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The purpose of this paper is to synthesize the diverse literature on board demographic diversity and to provide avenues for future research.

The study provides a comprehensive literature review of theoretical and empirical studies published in leading management journals from 1989 to 2015.

The literature review revealed several aspects that are related to board demographic diversity. These aspects have been classified into: definitions and types of board diversity, dimensions of board demographic diversity, measurement and outcomes of board diversity, reasons for existing conflicting empirical findings about the relationship between board diversity and firm dynamics, and research on mediators and moderators.

Issues pertaining to board demographic diversity identified in this paper have theoretical and practical implications, and include avenues for future research.

Artificial intelligence (AI) applications’ usage in Chief Officers’ (CXOs’) decision-making is a topic of current research interest. A fundamental dilemma is carefully planning an effective combination of a CXO’s professional experiences and AI applications’ decision-making responsibility. However, the existing literature fails to specify the value of co-creation of AI applications and the human experience in managerial decision-making. To address this gap in the literature, the authors’ examine how an ideal cognitive-technology fit can be created between human experiences and AI-based solutions at CXO-level decision-making using the theoretical lens of the Service-Dominant Logic.

The authors’ employed a grounded theory approach and conducted a focus group discussion with seven participants to shed light on the factors that may balance AI applications’ usage and CXOs’ experience in making business decisions. This was followed by 21 in-depth interviews with employees from knowledge-intensive professional service firms to validate the findings further of a new phenomenon. Further, given the newness of the phenomenon, this approach allowed researchers a retrospective and real-time understanding of interviewees’ experiences of the phenomenon under consideration.

The advantages and constraints of both CXOs’ experiences and AI applications deserve due consideration for successfully implementing technology in knowledge-intensive professional service organizations.

This study may appeal to researchers and practitioners interested in the future of decision-making, as the authors’ study findings advocate for balancing CXO’s expertise and the use of AI in decision-making.

Based on the preliminary findings, the authors developed a theoretical framework to understand the factors that govern AI implementation in an organization and how a competitive strategy may emerge from value co-created by AI applications and CXOs’ experience, particularly in knowledge-intensive professional service firms.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

In the wake of inconsistent findings between board diversity and firm performance, the purpose of this paper is to advance the research by examining the linear and non-linear nature of the relationship between board demographic diversity (gender, age, tenure, and education) and firm performance in Indian knowledge-intensive firms (KIFs).

This study uses a panel data set of top KIFs in India that is listed in National Stock Exchange’s Top-200 list for the period 2010-2014.

Results indicate that there exists a positive linear relationship between the overall board demographic diversity index (board gender, age, tenure, and education) and firm performance. Among the effects of individual board diversity variables, the authors have found that board age diversity positively whereas education diversity negatively influences firm performance. Furthermore, gender diversity and tenure diversity do not significantly influence the firm performance.

This study is based on the following demographic factors: gender, age, tenure, and level of education. The authors did not include other demographic variables such as nationality and language.

This research would help knowledge-intensive companies in designing their corporate boards. The results indicate that companies should have more diverse boards to enhance firm performance.

To the best of the authors’ knowledge, this is the first research to examine the effect of the overall board diversity index and individual board demographic diversity indices (gender, age, education, and tenure) on firm performance in the context of KIFs in India.