Artificial intelligence (AI) affects all aspects of a business, significantly contributing to problem-solving and introducing new operational processes within companies. Interest in AI is growing due to its capacities regarding the efficiency of operations, reduced working time, and quality improvements. However, to ensure proper development, businesses should also address the ethical effects generated by AI technologies. This research aims to identify AI’s ethical impact and associated challenges in the business consulting industry and the consultants’ perspective on AI’s future implementation in their specific sector. The methodology is based on the design of a structural equation modelling using data collected through a survey addressed to business consultants. The results highlight that ethical concerns are positively correlated with the identified harmful consequences of AI, such as high implementation costs, the possibility that this technology will lead to job losses, or a lack of human interaction and creativity. The consultants’ perspective on the future aspects of AI’s use in business consulting is negatively impacted by the following ethical outcomes: discrimination, invasions of privacy, denial of individual autonomy, unjustifiable results, and disintegration of social connection.

Purpose: Technological innovation has the potential to consolidate and create more conscious investment strategies, opening new avenues for both local and foreign investors. Despite many efforts within firms towards business process efficiency, research on comprehensive strategies embedding digital tools is still in the early stages. This study examines how environment-friendly and sustainable investors across the European Union (EU) can leverage technology and digital innovation to enhance sustainable business processes and financial performance. Design/methodology/approach: The methodology is based on robust regression and dynamic GMM models, cluster analysis using the Ward method and network analysis through Gaussian graphical models. The data are extracted from the European Innovation Scoreboard and cover 27 EU countries from 2016 to 2023. Findings: The empirical findings provide a viable path for investors to actively plan a strategic layout to improve the adaptation of technological innovation and achieve a broader perspective of sustainable business practices, with positive spillovers on financial performance and environmental sustainability. Practical implications: Lessons are learnt from the multiple and diverse connections between the analysed dimensions. Firms and policymakers should embed levers in their strategies/policies that enhance the use of information technology and stimulate competitiveness in science, with a keen focus on human resources. Originality/value: The study stands out through the advanced modelling techniques applied to offer detailed insights into the relationship between technological innovation, sustainable firm investments and performance for specific groups of innovators in the EU.

Drawing on diffusion of innovation theory, this cross-national study examines the association between cultural dimensions and artificial intelligence (AI) capability on a 78-country sample. This cross-country, worldwide approach enables a more comprehensive understanding of differences in cross-national AI capability, providing cultural explanations for a new perspective on the diffusion of novel technologies. Our main findings reveal that individualism demonstrates the most stable positive association across model specifications. Uncertainty avoidance and motivation towards achievement and success are significant in the baseline SEM, but the results become sensitive after adding country-level control variables. Long-term orientation is significant in some OLS models but not in the baseline SEM. Power distance and indulgence are not supported in the baseline SEM. Results suggest that cultural values should be considered alongside economic, infrastructural, and regional conditions when analyzing cross-national differences in AI capability. Our findings provide a contextual perspective for policymakers and managers that are developing strategies for achieving competitive advantage. Considering the turbulence of the business and social environments, we argue that cultural adaptive capabilities are essential for global competitiveness.