The nature of leadership is being redefined in the age of AI. As artificial intelligence becomes embedded across organizational functions — from decision-making and resource allocation to customer interaction and strategic forecasting — leaders are not being rendered obsolete by AI; rather, they are required to assume new, indispensable roles that shape how AI is integrated into the fabric of organizational life.
Moore than ever before, we see an urgent demand for agile leadership — the ability to navigate rapid change with intelligence, integrity and foresight. In my book, Nimble: Make Yourself and Your Company Resilient in the Age of Constant Change, I have argued that we need to understand agility as being nuanced by context. The result is a framework of five agilities. Analytical agility refers to the capacity to interpret data critically and make informed decisions under uncertainty. Operational agility involves adapting structures and processes to respond efficiently to dynamic conditions. Innovative agility is the ability to imagine new possibilities and reframe challenges creatively. Communicative agility reflects the skill to engage stakeholders with clarity and empathy, and exert influence across diverse contexts. And at the center lies visionary agility — the capacity to hold a long-term, values-driven orientation even as conditions shift rapidly. While AI can augment analytical and operational capacities, the remaining domains — especially visionary agility — demand human discernment, moral judgment and leadership foresight.
In the AI-driven world, visionary agility enables leaders to interpret new information meaningfully, challenge what must be challenged, and steward resources and technologies in alignment with broader human purposes. These three functions — interpreter, challenger and steward — are the critical roles of agile leadership in an AI-driven world.
Interpreters: Translating AI output into strategic intent
AI systems are capable of extraordinary computational feats: analyzing vast datasets, identifying subtle correlations and generating predictive outputs. Yet, they lack the capacity for intentionality. AI does not understand culture, vision or long-term strategic goals. That work remains the responsibility of human leaders.
Consider Stitch Fix, the online personal styling platform that uses machine learning to generate clothing recommendations for customers. Despite its technological sophistication, the company places human stylists between the algorithm and the client. These stylists act as interpreters — contextualizing algorithmic suggestions through the lens of customer feedback, lifestyle and tone. This interpretive layer preserves the brand’s core promise: personalized human service.
Such decisions are not incidental. They demonstrate the leader’s role in ensuring that AI — no matter how advanced — serves organizational intent and human meaning. Visionary agility begins with the interpretive act of linking outputs to values.
Challengers: Interrogating the machine
Interpretation must be complemented by the willingness to challenge AI recommendations, particularly when they raise ethical, cultural or societal concerns. Visionary leadership requires more than passive acceptance of technical outputs — it demands critical engagement and the courage to push back.
A notable example comes from Salesforce, which paused the deployment of predictive policing and facial recognition technologies as early as 2019. While technically feasible and potentially profitable, these applications of AI raised significant ethical red flags. Salesforce executives, including CEO Marc Benioff, chose to decline business opportunities where the technology might exacerbate racial profiling or violate civil liberties.
This was not simply a branding exercise. It reflected a leadership stance that challenged the idea that technical capacity alone justifies implementation. By setting internal guardrails and refusing to engage in ethically compromised deployments, Salesforce exemplified how visionary agility empowers leaders to override algorithmic logic in favor of societal responsibility.
Stewards: Governing for the long term
Beyond interpretation and challenge lies the responsibility of stewardship — the deliberate governance of AI systems in alignment with human values, transparency and accountability.
An instructive example comes from Mozilla, the nonprofit behind the Firefox browser and a long-standing advocate for ethical technology. Mozilla has embedded AI ethics into both its development practices and public engagement. Its Mozilla Foundation funds external audits of AI systems and supports the development of transparency tools for algorithmic accountability.
Rather than using AI solely for product optimization, Mozilla has positioned itself as a custodian of the public interest in technology, helping to set industry norms around fairness, explainability and user rights. Its leadership reflects a commitment to proactive governance — anticipating how AI may affect not just individual users but democratic systems and societal cohesion.
This model of stewardship is central to visionary agility: the ability to act with long-term foresight and ethical grounding, ensuring that innovation unfolds in service of humanity rather than at its expense.
Leadership beyond the algorithm
AI will continue to automate, accelerate and optimize. But it cannot ask whether an action is just, whether a strategy is humane or whether a solution aligns with an organization’s purpose. These remain the responsibilities of human leaders.
Agile leadership — rooted in the five interdependent agilities — ensures that we do not merely use AI effectively but lead with it wisely. Within this framework, visionary agility becomes the fulcrum: it is the domain where leaders act as interpreters of insight, challengers of misalignment, and stewards of meaning.
AI may know what is probable. But leadership must always know and do what is right.