Businessman on a ladder reaching the star above cloud.Business concept.
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Although nobody has data on the future (including, by the way, self-proclaimed futurists and the growing number of apparent experts who deliver a never ending flurry of granular stats and facts on what will happen to jobs, skills, careers, and humanity as a whole), there are obvious reasons to be concerned by it.
First, judging by the amount of change we have experienced in the past five years alone (no prizes for guessing what the source of this change is), organizations and leaders are still struggling to adapt or adjust to the present. And, while obsessing over the future is often a good strategy for not dealing with the present, it is safe to assume that even more change is in the air, whether incremental or exponential, so it would be reckless to dismiss this and perhaps mad to adopt a business as usual strategy. We can think of organizations and leaders as ships in the middle of a storm, contemplating an even darker horizon and knowing that there’s still a long way to go. Or if you prefer railroads: the light at the end of the tunnel may be a train coming their way.
Second, when uncertainty is perhaps the only certainty (though, to be honest, I am not even certain of this!), human skills like creativity, curiosity, adaptability and ingenuity are at their best, emerging as a competitive advantage or differentiators. Every organization and leader has access to the same information and AI has democratized (and to a large extent commoditized) the ability to convert that information into insights. Yet, there is still the stuff AI cannot answer, which includes how AI will unfold and how best to prepare for it, as well as any broader or deeper insights about the future. Likewise, there is a great deal of room for variability when it comes to making bets about the future and especially act on our specific assumptions to enact the behaviors that bring those bets to live and may equate to pursuing your own pathway for sailing in the storm or finding the way to the top (or at least out of the tunnel). Strategy, innovation, transformation, and any big business imperative only make sense when you don’t know the result and would not exist or have any meaning if the cause-and-effect link between current actions and future outcomes was known.
Third, even if the future is uncertain, the tacit assumptions we make about the future (e.g., more change, more complexity, different from the past, more volatile, less stable, etc.) are sufficient to allocate resources in a strategic rather than arbitrary fashion, not least because our models of the future are always based on the past, and things that may superficially look “unprecedented” can often be explained by past experiences, occurrences, and data points. Needless to say, there’s no other way to strategize or prepare for anything, since the assumption that the future is comprised of unknown unknowns or is categorically distinct from anything that happened in the past and therefore not captured by any past or present models could only lead to inaction or random actions. Incidentally, the same goes for hyperbolically utopian (exuberant prosperity for all) or dystopian (humanoid robots in charge) visions of the future, which make any form of planning pointless.
Among the most widely shared tacit (and at times explicit) assumptions that can be made about the future is the notion that leadership talent, the ability to coordinate collective human activity, from small teams to large organizations and societies, will become more rather than less important in the future. Why is this assumption so apparently obvious? Because when the stakes are high, challenges grow in complexity, and collective adaptability is hard to master, the need for sophisticated and skilled orchestration, direction, and mobilization increases. This calls for proficient levels of leadership talent and, above all, potential. If talent is the ability to deliver extraordinary levels of performance, potential is the probability to develop higher levels of talent in the future. We can observe and quantify talent by examining a person’s past and present performance, but potential is a bet we make on a person’s likelihood to display new forms of talent in the future.
When the world is simple and performance is easy to master, leadership is rather less relevant, which means that even people with subadequate or rudimentary leadership skills may deliver acceptable results, and that their teams and organizations may perform well relatively independently of the leader’s actions. However, when the world is complex and performance becomes hard to master, leadership becomes the indispensable source of team effectiveness and variability between teams’ performance is not just larger, but also strongly dependent on the leader’s talents. Furthermore, when the world keeps changing and the nature of our challenges keeps growing and evolving (meaning, your ability to solve today’s problems may be unrelated to your ability to solve tomorrow’s problems) the crucial challenge is to evolve leadership itself, or bet on individuals who have the potential to develop and evolve in line with the challenges they face.
A leadership model for the human-AI age
Russell Reynolds AI Leadership model
If we treat AI, not as a tool or related set of tools, but rather as the defining leadership challenge of our times, and the likely challenge humanity will need to master in the next few years or decades (whether this means dealing with disruptions, productivity gains, unfulfilled promises, re-organization to achieve value realization, strategic business advantage or differentiation, and perhaps even economic bubbles), one thing is sure: as in any previous chapter of our human evolution, the ability to organize collective human activity, which today also includes being able to coordinate the human-AI interface or how humans can be augmented by AI, will require competent leadership. That is to say, groups, teams, organizations and nations that are better led can be expected to outperform those that are poorly led, and given the size of the challenge (both in terms of risks and opportunities), having the right leaders and being able to future-proof them should be seen as a strategic priority for organizations and nations.
As the chart above illustrates, when it comes to leadership, AI does not change everything but it still does impact some of the critical features that will likely make leaders effective in the future and help their teams navigate the human-AI age. First, for many decades – in what is largely known as the human capital age – leadership selection and development have largely focused on hard skills, expertise, or intellectual capital (what you know, often signalled via formal credentials and expertise). However, those aspects of leadership talent have been severely disrupted by AI, which has already won the IQ battle against humans. Indeed, even rudimentary direct-to-consumer LLMs and gen AI platforms know much more about most things than most if not all humans know, changing the very meaning of expertise: from knowing the answers to questions, to asking the right questions, and knowing enough to vet or edit the answers provided by AI, which includes the ability to ignore the irrelevant and to use AI better than a novice would.
