to understand consumer’s intention toward purchase. For example, Alibaba, the world’s largest e-commerce provider company uses AI to predict the pattern of customer purchase. Also, Alibaba is a solution provider to traffic maintenance with the help of AI [24].
1.4.3 Pricing
AI can help increase the sales of an organization by precisely the dynamic pricing. AI recommends the prices for the product and service by analyzing the demand/supply data. An app or website bot which keeps track of the history of sites and cookies can be used for the predictive analysis, thereby enabling the customer to enjoy real-time pricing. For example, during the lean season, the hotel room’s occupancy reduces, and AI can recommend dynamic pricing/real-time competitive pricing. AI helps to provide dynamic pricing by analyzing the historical transactions, competitor’s pricing, customer’s preview/reaction on social platforms, etc. There are several AI platforms, for example, Wise Athena recommends pricing and advertising decisions. Navetti Price Point uses ML to recommend pricing. Perfect Price empowered by AI provides dynamic pricing for auto rentals [5].
1.4.4 Content/Product/Service Recommendations/Search Optimization
According to lexico.com, content marketing is “a type of marketing that involves the creation and sharing of online material (such as videos, blogs, and social media posts) that does not explicitly promote a brand but is intended to stimulate interest in its products or services.” In recent times, the marketers are using AI tools to write content/recommendations to the target audience based on their likes and dislikes. Some of the AI tools are Wordsmith, WordAi, Rocco, etc.; these tools help the marketers by creating the content which is known as Content Curation and Content Automation. The rationale of these tools is to provide organized and customized content to the target audience for better customer engagement. The recommender systems developed with AI can enrich the shopping experience of customers. For example, personalized recommendations suggested by Netflix and Spotify.
1.4.5 Sales Prediction Based on Consumer’s Demographics
Based on the analysis of data, AI can predict and prioritize sales leads. AI can estimate the probability of a purchase by a customer. AI and ML analyze the data from the emails and phone calls that are with the company. This analysis can predict the present and future sales trends. Pointillist’s Behavioral Marketing Platform discovers and analyzes the path and patterns of behavior of the consumer to predict sales. Dominos uses AI tool called Dom Pizza Tracker. According to its website, in-store cameras “use advanced machine learning, artificial intelligence, and sensor technology to identify pizza type, even topping distribution and correct toppings”.
1.4.6 Virtual Assistants/Real-Time Conversations
AIs, known as chatbots like Alexa, Google Assistant, and Siri, are voice recognition technology that can understand and recognize speech or spoken words and execute the command from the internet through an AI drive assistant. For example, Indian Railways use chatbots as ask Deesha, etc. These chatbots simulate the natural language simulation and usually are prepared to answer the FAQs. This can reduce human intervention and reduce response time. Google is incorporating and innovating the use of AI and ML. Google’s division Waymo is working on AI for self-driving technology for automobiles. While Google Duplex has introduced the voice interface with the help of AI to automate phone calls. Amazon has introduced the AI-based voice assistant, Alexa. Also, Amazon is using AI to beforehand predict the products required by the customers. Microsoft is using AI in developing intelligent capabilities in its products and services, such as Cortana, Skype, and Bing [24].
1.4.7 Visual Searching
ML and AI provide the platform to the customers to search for the product with the help of a picture. It is far advanced from text-based searches. Pinterest CEO, Ben Silbermann predicts, “The future of search will be about pictures rather than keywords” [38]. For example, ZALORA online fashion retailer has a catalog of 3,000+ brands on their website. By implementing Search by Image (Visual Searching) and Visually Similar Product Recommendations, Zalora enabled a better search experience for its customers. Facebook uses Deep Text, an AI-based application to interpret the content of the posts, which can be in any language. Another application DeepFace is used to recognize the face of a person in a photo. Apple uses AI and ML in its products, for example, iPhone has the feature of face recognition, voice assistant Siri, etc.
1.4.8 CRM
AI is changing the scenario toward the customer relationship with the organizations. AI helps decode and provide insights into the customer behavior, patterns of purchase by analyzing the emails, telephonic conversations, chatbots, etc. Cogito provides the analysis of telephonic conversations and provides the customer’s emotional state. AI is also capable of detecting anomalies and duplicacy in CRM data. Amplero, a platform based on ML, works for the customer relationship management (CRM) domain. Salesforce Einstein is the AI platform for CRM, which provides solutions for the prediction of customer behavior and purchase patterns. It is used for data mining, deep learning, and NLP.
