Part 9 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article Leadership training and development in the age of artificial intelligence by Sposato (2024)
In the fast-evolving AI landscape, is the biggest challenge redesigning business processes, or redesigning the leader? This article highlights the critical imperative for leaders to adapt and commit to continuous learning, emphasizing the necessity of updating leadership training in the AI era. The core finding suggests that as AI automates regulatory and transient data-driven tasks, the next generation of managers must shift their focus to higher-level liabilities. These include fostering innovative thinking, creative problem-solving, and concentrating on strategic employee development. This redirection requires directors and leaders to understand the technical roles of AI and intentionally fill the human gaps left by automation, transitioning effectively to a data-centric decision-making approach.
This evolution makes sustained critical thinking synonymous with future leadership viability, specifically demanding the cultivation of a culture of continuous learning. Leaders must use critical judgment to invest in technologies that genuinely streamline operations, freeing them up to focus on strategic planning and innovation, rather than simply replacing tasks. The “so what” for critical thinking is that it ensures leaders assume the role of guardians of powerful machines, continuously questioning and adapting their skill set, and resisting the urge to rely on AI without contextual validation.
The author, M. Sposato, implicitly suggests that whether leaders are born or made, structured development is needed to address the challenges of staff shortages and technological change. What elements of traditional leadership training must be unlearned immediately to cultivate the critical, adaptive mindset required by the AI era? Share your opinion.
Reference: Sposato, M. (2024). Leadership training and development in the age of artificial intelligence. Development and Learning in Organizations: An International Journal, 38(4), 4–7.
Part 8 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article The good shepherd: Linking artificial intelligence (AI)-driven servant leadership (SEL) and job demands-resources (JD-R) theory in tourism and hospitality by Han et al. (2026)
Can an AI ever truly be a “servant leader,” or is the concept limited to the human capacity for genuine empathy and community building? This research examines AI servant leadership in the hospitality and tourism sector, finding that AI’s cognitive dimensions—specifically conceptual skills and empowering—are significantly more effective for boosting employee job satisfaction by reducing job demands and clarifying role ambiguities. AI servant leaders excel at data analysis, task execution, and providing precise guidelines, mimicking human thinking using data analysis protocols. However, the AI leader demonstrates profound limitations in its capacity to convey authentic emotional responses and empathy, leading to a failure in crucial dimensions like “emotional healing” and “creating value for the community”.
The analytical strength but emotional weakness of AI leaders necessitates that human critical thinking focuses intensely on the socio-emotional and community gaps within the workforce. Critical thinking is required to determine the optimal boundary conditions for AI leaders and ensure that technology enhances, rather than diminishes, human connection and communal values. The “so what” is that human leaders must apply critical judgment to synthesize AI’s cognitive efficiency with the necessary emotional support and communal values, especially since AI leaders may not grasp the concept of shared values in a community.
The authors, H. Han, S. H. Kim, T. A. Hailu, A. Al-Ansi, S. M. R. Loureiro, and J. Kim, suggest that while AI’s cognitive functions are supported by their study, its emotional responses to employees are limited, reinforcing the need for human leaders. How must human leaders strategically apply their emotional intelligence to complement AI’s conceptual efficiency, especially in service-driven environments like hospitality?
Reference: Han, H., Kim, S. H., Hailu, T. A., Al-Ansi, A., Loureiro, S. M. R., & Kim, J. (2026). The good shepherd: Linking artificial intelligence (AI)-driven servant leadership (SEL) and job demands-resources (JD-R) theory in tourism and hospitality. International Journal of Hospitality Management, 133, 104470. https://doi.org/10.1016/j.ijhm.2026.104470
Part 7 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article Influence of Leadership on Human–Artificial Intelligence Collaboration by Zárate-Torres et al. (2025)
In the newly emerging hybrid workforce, what defines the essential boundary between the cold logic of an algorithm and indispensable human judgment? This research proposes a conceptual model where leadership acts as an ethical and strategic mediator in the Human Intelligence (HI)–Artificial Intelligence (AI) relationship, defining a crucial hybrid space of cooperation. The core finding establishes that while AI provides algorithmic efficiency based on data processing, HI remains necessary for interpretation, experience, and contextual judgment. Leadership modulates this relationship, shifting from mere supervision toward an essential role in co-creation. The model posits that effective leadership must integrate ethical governance mechanisms and establish a balancing mechanism to algorithmic efficiency through cognitive adaptability.
