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Introduction: The world is passing through a technology explosion phase where one technology is being replaced by another very quickly. Emerging technologies play more important roles in the insurance sector directly or indirectly. These technologies have a high potential to change the insurance paradigm.

Purpose: In this chapter, we discuss emerging technologies such as artificial intelligence (AI), big data, blockchain, the internet of things (IoT), mobile technology, predictive analytics, social media, telematics, chatbots, low codes, and drones in the context of the insurance industry.

Methodology: To carry out our analysis, we searched for data using the keywords for each technology from the Web of Science (WoS) coral database. Certain inclusion and exclusion criteria were followed to select the articles for further analysis. R-studio was used for the data analysis and visualisation.

Findings: It was found that the highest number of research articles published are related to big data, followed by AI and social media. The first article on AI in insurance appeared in 1975. Social media is the highest cited new technology, whereas the low codes are the undiscovered paradigm for the insurance sector with no published research. Research on the impact of chatbots, drones, and mobile technology in the insurance industry is still at a nascent stage. We also noticed that the United States is leading the research on emerging technologies in the insurance sector.

Implications: This chapter audits the emerging technologies in the insurance sector and identifies technological areas with the highest, least, or no research, dominant journals, authors, and countries. This holistic overview empowers managers and academicians to decide the future course of action.

Introduction: In a world characterised by volatility, uncertainty, complexity, and ambiguity, change is the only constant. Over the years, human resource management (HRM) has evolved from conventional functions of hiring and firing to being a strategic partner in organisations. Similarly, there has been a paradigm shift in the landscape of artificial intelligence (AI) from being a mere searching tool to the design and development of intelligent robots. Over the years, AI has emerged into a collection of powerful technologies re-inventing different functional areas, including HRM. The application of AI in HRM is perceived as an optimistic opportunity since it ought to bring maximum value at minimum cost. AI focuses on building tools that exhibit human-level intelligence and discernment in making decisions.

Purpose: The purpose of this chapter is to draw deeper insights into the relevance of AI in different functional areas of HRM. Integrating AI into HRM functions such as talent acquisition, training and development, performance management, employee engagement, and the like can help leverage efficiency and create an engaging employee experience. In the wake of Industry 4.0, where digitalisation has become imperative, this chapter explores the integration of AI into specific HR functions for a synergistic competitive advantage in companies. The purpose of this chapter is to signify the integration of AI into four vital functions of HRM, namely talent acquisition, training and development, performance management, and employee engagement. The objective is to chart how companies integrate various AI tools in four specific HRM functions to enhance efficiency. Also, the companies willing to implement AI in their HR functions can refer to the case studies used as exemplars in the chapter.

Methodology: This conceptual chapter is based on the secondary sources, which also build upon case studies of different companies that have implemented AI-enabled solutions and integrated them into different HRM functions and processes per needs. This chapter utilises the conceptual framework of both AI and HRM functions to give deeper insight into the challenges and implementation of technology-enabled solutions.

Findings: AI is used in HRM functions to automate repetitive and operational tasks to shift the focus to more strategic aspects. Despite many advantages of AI and machine learning, very few companies are using it, and companies may integrate technology-enabled solutions based on the size and nature of business.

Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything smarter than ever. IoT leads to a network of things which creates a self-configuring network. Improving farm productivity is essential to meet the rapidly growing demand for food. In this chapter, the authors have introduced a smart greenhouse by integration of two leading technologies in the market (i.e., Machine Learning and IoT). In proposed model, several sensors are used for data collection and managing the environment of greenhouse. The idea is to propose an IoT and Machine Learning based smart nursery that helps in healthy growing and monitoring of the seed. The structure will be a dome-like structure for observation and isolation of an egg with various sensors like pressure, humidity, temperature, light, moisture, conductivity, air quality, etc. to monitor the nursery internal environment and maintain the control and flow of water and other minerals inside the nursery. The nursery will have a solar panel from which it stores the electricity generated from the sun, a small fan to control the flow of air and pressure. A camera will also be equipped inside the nursery that will use computer vision technology to monitor the health of the plant and will be trained on the past data to notify the user if the plant is diseased or need attention.

This chapter presents the e-marketing practices followed by the micro, small and medium enterprises (MSMEs) in India. It explored the owner-managers perceptions of MSMEs regarding their average expenditures, budget allocations, management, policy, sources of information, return on investment and their desire for formal training on e-marketing activities in future. Data were collected from 253 MSME owner-managers through an e-questionnaire. The researchers found that the majority of the MSME owner-managers allocate a monthly budget for e-marketing initiatives, and they have increased it over the past few years. However, the total expenditure on e-marketing activities is between 1% and 10% of their total marketing budget. These businesses are partly or fully outsourcing search engine optimization (SEO), display advertising and referral marketing, whereas other e-marketing activities are managed in-house. Generally, these MSMEs are not measuring the success of their digital marketing efforts. If they do it, they are not doing it in a professional manner. MSMEs were found to be slow in posting content and engaging their followers on social media. Surprisingly, two-third of the MSMEs that participated in this study did not show any desire to pursue courses in digital marketing. In conclusion, this study puts forward key implications to practitioners as well as to the government agencies that are involved in the promotion of information technology among MSMEs.