Relatedly, for decades organizations assumed that the best predictor of future leadership performance was past performance. So, if you want a safe pair of hands or someone who will deliver results in the future, look for track record, experience, and assume there is no better recipe for the future than to copy-paste from the past. But, the less the future resembles the past, the more irrelevant past performance is as future indicator of performance. AI has already impacted most jobs and roles, to the point that even when we are still in the same functional or formal role as before, how we actually add value in that role has change dramatically, because we outsource some tasks to AI, AI agents, and automation technologies, in order to free up time and skills for higher-value human activities. While we don’t know how fast and far and in what direction AI will continue to unfold and develop, it is logical to assume that the distance with the past will continue to increase, so hiring leaders for what they have done will be less useful than hiring them for what they could do; and what they will need to do is probably going to look less and less similar to what they have done in the past.
Transformational leadership, once regarded as a niche or specialized sub-type of leadership (evocative of the unconventional misfits hired to drive change and infect the organization with the innovation virus, or similar clichés), now becomes a foundational leadership capability. Nobody should be seen as a leader unless they have some transformational foundations in their DNA or are at least capable of developing a transformational mindset, since driving or leading change is now the fundamental task of leaders. Likewise, transformational leadership is no longer a specific role or formal title, but rather a central leadership activity for anybody responsible for a team, business, or unit.
Importantly, while we may not be able to predict either the future or the hard skills leaders will need to develop in the future, it is safe to assume that leadership potential, defined as the ability to develop the leadership skills and talents needed to be effective in the future, will mostly center around the competencies or qualities AI is unlikely to replace or automate, which are the very qualities followers will need most from their leaders, not least because they won’t be able to source them from AI or outsource them to it. As the above chart shows, these comprise EQ or the range if interpersonal and intrapersonal skills that enable leaders to connect with others on a human and humane level (something AI can fake well but not really replace); curiosity and judgment, which includes the intellectual humility to understand and care about what you don’t know, and the openness to learn and experiment in an age in which cognitive surrender and intellectual laziness are the unwanted symptoms of our obsession with productivity and efficiency (a euphemism for laziness); vision, because when nothing is clear and everything seems uncertain, humans remain meaning-craving machines and will look at leders as sources of meaning to mitigate their anxieties and insecurities; resilience, since the ride is likely to be bumpy and setbacks are nearly guaranteed, so the ability to bounce back stronger and be antifragile will likely be a pivotal survival skill for leaders and their teams; coachability, because leaders who think they are a finished product are probably finished; and agility and range, which include the ability to span between opposite extremes and manage the fundamental paradoxes underpinning all critical leadership challenges, not to mention resolving or navigating one’s own paradoxical leadership challenges.
The astute reader may have noticed that these soft skills, while presented as central to future leadership, as not exactly new. Indeed, even before AI went mainstream with the recent breakthroughs of LLMs and genAI platforms, there has been a salient trend whereby the growing importance of soft skills co-existed with the rapid devaluation of hard skills, with leadership potential being more about the foundational attributes that enable leadership to evolve and adapt to new challenges and become smarter or at least more adaptable over time, much like AI does.
The apparent paradox is that the more advanced our technologies become, the more valuable our oldest human capabilities seem to become. There is nothing particularly futuristic about curiosity, judgment, resilience, or the ability to inspire others. Aristotle would have recognized them. So would Confucius. AI has not suddenly made these qualities important. Rather, it has exposed how much we had been underestimating them while overvaluing knowledge, credentials, and experience as proxies for future performance. In many respects, the AI revolution is forcing us to rediscover what leadership was always supposed to be: not demonstrating that you have the answers, but creating the conditions in which people can collectively discover better ones.
There is a broader lesson here. Every technological revolution eventually changes what it means to be exceptional. Once machines outperform humans at a particular activity, excellence simply migrates elsewhere. We stopped admiring people for their ability to multiply large numbers in their heads when calculators arrived. We no longer judge photographers by their ability to develop film in a darkroom. Likewise, the widespread availability of AI means that expertise itself becomes less scarce than the judgment required to deploy it wisely. The frontier of human advantage has always moved, and there is little reason to believe this time will be different.
Perhaps, then, the future of leadership is less about preparing people for a world dominated by artificial intelligence than about ensuring they do not become artificially intelligent themselves: endlessly optimizing, predicting, calculating, and producing, while gradually surrendering the curiosity, imagination, and moral judgment that made those optimizations worth pursuing in the first place. Technology has always rewarded those who learned to master it without becoming like it. There is little reason to think AI will prove the exception. In the end, the defining question for leaders will not be whether they can keep pace with increasingly intelligent machines, but whether they can continue cultivating the distinctly human qualities that machines, however capable they become, still struggle to explain, let alone inspire.