The introduction of this HI-AI hybrid space fundamentally reinforces and redefines human critical thinking as the ultimate strategic and ethical function. Critical thinking is embodied in the leader’s role of translating automated decisions into comprehensible language for teams, ensuring algorithmic transparency, and contextualizing decisions ethically. The essential need for human critical thought is derived from the fact that it is the only mechanism capable of putting automated decisions “in real context through human judgment and reasoning”, thereby guaranteeing organizational resilience beyond technical capability.
The authors, R. Zárate-Torres, C. F. Rey-Sarmiento, J. C. Acosta-Prado, N. A. Gómez-Cruz, D. Y. Rodríguez Castro, and J. Camargo, suggest that leadership acts as the axis that brings together human and technological systems, creating highly flexible, efficient, and ethically overseen interaction. As your organization integrates AI, how are you explicitly training leaders to be effective translators of algorithmic logic into human-centric direction? Share your strategies.
Reference: Zárate-Torres, R., Rey-Sarmiento, C. F., Acosta-Prado, J. C., Gómez-Cruz, N. A., Rodríguez Castro, D. Y., & Camargo, J. (2025). Influence of Leadership on Human–Artificial Intelligence Collaboration. Behavioral Sciences, 15(7), 873. https://doi.org/10.3390/bs15070873
Part 5 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article How Will Artificial Intelligence (AI) Evolve Organizational Leadership? Understanding the Perspectives of Technopreneurs by Zaidi (2025)
Will the next generation of leadership be defined by human intellect, or by the sophistication of the algorithms they manage? Expert interviews confirm that AI mandates fundamental, real-time shifts in leadership philosophies, transforming leaders into “tech-savvy leaders” committed to continuous learning. The primary finding is that AI enables the automation of routine tasks (like organizing and scheduling), allowing human leaders to pivot toward higher-level responsibilities, such as creative thinking, employee development, and bridging the human-technology gap. Crucially, the study reinforces the irreplaceable value of human judgment, noting that AI lacks intuition, a moral compass, and a ‘soul’, meaning it cannot settle complex business problems alone.
This transformation intensely reinforces the need for advanced human critical thinking in both decision-making and ethical oversight. Leaders must use critical thought to effectively become the guardians of powerful machines. This requires them to critically understand the truth of the algorithms they use, including their limitations and capabilities, especially within the company’s decision chain. The key critical function is determining “where people can be taken out of the loop, and where they can be involved,” ensuring automation doesn’t lead to an organizational philosophy that neglects human well-being.
The author, Syed Yasir Abbas Zaidi, suggests that AI coaching is further enhancing tomorrow’s AI congruent business leaders, fundamentally altering how leaders make decisions and transforming future team dynamics. How do we standardize the measure of a leader’s “tech savviness” to ensure they maintain critical, ethical oversight over the AI systems they deploy? Let’s discuss.