1.5 Discussion and Findings
The study attempted to unravel how AI disruption is revolutionizing HR and marketing. Our contribution is an exploration of various studies on the role of AI in the various functions of HR and marketing. The study revealed that AI in the field of HR has facilitated quality hiring [17, 30], personalized training [17, 31], ensured transparency in compensation management [17], and performance management [14, 17]. AI is also helping in removing biasness in recruitment and performance appraisal and is assisting the organizations in employee retention. Furthermore, both the candidates and the employees feel engaged. Besides, AI has widely reduced the cost of the organizations with respect to hiring, orientation, onboarding, training, etc.
As regards marketing, AI has transformed the way marketing was done traditionally. AI has facilitated the marketers to satiate the ever-demanding customers and steep rise in competition. These findings suggest that substantial improvement in the prediction of precise trends, customer purchase intention, and consumer behavior has become possible with AI and ML and therefore has improved the ROI for the organizations. The AI has reduced the time and the efforts, which were earlier used to collect the data and analyze the data and further processing [16]. From the consumer’s point of view, AI has offered several advantages as convenient shopping and after-sales service. Further, AI has improved the marketing mix as the development of the new product, automatic recommendations, dynamic pricing, and availability of product/service at any place and at any time (mostly, 24/7), creation of personalized advertisement communication and other personalized promotional offers. The results of this study have provided strong evidence in support of AI and ML can enhance the marketing results. The study “Lessons of 21st-Century Brands Modern Brands & AI Report (17 pp., PDF, free, opt-in)” concluded, “AI enables marketers to increase sales (52%), increase in customer retention (51%), and succeed at new product launches (49%). AI is making solid contributions to improving lead quality, persona development, segmentation, pricing, and service.” Internet marketers can now focus on heavy internet users for the products and services offered on e-commerce sites. The AI and ML should be used in marketing analytics to achieve better ROI [37].
1.6 Implication for Managers
AI is influencing various functions of management. The AI can help managers especially in human resource management and marketing management. Earlier, the HR managers had to spend a lot of time in screening various candidates manually. Similarly, biasness prevailed in recruitment, performance appraisal process, etc. Now, the managers can use AI to overcome issues of biasness. With the advent of AI in HR, the recruitment and hiring process has become faster as AI can auto screen thousands of resumes in a minute which are free from biasness. Besides, the managers can also use AI for engaging its workforce and employee retention. The orientation and onboarding processes have become easy.
In marketing management, earlier, the managers had to rely on the market research, data mining to interpret the market trends, customer’s needs, taste, and preferences. The AI has made possible the above interpretations in the real-time scenario. As it can precisely estimate the probability of a customer making a purchase and also can predict the customer value [36]. The benefits of using AI and ML in marketing is improved efficiency and optimal utilization of marketing efforts and resources, time-saving, creation of better customer profiles, and transforming customer satisfaction into customer delight [28].
Figure 1.3 Martec’s Law.
AI offers quality and quick decision-making to the managers. The managers should look to AI as a tool for empowering and supporting them rather than replacing them. Thus, the managers should adopt AI in various aspects of management like HR, marketing, finance, etc. Since AI automates various process-oriented task administration tasks, therefore managers should adopt AI so that they may shift their focus from administrative tasks to cross-functional reasoning tasks. Such a human-machine association will generate various new jobs and will pave way for innovation.
But technology is changing at a fast pace. Since the concept of AI implementation is a capital-intensive activity and continuous up-gradation is required. According to Martec’s Law, “technology changes exponentially, organizations change logarithmically” [6], as depicted in Figure 1.3. This becomes a challenge for organizations from developing countries. Thus, managers in developing countries should try to keep pace with technological advances.
1.7 Conclusion
Thus, it can be concluded that AI disruption is rapidly revolutionizing the various functions of HR, marketing, finance, etc. AI in the field of HR has facilitated quality hiring and ensured transparency in compensation management and performance management. AI is also helping in removing biasness in recruitment and performance appraisal and is assisting the organizations in employee retention. AI has widely reduced the cost of the organizations with respect to hiring, training, and engaging the employees.
Today, businesses are generating huge data, especially from the e-commerce segment. The companies can gain a competitive advantage with this data. AI and ML have paved the way to analyze, scrutinize, and draw precise inferences and recommendations. The AI is enhancing the marketing strategies for the businesses. AI disruption is helping in quick and effective decisions. ML is optimizing the advertising and customer segmentation. AI and ML are also helping companies with better product design to the delight of the customers. Therefore, the organizations should embrace AI for empowering and supporting their employees so that the focus of the employees shifts from administrative tasks to cross-functional reasoning tasks.
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2Ring Trading to Algo Trading—A Paradigm Shift Made Possible by Artificial Intelligence
Aditi R. Khandelwal
IIS Deemed to be University, Jaipur, India
Abstract
