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The usage of AI-powered chatbots and virtual assistants facilitates seamless communication, offering instant responses to inquiries and enhancing customer satisfaction. In Japan, the hospitality industry is at the forefront of this AI-driven transformation and through collaborations with technology companies, hotels are deploying AI-powered concierge services, smart room automation, and language translation systems to cater to diverse guest needs. The integration of AI in Japan's tourism sector not only enhances operational efficiency but also showcases the country's commitment to innovation and delivering exceptional customer experiences. As Japan embraces AI in its hospitality industry, it navigates the delicate balance between leveraging technology and preserving human interaction and by combining the efficiency and accuracy of AI with the warmth and personal touch of human hospitality, Japan aims to redefine the future of tourism. Moreover, AI streamlines operations by automating repetitive tasks, optimising resource allocation, and improving efficiency in areas such as reservation management, inventory control, and demand forecasting. However, along with these benefits, there are significant challenges to consider. Privacy concerns arise as AI systems collect and process personal data, necessitating robust security measures to protect sensitive information. Ethical considerations must also be addressed, as the use of AI raises questions about transparency, bias, and accountability. Furthermore, while AI enhances efficiency, there is a concern about losing the human touch that has long been a hallmark of the hospitality industry. Balancing the benefits of AI with maintaining personalised and authentic guest experiences becomes a crucial challenge.

Climate change requires society to focus more strongly on sustainability. This requires an adjustment both on the demand side and on the supply side. Consumers must be given incentives to optimise their consumption according to sustainability aspects. In the supply of capital goods and consumer goods, firms must do their part to ensure that environmental savings are made possible and cost-efficiency. However, there must be doubts that a more resource-efficient production technology leads to the desired environmental effects. Policymakers ignore the Jevon’s paradox. The Jevon’s paradox states that an improved technology that leads to resource savings disproportionately increases the intensity of use. In absolute terms, there is a higher consumption of resources after the technology is introduced. This effect is currently ignored, for example, by all forecasts on demand for lithium for electromobility. Regardless of this, it is fundamentally better to optimise the technologies. However, this raises the question of whether the Jevon’s paradox cannot be undermined by artificial intelligence. Artificial intelligence applied to production promises the possibility to replace partial optimisations with total optimisations. By pursuing an absolute maximum (maximum maximorum), the intensity of use is limited. Therefore, this chapter is concerned with understanding the primary effects of artificial intelligence in production and highlighting the potential effects on sustainability.

Purpose: Increasing the sustainability in industrial production is getting more and more important. Furthermore, the technology of artificial intelligence is getting more and more important as well. For this reason, it is time to understand how artificial intelligence and sustainability are linked with one another in the context of production.

Need for the study: This chapter aims to deliver a solid argumentation regarding the prospects and the relevance of the usage of artificial intelligence in the context of production. Moreover, it specifically aims to show how artificial intelligence affects the sustainability of production.

Method: Literature analysis.

Findings: The findings are that artificial intelligence does enforce cooperative action within the industry via the effects on productivity variables, transaction costs, and production elasticities. Furthermore, the Jevon’s paradox does not seem to apply to artificial intelligence. Therefore, it is suggested that more empirical research has to focus on this topic.

Practical Implications: This chapter highlights the importance of artificial intelligence for the topic of sustainability.

Artificial Intelligence (AI) is one of the newest technology that is quickly advancing and can be utilised to improve human resource competence in the age of rapid digital transformation. The present competitive scenario demands accurate data that need to be collected and analysed for organisational growth.

Purpose: The research examines the applications and usage of AI in performance management and further analyses the future of PM from the perspectives of AI.

Methodology: The study is conceptual and relies on secondary data from research papers, publications, HR blogs, survey reports and other sources. Employee performance and attitudes were monitored using digital technologies, big data analytics and AI. The quality of employee performance continues to increase with the integration of AI, enabling predictive analytics to increase employee performance.

Research Implication: In employee performance appraisal, a digital performance management system leads to openness and honesty with time, effort and sincerity. It is based on the performance management system’s practical usefulness.

Theoretical Implication: The study’s findings provide HR managers, academics, IT professionals and practitioners with an understanding of how AI may be used for performance management and its consequences on their operations. In addition, the connection between the HR devolution theory on performance management and AI is discussed.