Reference: Zaidi, S. Y. A., Aslam, M. F., Mahmood, F., Ahmad, B., & Bint Raza, S. (2025). How will artificial intelligence (AI) evolve organizational leadership? Understanding the perspectives of technopreneurs. Global Business and Organizational Excellence, 44(1), 66–83. https://doi.org/10.1002/joe.22275
Part 3 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article Exploring the Impact of AI on Leadership Styles: A Comparative Study of Human-Driven vs. AI-Assisted Decision-Making in High-Stakes Environments by Hwang (2024)
When AI handles risk management in high-stakes sectors, does the human leader become obsolete, or is their role simply elevated? This research finds that AI integration in high-stakes environments (such as finance, healthcare, and aviation) fundamentally shifts leadership roles away from centralized control toward decentralization, with a crucial focus on interpretation, oversight, and ethical accountability. AI significantly augments decision-making accuracy and speed by analyzing vast datasets and offering predictive insights, which allows executives to concentrate more on organizational and strategic decisions. However, this augmented efficiency simultaneously introduces critical challenges regarding team trust in AI decisions and the complexities of ensuring algorithmic transparency and managing emotional/ethical nuances.
The profound shift toward decentralized decision-making clearly defines the indispensable requirement for human critical thinking: the leader must become the interpreter of algorithmic outcomes. This critical function bridges the gap between AI’s analytical strength and its inherent lack of contextual sensitivity required for real-world application. Without this interpretive layer, leaders risk losing the necessary ethical grounding, confirming that critical thinking is essential for maintaining human oversight in environments where mere technical accuracy might overlook broader social consequences.
The author, Jinyoung Hwang, suggests that organizational success requires adopting collaborative leadership approaches that blend AI capabilities with essential human judgment. If AI provides a highly optimized, data-driven recommendation, how do you critically ensure that the execution aligns perfectly with human values and existing team dynamics? Share your perspective.
Reference: Hwang, J. (2024). Exploring the Impact of AI on Leadership Styles: A Comparative Study of Human-Driven vs. AI-Assisted Decision-Making in High-Stakes Environments. International Journal of Science and Research Archive, 13(01), 3436–3446. https://doi.org/10.30574/ijsra.2024.13.1.2030
Part 4 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article Generative artificial intelligence use in the workplace: implications for management practice by Hernández-Tamurejo et al. (2025)
If trust is the strongest predictor of GenAI acceptance, what happens when managers blindly trust outputs generated from biased data? This mixed-method study finds that trust is the strongest predictor of intention to use Generative AI (GenAI). Crucially, this trust is conditioned primarily by the perception that organizational data management routines are reliable and objective. Interestingly, employee and manager perceptions of information transparency or privacy risk were found not to directly influence trust or usage intention. This raises significant risk, as users might blindly trust GenAI outcomes due to perceived efficiency benefits, leading to doubtful content usage in management decision-making and creating integrity issues in service delivery.
This reliance on perceived data integrity creates a paradox that demands rigorous human critical thinking focused on managing inputs and evaluating outputs. The research emphasizes that trustworthy data governance, not abstract explainability, is the foundation of sustainable GenAI adoption. Critical thinking must, therefore, be deployed to scrutinize both the data sources used by the AI and the factual accuracy of the outputs provided, rather than passively accepting results based on the promise of efficiency. This critical function serves as the essential check against the allure of speed, ensuring managers avoid the irresponsible use of GenAI content in high-stakes decisions.
The authors, Á. Hernández-Tamurejo, R. Bužinskienė, B. Barbosa, A. Miceikienė, and J. R. Saura, suggest that adopting monitoring, calibrated disclosure, and adaptive privacy protocols are concrete managerial levers to strengthen GenAI acceptance. In your experience, is the greatest challenge in AI adoption enforcing transparency, or instilling the critical capacity in staff to question seemingly objective algorithmic output? Share your thoughts.
