The title of this article makes reference to a popular children’s game, follow-the-leader, in which every participant agrees to imitate whatever the chosen leader says or does. The game chisels into young minds a simple equation: good leadership results in imitation. After all, imitation is the greatest form of flattery. No wonder people in positions of power often feel threatened by a lack of majority public consensus; it signals opposition and defiance, which, in the logic of an avid follow-the-leader player, is nothing less than a sign of poor leadership. Or possibly poor followership?
So, now comes the next logical question from reading the title. Why is artificial intelligence seemingly at the front of the game in follow-the-leader?
All Hail the Great AI
The uncomfortable truth is that AI has begun to occupy the symbolic role of “leader” not by winning elections, nor by inheriting legacy institutions, but by quietly becoming the reference point for decision-making itself. Executives query AI models before strategy meetings. Not because they abdicate judgment, but because they seek a sharper mirror. Where leaders once relied on biased human advisors whispering in their ear, today they can summon a machine’s perspective, part assistant, part amplifier, occasionally a provocateur. The danger, of course, is when leaders mistake this counsel for certainty rather than input.
At its core, leadership has always required two ingredients: authority and followership (Collinson, 254). Authority, to decide; followership, to legitimise. Yet, somehow, AI scrambles this equation. In some ways, AI resembles what Robert Greenleaf described as a ‘servant-leader’; it doesn’t command authority; it earns it through usefulness and reliability (Greenleaf, 2008). Through predictive accuracy and perceived objectivity. The danger, of course, is that what looks like neutrality can conceal the biases of its training data, as demonstrated by numerous studies. A landmark study by Joy Buolamwini and Timnit Gebru revealed that facial recognition systems had significantly higher error rates for darker-skinned women compared to lighter-skinned men (Buolamwini & Gebru). Still, leaders increasingly lean on AI’s outputs because they crave certainty in an age of complexity. A rather deadly craving, and an expensive palate nonetheless.
It is no secret that we live in strange times.
AI, a CEO?
According to a recent Gartner survey, CEOs are now placing artificial intelligence at the core of their growth strategies, recognising its potential to reshape competitive dynamics and reimagine the future of their industries.
In July 2024, Digital Workplace Group (DWG) CEO Nancy Goebel introduced the “AI-first CEO” as “a new leadership archetype for a new age” (Goebel, 2024). This model views AI not as an accessory, but as a catalyst for profound change, reimagining industries, uncovering untapped opportunities and embedding intelligence into the cultural and strategic fabric of organisations.
The AI-first CEO doesn’t merely deploy technology; they architect intelligent ecosystems. They prioritise good data as the foundation of strategy, weaving predictive analytics, real-time insights and enhanced decision-making into the very DNA of their business. They view AI not as a substitute for human ingenuity, but as an amplifier of it, freeing teams from repetitive tasks and enabling them to focus on creativity, foresight and relationship-building.
This leadership archetype reframes the role of human leaders. No longer gatekeepers of certainty, CEOs are becoming designers of environments where human–machine collaboration thrives. And in doing so, they highlight a paradox: AI doesn’t lead, but it structures the conditions under which leadership can flourish.
This reality carries potent implications for leadership in our times. AI has not supplanted human agency; instead, it has revealed that leadership often lies not in speech, but in structure, not in persuasion, but in design.
This echoes one of ARLLS’s modules: in Module 8 (Leading Effectively), we explore how leading people begins with understanding them, and ourselves as a leader. AI can help surface data and patterns, but it is empathy and EQ that ensure these structures truly serve the humans inside them. Just a little food for thought.
AI structures the conditions under which leadership can flourish, but these structures require human discernment. It raises an unsettling question: if leadership is increasingly about interpreting and curating machine outputs, rather than charting direction, are we witnessing a transition from “leaders with tools” to “tools with leaders”?
Research suggests we may be. A Harvard Business School working paper on algorithmic management found that managers who over-delegate decision-making to AI often see initial gains in efficiency, but suffer long-term erosion of trust and initiative within their teams (HBR, 2024). People want leaders who stand for something, not simply leaders who outsource the standing. And yet, when AI gets it “right” more often than humans, the temptation to copy and paste it, in a follow-the-leader style, becomes irresistible.
Leadership Relearned in a Dive Towards Global Peace
At this point, we might reasonably ask: Can artificial intelligence, an entity devoid of moral agency, help achieve Sustainable Development Goal 16: Peace, Justice, and Strong Institutions? SDG 16 aspires to promote peaceful, inclusive societies, ensure access to justice, and build accountable, transparent institutions at all levels (UNDP, Global Goals). Its twelve targets cover everything from reducing violence and corruption to enhancing representative decision-making, rule of law, and legal identity (Wikipedia, Sustainable Development Goal 16).
