Tag Archives: EthicalAI

19. The AI-Enabled Leadership Framework: Unifying Strategy, Ethics, and Human Judgment

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The following is the conceptualisation of the research-based series exploring AI’s impact on leadership.

If AI is a strategic imperative, can leaders afford to treat ethics and data fluency as mere compliance checklist items? The ultimate challenge of the AI era is synthesis: bringing together disparate technical, ethical, and human demands into a coherent strategic model.

Flow chart detailing The AI-Enabled Leadership Framework Model, structured across three phases: Foundation (Blue), Action (Purple), and Sustainability (Green). The model identifies 14 strategic steps, starting with a Red Target icon for the core Vision and including areas like Governance, Ethics, Upskilling, and Feedback.
The complete strategic framework illustrating 14 steps for guiding leadership development and decision-making in AI-transformed organizations.

The “AI-Enabled Leadership Framework Model” achieves this synthesis by structurally integrating the critical requirements identified across contemporary leadership research into three interdependent sections. First, it establishes the Foundation by mandating Executive Data and AI Fluency and Governance, Risk & Guardrails. This addresses the strategic necessity of understanding ML essentials and generative architectures, enabling leaders to ask sharper questions about systems and data. Second, the AI-Enabled Leadership in Action section addresses the core behavioral shift, requiring Adaptive Leadership Traits and Ethical and Inclusive Decision-Making. This is the most critical function: ensuring human judgment balances utilitarian AI output with necessary human values. Third, the Sustainability and Continuous Growth section manages the long-term journey through Transformational Capability and Feedback Loops. This aligns with the Dynamic Managerial Capabilities (DMC) view, ensuring the organization can actively Pilot → Refine → Scale → Iterate to maintain competitive advantage in volatile environments. The framework functions as an integrated blueprint, transforming theoretical mandates into a practical roadmap for leading hybrid human–AI organizations.

This structural approach directly addresses the primary research gap: the fragmentation of literature across technical, behavioral, and ethical domains. It elevates critical thinking from an abstract concept to a structured, repeatable process embodied in the Ethical and Inclusive Decision-Making phase (Goal 9). This critical function serves as the essential mediator, putting automated decisions into real-world context through human judgment. Furthermore, by emphasizing Trust, Transparency, and Human Oversight (Goal 10), the model compels leaders to address the risks of algorithmic bias and ethical missteps, ensuring that the powerful “double-edged sword” of AI is wielded responsibly.

I would like to suggest that this framework provides a strategic roadmap for organizations to navigate the transformative potential of AI. How does your organization currently measure and reward leaders who successfully balance AI-driven efficiency with ethical mediation and human oversight? Let’s share approaches.

2. AI-Powered Leadership: A Systematic Review

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Part 2 of 17 of a research-based series exploring AI’s impact on leadership This post summarises the article AI-powered leadership: a systematic literature review by Aziz et al. (2025).

When AI delivers a ‘data-driven’ decision, who is responsible for the social and ethical fallout if it goes wrong? The emergence of Artificial Intelligence (AI) has positioned itself as a critical factor in reshaping organisational dynamics, particularly in the realm of leadership. This systematic literature review investigated the evolving relationship between AI and leadership, focusing on definitions, prevalent themes, and challenges. The findings confirmed a complex range of key challenges in AI-powered leadership, including ethical dilemmas, difficulties in human-AI interactions, implementation hurdles, and long-term risks associated with deep AI integration. The study synthesises findings across diverse disciplines like management and ethics, aiming to advance the understanding of this complex relationship and facilitate scholarly investigations into the AI-powered leadership domain. Although AI offers tools to enhance efficiency and cognitive abilities, a clear, universally accepted definition of AI-powered leadership remains elusive.

The inherent fragmentation in defining AI leadership and the established link to ethical dilemmas underscore the absolute necessity of robust human critical thinking and moral judgment. The true value of critical thought here is its role as an essential safeguard against algorithmic overreach. Leaders must critically clarify how the benefits of AI are achieved while upholding ethical standards and human-centric values. This involves navigating the inherent risk that reliance on data-driven decision-making may fail to adequately factor in crucial ethical and social issues.

The authors suggest that clarifying the challenges presented by the integration of AI into leadership contexts empowers scholars and practitioners to understand the evolving AI landscape and its impact on effective leadership. What steps are organizations taking today to explicitly build human moral judgment into AI-powered decision architecture? Share your insights.

Reference: Aziz, M. F., Rajesh, J. I., Jahan, F., McMurrray, A., Ahmed, N., Narendran, R., & Harrison, C. (2025). AI-powered leadership: A systematic literature review. Journal of Managerial Psychology, 40(5), 604–630. https://doi.org/10.1108/JMP-05-2024-0389