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The primary aim of this study is to investigate the integration of generative artificial intelligence, specifically ChatGPT, into workplace L&D practices, exploring the associated advantages and challenges such integration from an organizational change perspective.

This study uses a qualitative approach, conducting semi-structured interviews with twelve learning and development (L&D) experts.

This study indicates that ChatGPT can positively impact L&D by streamlining processes and potentially enhancing employee performance, engagement and satisfaction. However, to mitigate employee resistance, organizations must clearly communicate the necessity and rationale behind the change, involve employees in the implementation process and address trust issues. Key challenges such as overreliance on ChatGPT, AI skill shortages and technology issues like privacy breaches and misinformation must be managed through strong governance frameworks, including policies, guidelines and regular audits.

The study’s scope is confined to semi-structured interviews with L&D experts, potentially limiting its generalizability. Further research could explore the long-term effects and broader implications of ChatGPT integration in different organizational contexts.

By framing GenAI integration within the context of organizational change, this study offers insights into managing the transition effectively by providing guidance for managers on effectively integrating ChatGPT into L&D practices, emphasizing the importance of mitigating potential negative consequences while maximizing benefits.

Integrating ChatGPT into organizational L&D has the potential to reshape how employees acquire new skills and knowledge, potentially influencing organizational culture and dynamics. However, careful consideration is required to ensure that the integration process aligns with ethical and social norms, minimizing adverse impacts.

This research contributes foundational insights into the integration of ChatGPT in corporate L&D by researching and understanding the opinions of corporate professionals. It serves as a starting point for organizations to identify challenges in adopting GenAI.

This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system.

This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer.

The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria.

This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

In the dynamic landscape of industrial enterprises, the integration of advanced technologies has emerged as a crucial factor in enhancing both operational efficiency and sustainability. This paper explores the impact of artificial intelligence (AI), the Internet of Things (IoT), and blockchain technology on accounting sustainability performance. AI's data processing and predictive capabilities, IoT's real-time monitoring, and blockchain's transparency and security are examined for their roles in transforming traditional accounting practices. The discussion highlights how these technologies collectively improve the acceluracy, efficiency, and reliability of financial and sustainability reporting, driving a culture of transparency and continuous improvement. By aligning financial objectives with sustainable practices, industrial enterprises can achieve long-term stability and contribute to global sustainability efforts. This study underscores the importance of technological adoption in navigating the complexities of modern industrial operations and achieving a balance between financial success and sustainable stewardship.

This study examines the impact of female directors on cash holdings in Egyptian listed firms, particularly in light of Decree 123/2019, which mandates female board representation. This study aims to determine if female directors mitigate agency conflicts related to cash holdings and how these dynamics shift post-quota implementation.

Using a panel fixed-effects model, the research analyzes 1,563 firm-year observations from 223 non-financial Egyptian firms listed on the EGX between 2014 and 2022. The robustness of the findings is tested through additional analyses using alternative proxies for cash holdings, different sample periods and a two-stage least squares approach to address endogeneity concerns.

This study finds a significant negative association between female directors and cash holdings, suggesting that female board members may promote more conservative cash management practices. However, this relationship weakens post-quota implementation, becoming statistically insignificant. This implies that while quotas increase female representation, they do not necessarily enhance corporate governance effectiveness regarding cash management. The pre-quota positive link between female directors and excess cash holdings also becomes insignificant post-quota.

The study focuses on female directors’ impact on cash holdings, excluding potential effects on other board subcommittees or functions. It does not capture long-term benefits of increased female representation, which may emerge as the pool of qualified female directors grows. Future research should explore broader implications of gender diversity guidelines and other diversity dimensions across various corporate governance aspects and institutional contexts.

This research provides empirical evidence from an emerging market context on the understudied impact of gender diversity on cash holdings. It critically evaluates the unintended consequences of mandatory gender quotas, highlighting the complexity of regulatory interventions in corporate governance. The study stresses the need for policymakers to address factors limiting the effectiveness of such quotas and to consider potential suboptimal outcomes when increasing female board representation without a corresponding increase in the supply of qualified female directors.