Reference: Hernández-Tamurejo, Á., Bužinskienė, R., Barbosa, B., Miceikienė, A., & Saura, J. R. (2025). Generative artificial intelligence use in the workplace: implications for management practice. Review of Managerial Science. https://doi.org/10.1007/s11846-025-00949-z
Part 2 of 17 of a research-based series exploring AI’s impact on leadershipThis 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
Part 1 of 17 of a research-based series exploring AI’s impact on leadershipThis post summarises the article Enhancing top managers’ leadership with artificial intelligence insights from a systematic literature review by Bevilacqua et al. (2025)
In the AI era, are executive leaders truly adapting, or are they just layering technology over outdated strategic mindsets? Drawing on Upper Echelons Theory (UET), this systematic literature review confirms that AI radically restructures the managerial processes of organizations, making top managers’ leadership a determining factor in AI innovation effectiveness. The study identifies three key research clusters, with a core finding focused on the required AI-driven skills of top managers: data-driven decision-making, agility, and emotional and social intelligence. Successful integration requires leaders to cultivate environments that foster collaboration and knowledge sharing to maximize AI value. The integration necessitates a profound evolution of leadership dynamics, demanding leaders to balance technical capabilities with the ability to handle organizational and sociocultural factors.
The critical finding confirms that data provision alone is insufficient; sophisticated critical thinking is required to translate AI output into legitimate strategic action. The ability to analyze data critically and accurately and extract relevant insights remains crucial for top managers. This critical lens is essential not only for internal process efficiency but, more importantly, for navigating external pressures; top managers must use critical thought to align AI adoption with sociocultural context, ensuring regulatory compliance and ethical use. The critical layer ensures technology adoption, which is influenced by factors like social perceptions and regulations, contributes responsibly to competitiveness.
The authors, S. Bevilacqua, J. Masárová, F. A. Perotti, and A. Ferraris, suggest that the study contributes to UET by integrating AI as a crucial variable that radically transforms leadership and decision-making at the executive level. As AI tools multiply, how can we measure and accelerate the critical skill of translating algorithmic insights into human-centric strategic results? Let’s discuss.
Reference: Bevilacqua, S., Masárová, J., Perotti, F. A., & Ferraris, A. (2025). Enhancing top managers’ leadership with artificial intelligence insights from a systematic literature review. Review of Managerial Science, 19, 2899–2935. https://doi.org/10.1007/s11846-025-00836-7
Artificial Intelligence AI Photo by Alex Knight on Pexels.com
It’s no secret that Artificial Intelligence (AI) technologies are becoming increasingly popular and powerful tools to help people with a variety of tasks. But when it comes to writing a speech, using AI may not be as straightforward as it seems. While AI can provide assistance in terms of researching and organizing content, it still requires a significant amount of work and effort to craft a speech that stands out. In this blog, we’ll explore how I used AI technologies to attempt to write a persuasive, engaging speech.
I started by asking my AI app “How do you use AI to write a public speaking script?”
This was the response.
When it comes to public speaking, crafting the perfect script can be a daunting task. From finding the right words to memorizing your lines, it can be difficult to stay organized and present yourself in the best light. Fortunately, artificial intelligence (AI) can help you create an impactful public speaking script with ease.
AI-powered tools can help you craft a speech that resonates with your audience. By understanding your audience’s interests and passions, AI-powered tools can suggest topic ideas and provide you with hints and tips on how to improve your presentation. Additionally, AI can analyze your writing to identify any areas that need improvement, such as structure, grammar, and flow.
When it comes to writing your script, AI can help you edit your work quickly and efficiently. By utilizing natural language processing (NLP) algorithms, AI can detect and correct any spelling and grammar mistakes, as well as suggest better word choices. AI can also help you create a more engaging script by providing you with suggestions on how to capture your audience’s attention with storytelling elements and emotion.
To make sure your script is error-free and professional, AI can also help you with the proofreading process. By using machine learning algorithms, AI can scan your script for any typos, grammar errors, and inconsistencies. Additionally, AI can provide you with real-time feedback on how to improve your script and make it more impactful.
Finally, AI can also help you rehearse your presentation. By using text-to-speech (TTS) technology, AI can read your script out loud, so you can get a better understanding of how your words flow and sound. Additionally, you can use AI-powered virtual reality (VR) systems to practice your public speaking in a simulated environment, so you can get a better feel for the performance and craft a more engaging presentation.
