When AI can do the analysis, what’s left for leaders to do? After completing Athena’s Leading AI Transformation course, Kelli Richards found that the answer is surprisingly human.
When AI can do the analysis, what’s left for leaders to do? After completing Athena’s Leading AI Transformation course, Kelli Richards found that the answer is surprisingly human.
This article was originally published on the LinkedIn of Kelli Richards and is published with permission
I recently completed an eight-week certification program through Athena Alliance called Leading AI Transformation. It was co-created by my friend and colleague Jocelyn King (a leader in the cybersecurity world), and Coco Brown (founder and leader of Athena Alliance) – two women whom I respect a great deal.
I went into the course expecting to deepen my understanding of AI transformation: strategy, governance, organizational design, decision-making, adoption, ethics, and the practical realities of integrating AI into an enterprise.
And I did. But somewhere along the way, something more interesting happened as well.
The course changed some of the questions I’m asking. Instead of simply asking, What can AI do?, I find myself increasingly asking: What does AI require of us as leaders and what does it enable us to do more of as a result of its presence?
Those turned out to be much bigger and more meaningful questions.
Because the more capable AI becomes, the more visible our own leadership gaps (and opportunities!) become. AI doesn’t just expose inefficient workflows. It exposes fuzzy thinking. Poor decision-making. Organizational silos. Weak accountability. Cultures built around protecting territory rather than creating value. Leaders who confuse having more information with having better judgment.
One of the ideas from the course that stayed with me was that AI doesn’t create the need for strategic perspective. It makes the absence of it immediately visible and consequential.
That landed.
For years, companies have tended to treat major technology shifts as something to be delegated. Give it to IT. Form a task force. Launch some pilots. Hire a consultant. Buy some tools. AI doesn’t fit comfortably into that model.
If AI changes how decisions get made, how work gets performed, where expertise resides, how organizations allocate capital, and ultimately how value gets created, then AI belongs squarely in the leadership conversation.
And not just the CIO’s conversation.The CEO’s. The board’s. The leadership team’s. Because implementing AI and becoming an AI-native organization are very different things.
The latter requires leaders to reconsider the architecture of work itself: where machines should execute, where humans should exercise judgment, where accountability lives, and what happens to the capacity that automation frees up.
The course posed a particularly useful question: if 30–50% of processes eventually shift, what do we actually do with that liberated capacity?
That question deserves far more attention than it’s getting. Do we simply reduce headcount? Do we ask the remaining people to do more? Or do we consciously redirect human capacity toward innovation, relationships, creativity, judgment and growth? Those choices aren’t technology decisions. They’re leadership decisions.
Another shift for me concerned decision-making.AI is extraordinarily good at helping us generate possibilities, analyze information and interrogate assumptions. But leaders increasingly have to make consequential decisions in situations where information is incomplete, circumstances are changing rapidly, and there simply isn’t a knowable “right answer.”
The course explored several frameworks for operating in that ambiguity, including Roger Martin’s deceptively simple question:
What would have to be true?
Rather than arguing endlessly about whether an idea is right or wrong, ask what conditions would have to be true for it to succeed.
That subtle shift changes the quality of a conversation. It moves people from defending positions toward examining assumptions. And I suspect this capability will become increasingly valuable as AI gives us more options, more analysis, more scenarios and more apparent certainty.
More intelligence doesn’t necessarily produce better judgment. Sometimes it simply gives us more sophisticated ways of rationalizing what we already believe. The leadership advantage may increasingly belong to people who know when to question the answer — including the answer AI just gave them – and then do so!
This may have been the most important lens I took away from the program.
As AI becomes capable of doing more of the analytical and operational work we’ve historically associated with knowledge workers, we naturally focus on what machines will replace. But there is another way to look at it.
What becomes more valuable precisely because AI cannot provide it?
Athena challenged us to develop what it called a human value thesis: to become explicit about the human contribution in an AI-native organization.
The curriculum identified capabilities including moral judgment, first-principles reasoning, trust and human connection, leadership under uncertainty, meaning-making and presence.
I’ve thought about that a lot. Because the paradox of the AI era may be that the more technologically sophisticated our organizations become, the more valuable deeply human leadership becomes. And the more core attributes matter that are uniquely human; things like: discernment, courage, context, creativity, empathy, taste, trust, meaning, presence, and critical thinking.