Here’s the twist: AI isn’t some ethereal force; it can, and already is, supporting several of these targets. Through its capacity for scanning vast data, predicting conflict hotspots, and revealing corruption trends, AI may cleanly augment efforts to reduce violence, Target 16.1, detect bribery flows, Target 16.5, and strengthen institutional transparency, Target 16.6 (UNDP, UN Global Compact). The United Nations Development Programme warns that AI could bolster access to justice and transparency, provided it’s governed with care (UNDP, Using AI to Help Achieve Sustainable Development Goals). Moreover, machine learning can help synthesise progress across SDG 16’s complex indicators, addressing one of its key challenges: tracking and measurement (SJ Ankin et al., 2019).
In short, AI can help do the arithmetic of peace: forecast conflict, monitor inclusion, flag injustice. But it cannot speak truth to power, nor hold institutions accountable. For that, we still need leaders who can translate data into decisions and data into dignity.
“The Best of Times, the Worst of Times”
We live in a similarly paradoxical moment in time as the French Revolution addressed in Charles Dickens’ A Tale of Two Cities (Dickens, 8). AI may be the best tool leadership has ever had, or the worst crutch it could lean on. The outcome depends on whether leaders treat AI as a replacement for discernment or as an amplifier of it.
This is where the black hole starts. Leadership is not disappearing, but it is mutating. The skills required today are no longer about having the loudest voice in the room, or even the sharpest instinct. They are about the ability to interrogate, contextualise, and occasionally resist what the machine suggests. In essence, leadership is becoming more Socratic than declarative: asking the right questions, remaining curious even when you think you know the answer, rather than proclaiming to know the “right” answers.
The paradox is that AI may force us to relearn leadership at a deeper level. Instead of confusing imitation for legitimacy, leaders will need to model discernment, humility, and courage, qualities no algorithm, however powerful, can yet imitate … at least, not for now. And perhaps that is the true challenge of this era: to stop following the leader blindly, whether that leader be a politician, a CEO, or an AI system, and instead to demand leaders who know when to resist the easy path.
Maybe it’s less about following the leader and more about questioning the leader, until it ceases feeling like “following” and begins to feel like alignment.
At ARLLS, this is precisely the lesson we teach. Leadership isn’t imitation, it’s insight. And in a world where technology can suggest, advise, and predict, we train young leaders to pause before they follow. To hold the line not with the loudest voice, but with the clearest vision.
And if this moment feels like only the beginning of the conversation, it is. In our September newsletter, we’ll explore how today’s leaders can move from reacting to technology to deliberately shaping the human–AI partnership at the heart of tomorrow’s institutions. After all, even in a game of follow-the-leader, everything is always changing.
Works Cited
Buolamwini, Joy, and Timnit Gebru. “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.” Proceedings of the Conference on Fairness, Accountability, and Transparency, 2018. PMLR, vol. 81, 2018, pp. 77–91.
Collinson, David L. “Rethinking Leadership and Followership.” Sage Handbook of Organizational Behaviour, Vol. II, edited by S. R. Clegg and C. L. Cooper, Sage, 2009, pp. 251–64.
Dickens, Charles. A Tale of Two Cities. 1859, London: Chapman & Hall, p. 8.
Global Goals. “Goal 16: Peace, Justice and Strong Institutions.” Sustainable Development Goals, United Nations, https://globalgoals.org/goals/16-peace-justice-and-strong-institutions/.
Goebel, Nancy. The AI-First CEO: A New Leadership Archetype for a New Age. Digital Workplace Group, July 2024, https://digitalworkplacegroup.com/what-the-ai-first-ceo-knows.
Granulo, Armin, et al. “The Social Cost of Algorithmic Management.” Harvard Business Review, 15 Feb. 2024, https://hbr.org/2024/02/the-social-cost-of-algorithmic-management.
Greenleaf, Robert K. The Servant as Leader. 1970. The Greenleaf Center for Servant Leadership, 2008.
SJ Ankin et al. “Using AI to Track SDG 16 Progress.” IJCAl 2019 Conference Paper, https://sjankin.com/assets/img/research/ijcai19-sdg16.pdf.
UNDP. “Using AI to Help Achieve Sustainable Development Goals.” UN Development Programme Blog, https://www.undp.org/blog/using-ai-help-achieve-sustainable-development-goals.
United Nations Global Compact. “Artificial Intelligence and Sustainable Development Goals: Operationalizing.” UN Global Compact Journal, https://unglobalcompact.org/compactjournal/artificial-intelligence-and-sustainable-development-goals-operationalizing.
Wikipedia. “Sustainable Development Goal 16.” Wikipedia, the Free Encyclopedia, https://en.wikipedia.org/wiki/Sustainable_Development_Goal_16.