That’s not too bad! It’s a bit repetitive in places, but it’s easy to understand. So, the next thing was to ask the app to “write a speech on the benefits of having an executive coach.” This was the response:
Good morning everyone, Today, I’m here to talk to you about the pros and cons of executive coaching.
Let me begin by telling you a story. A few years ago, I was a young executive working in a large corporate environment. I had a lot of responsibility, but I was feeling overwhelmed and uncertain of my capabilities. I was struggling to stay on top of my tasks, and I was feeling like a failure. That’s when I decided to try executive coaching. I had heard that it could help executives become more successful, so I decided to give it a try.
At first, I was hesitant. I wasn’t sure if I was ready for the commitment and I didn’t know what kind of guidance I could expect.
But I was determined to make a change, so I decided to go ahead with it. The results were amazing.
With the help of my executive coach, I was able to develop a strategy to better manage my workload, delegate tasks and stay on top of my responsibilities.
I was also provided with tools to help me stay focused and motivated. The experience changed my life. I felt more organized and confident in my abilities, and I was able to make a successful transition into leadership roles.
But executive coaching isn’t always the right choice for everyone. There are a few potential drawbacks that you should be aware of before making the decision to take part in executive coaching.
The first is the cost. Executive coaching can be expensive, so you should make sure you’re willing to invest the money and have enough resources to get the most out of the experience.
Another potential downside is the time commitment. Executive coaching requires a significant time commitment from both the coach and the executive, so make sure you’re willing to dedicate the necessary time and energy to get the most out of the experience.
Finally, you should be aware that executive coaching isn’t a one-size-fits-all solution. Every executive has unique needs, so you’ll need to find a coach that’s the right fit for you and has the experience to help you reach your goals.
To sum it up, executive coaching can be a great way to help executives become more successful, but there are some potential drawbacks that you should consider before making the decision to take part in executive coaching. Thank you for your time and attention.
Ok, so a bit vanilla and could do with some more emotive language. But there is a good foundation and concepts that can be used to construct a more captivating narrative.
Next I used the AI to generate a more interesting story. I prompted the app with ” my executive coach helped me deal with a debilitating condition I had kept secret. include a detailed example.” This is the result:
I had kept a debilitating condition a secret from everyone—including my family, friends and colleagues—for a long time. I suffered from crippling anxiety and panic attacks, which made it difficult for me to engage in social situations and everyday activities. I felt ashamed and embarrassed, so I kept my condition hidden from the world. Then, I decided to work with an executive coach. At first, I was hesitant to open up about my condition, but eventually, I mustered the courage to reveal my struggles. My coach was incredibly understanding and compassionate. She provided me with support, guidance, and strategies to help me manage my anxiety. For example, my coach taught me techniques to help reduce my anxiety in the moment. She encouraged me to practice deep breathing and mindfulness, which helped me to stay grounded during stressful situations. Additionally, my coach provided me with long-term strategies to help me build my resilience. She taught me how to identify my triggers and develop effective coping mechanisms. My coach also helped me to create a plan to disclose my condition to my family, friends, and colleagues. She provided me with resources to educate myself and my loved ones about anxiety and panic attacks. She also helped me to craft a script so that I could explain my condition in a way that felt comfortable to me. Thanks to the support and guidance of my executive coach, I was able to take steps to address and manage my condition. I felt empowered to take control of my mental health and take ownership of my condition. I was finally able to be honest with the people around me and accept the help and support they offered.
This story is a bit more interesting but still lacks personality.
My key takeaways from this activity:
If you put in garbage, you’ll get garbage out. If you’re not precise with your commands for the AI, the result will be uninspiring. Give thought to what you exactly want.
Verify each line of the output. The content can be incorrect, redundant, or dull.
AI is a huge timesaver. It can be used to generate ideas, outlines and content and break through writer’s block.
AI can offer valuable prompts on topics you may have not considered.
Overall, Artificial Intelligence is an indispensable tool in any toolbox.
Justin O'Brien 