The ability to walk into a complicated room, sense what isn’t being said, connect dots that don’t obviously belong together, and help people see a possibility they couldn’t see before.
Those capabilities are difficult to put on a dashboard. They are also becoming increasingly difficult to dismiss as “soft skills.” They may turn out to be some of the hardest currency we have.
This connected strongly with something I’ve been thinking and writing about independently: what relentless technological acceleration is doing to people.
Organizations often treat transformation as a communications challenge. Explain the strategy. Hold a town hall. Publish the roadmap. Train everyone on the tools.
But humans don’t experience disruption as a PowerPoint presentation. They experience it in their nervous systems and then start to ponder questions like:
Will I still matter? Will my expertise become obsolete? Can I learn this fast enough? What’s next? What happens to my team? What happens to me?
One of the course’s most useful observations was that the “valley” of disruption may no longer be a temporary phase between periods of stability. The valley may be the “new normal” climate. The leadership challenge therefore becomes helping people develop the capacity to move through repeated disruption without losing capability, commitment or the people who matter most.
That’s a profoundly different leadership mandate. We aren’t preparing people for one transformation anymore. We’re helping them become capable of transforming continuously.
We spend enormous amounts of time discussing AI capability. We spend considerably less talking about legitimacy. Should employees trust how AI is being used? Do customers understand what is happening with their information? Who is accountable when an AI-supported decision goes wrong? Where does human oversight begin and end? Who gets to decide?
One of the course modules put this starkly: trust is the limiting factor in AI adoption and organizational change. Governance, ethics and accountability therefore aren’t compliance activities sitting somewhere downstream from innovation. They’re part of the infrastructure that makes sustainable innovation possible.
That was a particularly important reframing for me. The companies that move fastest over time may not necessarily be the ones willing to take the most risk. They may be the ones that build enough trust to keep people growing and evolving.
For all the discussion of operating models, workflows, governance, strategic judgment and organizational transformation, the final session returned to something far more fundamental:
Who are you as a leader when it is hardest to be yourself?
I loved that the course ended there. Because leadership under pressure reveals things that leadership theory doesn’t. When uncertainty rises, do we become more controlling or more curious?
When AI challenges something we have spent decades becoming good at, do we defend our expertise or rethink it? When we don’t know the answer, can we say so? When technology gives us the ability to move faster, do we automatically assume that we should?
When everyone around us is chasing the newest capability, can we retain enough sovereignty to ask whether it actually serves the outcome we want?
Athena framed authentic human leadership not as the “soft” conclusion to AI transformation, but as what makes everything else durable — because without credibility, self-awareness and consistency, strategy, architecture and communication eventually break down under pressure.
That may be my biggest takeaway from those eight weeks.
I’ve spent much of my career around technological inflection points. And one thing I’ve learned is that the technology itself is rarely the whole story. The interesting part is what happens around it and as a result of it.
What we build. What we stop doing. What becomes newly possible. What becomes obsolete. What we choose to protect. And who we decide to become because the world has changed.
That’s why I’m glad I took the time to go deeper on this subject.
Not because I emerged with a tidy playbook for “doing AI.” Quite the opposite.I emerged with better questions.
And as we enter this next phase — when AI moves from experimentation to now being threaded into the actual operating fabric of organizations — I suspect the quality of the questions leaders are willing to ask will matter every bit as much as the power of the technology they’re learning to use.
AI may be transforming the enterprise. But first, it is transforming what leadership requires of us.
Kelli Richards is a lifelong native Silicon Valley innovator, leader and visionary; a long-time Apple exec mentored by Steve Jobs for decades. She works with some of the most innovative growth stage companies helping them to unlock the full vision of their founders and senior management teams as they continue to scale. providing continued support to c-suite management team leaders and clients on global growth strategy, key partnerships, and content and consumer initiatives. leveraging innovation and emerging technologies as well as new business models to work smarter, more efficiently, and to accelerate success.
Kelli has been called” a force multiplier” who combines more than 25 years of senior level business experience in tech innovation with her talent for bridging industry sectors, and connecting individuals and teams to their work in a way that liberates their untapped potential and accelerates growth. A trusted advisor to founders and innovators, she’s also a thought partner to senior leaders, family offices and creatives. Simply put, when someone has challenging expensive problems they can’t solve on their own, or they need fresh insights and are seeking new direction, possibilities or alternatives, they call Kelli.