Tag Archives: AIIntegration

12. Transformational Leadership, AI Competitiveness, and Project Performance

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Part 12 of 17 of a research-based series exploring AI’s impact on leadership This post summarises the article Transformational Leadership, AI Competitiveness, and Project Performance: A Moderation Analysis by Ofosu-Ampong and Adu-Ntim (2025)

Does implementing highly automated AI processes inevitably lead to a loss of human leadership effectiveness and organizational oversight? This study investigated how leadership styles interact with AI competitiveness in multinational organizations, finding that while transformational leadership positively enhances the benefits of AI integration (scope and frequency of use), excessive AI-enabled process automation shows a negative effect on project performance. This research challenges the conventional assumption that greater technology acceptance automatically equates to higher productivity, noting that AI satisfaction did not significantly influence project performance when leadership oversight is lost due to over-automation. This emphasizes the critical need for a precise balance between AI-enabled processes and crucial human elements.

The negative correlation between excessive automation and diminished performance establishes a clear role for critical boundary management. Leaders must use critical thought to precisely determine where substitution ends and human augmentation begins. The key critical function for transformational leaders is managing the human–AI interaction to prevent automation saturation from compromising essential human oversight and strategic flexibility. This demands continuous critical evaluation of the trade-off: specifically, analyzing the “mechanisms through which transformational leadership behaviors directly impact AI-related outcomes” to maximize system benefits while maintaining appropriate levels of process automation.

The authors, Kingsley Ofosu-Ampong and Julius Adu-Ntim, suggest that organizations must develop leadership approaches that effectively promote AI usage while maintaining appropriate levels of process automation to maximize AI system benefits. What metric should leaders use to determine if they have crossed the threshold into ‘excessive automation’ that risks diminishing their human leadership effectiveness? Share your view.

Reference: Ofosu-Ampong, K., & Adu-Ntim, J. (2025). Transformational Leadership, AI Competitiveness, and Project Performance: A Moderation Analysis. International Journal of Global Business and Competitiveness. https://doi.org/10.1007/s42943-025-00124-x

10. The Impact of AI on Evolving Leadership Theories

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Part 10 of 17 of a research-based series exploring AI’s impact on leadership This post summarises the article The Impact of AI on Evolving Leadership Theories and Practices by Frimpong (2025)

Can leadership remain fundamentally “human” when data-driven AI challenges the traditional reliance on intuition, experience, and emotional perception? This paper argues that the rise of AI compels leadership theories to evolve, necessitating the development of hybrid leadership models that fuse AI’s analytical strengths with indispensable human qualities like empathy and ethical judgment. The core finding highlights that AI enhances leadership effectiveness by automating routine tasks, optimizing workforce performance, and providing valuable data-driven insights. However, this shift introduces critical risks, including algorithmic bias, a lack of transparency, and the potential erosion of human-centric attributes like emotional intelligence.

The emergence of this hybrid model places critical thinking at the core of human responsibility, transforming it into a necessary ethical safeguard. Leaders must critically interpret AI’s analytical insights within complex organizational and ethical contexts. The crucial takeaway is the need for human leaders to scrutinize the algorithms themselves, ensuring they reflect ethical frameworks, are fair, and are accountable, actively preventing the perpetuation of biases embedded in training data. This critical oversight ensures that the efficiencies gained do not diminish the foundational human attributes of trust and compassion.

The author, Victor Frimpong, suggests that integrating AI into leadership must be conducted with caution and responsibility, safeguarding fundamental human attributes like ethical decision-making. How can we ensure that “hybrid leadership” means augmentation of human judgment, not merely automation of human ethical responsibility? Join the debate.

Reference: Frimpong, V. (2025). The Impact of AI on Evolving Leadership Theories and Practices. Journal of Management and Work, 2024(4), 400–417. https://doi.org/10.53935/jomw.v2024i4.1100