Advances in Consumer Research
Issue 4 : 1053-1060
Original Article
AI Leadership in Industry and Government: Innovations, Challenges, and Future Roadmaps
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1
Assistant professor, Faculty of Management, SRMIST Vadapalani, Chennai
2
Faculty of Management, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu Dt., Tamil Nadu -603203, India.
3
Business Administration, PERI College of Arts and Science, Chennai, Tamilnadu
4
Designation: Professor, Department: Management Studies, Institute: Vignan's Foundation for Science, Research and Technology, District: Guntur, City: Vadlamudi, State: Andhra Pradesh
5
Designation: Assistant Professor, Department: CLS, Institute: Gitarattan international business school, GGSIPU, District: Rohini, City: New Delhi, State: Delhi
6
Designation: Assistant Professor, Institution: Satyam Fashion Institute, Noida
Abstract

Artificial Intelligence (AI) can be used to revolutionize the decision-making process in the industry and government, but the leadership approach to its creation and usage is incomplete and unbalanced. The current paper examines the corporate AI leadership trends in both industries and highlights the variations in the strategic focus, ethical regulation, and organizational core capabilities. The current study synthesizes evidence on similarities and differences in policy and industry reports and academic literature published on the topic of psychology and health published in 2021-2024 applying a secondary qualitative research design and thematic analysis. Results indicate that industry is more concerned about innovation and market related efficiency whereas governments are concerned with regulation, popular confidence and social equity. The difficulty to close the gap between an ethical intent and action is seen in both industries, and the lack of talent, lack of oversight systems, and unexplained governance functions stand on the way. The article provides a summary of new forms of collaborative AI leadership and offers a road map toward combined, interdisciplinary and responsible leadership structure. The study will work in line with increasing the debate regarding responsible AI by providing practical implications that can be implemented by leaders struggling with the dynamics of Industry 5.0 and algorithmic decision-making.

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