The COVID-19 pandemic ushered in multiple challenges for employees, which led to employee turnover, disengagement at work, employees’ mental health issues, etc. The study tries to elucidate how artificial intelligence (AI) herald great promise in human resource management in decreasing cost, attrition level and enhancing productivity. Considering the dearth of studies on recent trends in human resource management (HRM) in the context of AI, the study elucidates the role of AI in facilitating seamless onboarding, diversity and inclusion (D&I), work engagement, emotional intelligence and employees’ mental health. Thus, a conceptual model of recent trends in HRM in the context of AI and its organisational outcomes is proposed. A systematic review and meta-synthesis method are undertaken. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes. The findings of the study suggest that using natural language processing (NLP) and robots has eased the onboarding process. D&I is promoted using data analytics, big data, machine learning, predictive analysis and NLP. Furthermore, NLP and data analytics have proved to be highly effective in engaging employees. Emotional Intelligence is applied through AI simulation and intelligent robots. On the other hand, chatbots, employee pulse surveys, wearable technology, and intelligent robots have paved way for employees’ mental health. The study also reveals that using AI in HRM leads to enhanced organisational performance, reduced cost and decreased intention to quit the organisation. Thus, AI in HRM provides a competitive edge to organisations by enhancing the performance of the employees.

This chapter attempts to provide answers to the following questions:

• What is artificial intelligence (AI)? Moreover, what is AI-based retail innovation?

• How does AI work?

• What are the applications of AI in retail services innovation?

• What are the ethical aspects, considerations and issues regarding the employment of AI in retail?

What is artificial intelligence (AI)? Moreover, what is AI-based retail innovation?

How does AI work?

What are the applications of AI in retail services innovation?

What are the ethical aspects, considerations and issues regarding the employment of AI in retail?

Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

Purpose: In recent times, ‘artificial intelligence (AI)’ has been pervasive even in organisations or at home. AI is defined as programming computers or other technological devices to act, react, respond, or assist the same way humans do. AI has undeniably made people’s lives easier. In organisations, the impact of AI is even more visible. The main aim of this chapter is to examine the significant role of future work skill’s (FWS) each component in the field of on-growing automation. The focus will be especially on emotional and social intelligence (ESI) (a key component of FWS) while adopting AI.

Need of the Study: In terms of human resource management (HRM), AI is useful for people management, payroll services, staff monitoring and improving the recruiting network, among other things. Even managers put their organisation’s job openings on the web and get applicant resumes electronically. People and employees in the organisation have become more advanced and innovative due to AI. A device obtains employee attendance, and human resource (HR) can track their employees and their organisation’s workforce data. HR has now been awarded more authority to manage and fix their employee’s problems because of AI. In a rapidly changing world, AI is affecting all aspects. AI is yearning to automate all of the jobs.

Methodology: Now a question arises how we can stay relevant in AI economic development? As humans, we learned that every issue is a problem of optimisation because we simply require human skills to develop, create and innovate new things. Therefore, researchers recognised that adopting sustainable growth skills encourages people to continue learning throughout their lives. Moreover, AI has enabled machines the ability to learn over time. Still, they will never be able to develop new ideas like human intelligence. A machine can use only one fixed data algorithm. Now humans have made significant progress in various fields with the help of FWS; without integrated computer sciences, brain science would not make such an outstanding achievement. On the other hand, human minds are masters of their intelligence, such as creativity, complex problem-solving, cognitive thinking, ESI and communication. Breakthrough human mind are masters of algorithms represented people have to understand new trends of technology around us, and the best way to move forward is to be aware, adapt and update skills.

Practical Implications: However, AI is required because, regardless of technological advancements, AI is leading Industry 4.0. The industry’s transformation is in 4.0, and hopefully, 5.0 will jump on board soon. Undoubtedly, AI should streamline the process and eliminate redundancy or administrative tasks.

Finding: AI can be more effective in organisations if they incorporate other FWS, particularly the soft human ESI skills, whereas AI is present everywhere, we can still not neglect FWS, especially ESI. So, this chapter highlights the important role of soft skills, that is, ESI and FWS, while adapting AI for an effective HRM.