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This paper aims to study the extent of use of artificial intelligence (AI) in the modern organization; to comprehend the changing nature of future jobs in the context of application of AI; and to study the impact of AI on the economy of the country with special reference to the job market. Given the critical scenario of labor intensive Indian economy, the paper intends to show how AI shall affect rather coexist with human intelligence or labor.

The research on implementation of AI in different industries and its effect on job market are at a nascent stage. There is a dearth of literature. Hence, this study followed a qualitative approach to have a better understanding of the research questions as Bhattacherjee (2012) confirms that employing an interpretive paradigm (qualitative analysis as the analysis of data, e.g. data from interview transcripts) is the more productive way to study social order and that it is achieved through “subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives”. Sample selection: The selection technique utilized is purposive sampling. The respondents in this research are the general managers and HRs from different companies. A total of 14 senior professionals from various sectors were approached for the interview out of which seven people gave their consent to take interview. Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally.

A country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al., 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al., 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ”

Prior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it.

The AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government.

The answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale.

A study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy.

This study aims to examine a hierarchical framework for sustainable consumption (SC) for cruise ships and identify the causal relationships and decisive attributes of cruise ship operation practices that allow cruise organizations to achieve a higher level of sustainable performance.

This study applies a hybrid of the Delphi method and a fuzzy decision-making trial and evaluation laboratory (DEMATEL). DEMATEL methodology helps to construct complex causal relations through digraphs, which depict interrelationships among attributes. The fuzzy set theory assesses experts’ perceptions of attributes given in linguistic preferences. The Delphi method has been previously used to validate attributes and determine the validity and reliability of the construct from qualitative information.

A set of three aspects containing 21 criteria were defined based on previous literature and expert consultations. The analysis results show that waste minimization and recycling and recovery are causal aspects that influence efficient resource use. Emission controls on ships, cruise ship alternative energy sources, ballast water treatment systems, water purification systems and nanofiltration systems are also prominent criteria for the improvement of SC during cruise ship operation.

This study contributes to the literature by offering a hierarchical framework for SC literature and confirming the role of this issue in improving the cruise industry sustainability. In practice, as such results provide key attributes for successful performance, the implications are offered for companies developing new activities, either in ensuring compliance with business goals or in decreasing the environmental impact.

Employability is a key concept in higher education. Graduate employment rate is often used to assess the quality of university provision, despite that employability and employment are two different concepts. This paper will increase the understandings of graduate employability through interpreting its meaning and whose responsibility for graduate employability from the perspectives of four key stakeholders: higher education institutions, students, government and employers.

There are two stages to this literature review which was undertaken across bibliographic databases. The first stage builds a conceptual understanding of employability, relating to definition and how employability can be achieved and enhanced from the perspective of stakeholders. A structured search employing Boolean searches was conducted using a range of terms associated with key stakeholders. The second round of review drew on documentary analysis of official statements, declarations, documents, reports and position papers issued by key stakeholders in the UK, available online.

It reveals that responsibility for employability has been transferred by the UK government to higher education institutions, despite clear evidence that it needs to be shared by all the key stakeholders to be effective. In addition, there is a gap between employers' expectation for employability and the government's employability agenda.

This article highlights that solely using employment rate statistics as a key indicator for employability will encourage the practice of putting employers' needs above knowledge creation and the development of academic disciplines, with the consequence that higher education will become increasingly vocation driven.