Biography
Dr. Ramakrishnan Ramachandran is a researcher, educator, and former public-sector professional with a PhD in stakeholder management and corporate social responsibility. He worked for 22 years in the Government of India, including the Cabinet Secretariat and the Indian High Commission in Seychelles, before moving into manufacturing, information technology, and consulting. His academic writing addresses management, quality, ethics, environmental science, marketing, and mentoring. He has authored books and research papers and now undertakes corporate consultancy and professional development workshops for students and managers.
Conference contributions 2
AI LEADERSHIP AND THE FUTURE OF ACADEMIC INSTITUTIONS:
New competencies for academic leaders
Artificial intelligence is transforming higher education with is growing use in institutional structures, decision-making strategies, academic work, and leadership roles. As institutions negotiate hitherto unheard-of technical change, Academic leaders are challenged to balance between creativity, moral responsibility, organizational resiliency, and stakeholder expectations Though there is growing interest in artificial intelligence in education, little study on the leadership skills required to guide institutions through AI-driven transformation has been done. This conceptual article develops an AI Leadership Competency Framework for institutions of higher learning. To enable academic leaders to gain the core competencies required to operate AI-enabled businesses, the study combines strategic leadership theory with digital transformation literature, change management, and responsible AI governance. The proposed framework consists of five connected skills: Digital literacy, Adaptive change leadership, Human-centered stakeholder engagement, Strategic AI vision, and Ethical governance. Long-term corporate results as well as institutional preparation for artificial intelligence implementation depend on these skills. Apart from technological knowledge, the study shows artificial intelligence leadership as a complex ability comprising moral judgment, organizational learning, trust-building, and strategic foresight. Good artificial intelligence leadership also helps a company be more flexible, creative, accepting of its staff, and able to provide better education. It also lowers hazards linked with administrative mistakes, transparency problems, and algorithmic prejudice. By offering a comprehensive leadership framework for AI-enabled companies, this study supports scholarship in management and higher education. It provides helpful guidance for college leaders, legislators, and educational leaders working to create leadership capacity in reaction to fresh technological disruptions. The framework also lays the groundwork for later empirical studies on the connection between AI leadership skills and institutional transformation results in higher education.
RESPONSIBLE AI ADOPTION IN HIGHER EDUCATION:
A management framework for governance, trust, and organizational transformation
Through uses in instruction, learning, assessment, administration, and institutional decision-making, artificial intelligence (AI) is revolutionizing higher education. AI presents great possibilities for personalization, efficiency, and innovation. But its use also sparks issues about openness, trust, governance, academic integrity, accountability, and organizational readiness. Most research concentrates on technical execution or pedagogical ramifications; little focus is paid to the organizational and management aspects of responsible artificial intelligence acceptance. This article presents a conceptual management framework for ethical artificial intelligence use in colleges and universities. Drawing from theories of organizational transformation, technology acceptance points of view, institutional governance data, and ethical innovation concepts, the framework pinpoints the key organizational elements influencing effective artificial intelligence integration. More precisely, the study contends that AI governance frameworks, moral standards, leadership dedication, stakeholder involvement, and institutional AI knowledge taken together determine how much a company trusts AI systems. Institutional trust mediates the relationship between these organizational conditions and responsible AI adoption, which in turn contributes to organizational transformation. The recommended model views are responsible for artificial intelligence use as a strategic organizational competence rather than mostly a technical endeavor. It stresses how universities could balance responsibility with invention while still ensuring compliance with society's expectations and educational standards. The study supports management scholarships by using responsible innovation theory in the context of higher education and offering leaders a working governance framework for institutions. The framework could enable colleges, legislators, and educational administrators to develop sustainable AI adoption strategies that enhance organizational performance while maintaining ethical standards, stakeholder trust, and educational quality in the age of artificial intelligence.