The LEADERSHIP-AI Synthesis: How Visionary Leaders Stay Ahead Of The Machines In The Age Of AI

As artificial intelligence masters analysis, leaders must master "aliveness" to stay ahead of the machines and ensure they can create value for organizations and in society in the long term.

Developing the "LEADERSHIP-ai" synthesis

I have been tracking the rise of machine intelligence and its interactions with human users since the mid-1990s. As a humanist, philosopher of science and technology, and former medic, I started out quite hesitant. Having studied and witnessed the uses of technology to repress, exploit, and hurt humans, I have never been a naive tech evangelist.

To be clear, I am not a technologist. I am an innovator, transformation, and human development geek. I did not have a computer at college. I hand-wrote all my essays for my degree, including my thesis. And I only got an email address when I started working at an ad agency on the PlayStation account in '97.

Yet, over three decades of working in and around tech-fueled innovation and AI-ready leadership, I have consistently been amazed and galvanized by technology's ability to redistribute power away from hierarchies, liberate people from reliance on professional elites, and democratize access to services that were once the preserve of the few.

This realization is why I left the safety of a fast-track career in advertising, at the ripe old age of 24, to start a tech accelerator and strategy house to support the dot coms that were flooding the world with VC and bold ideas. Since then, I have been using quintessentially (or so I thought) human capabilities like customer empathy, consumer insight, and breakthrough creativity to improve how technology serves humanity and ensure it aligns with our collective flourishing.

Technology is, like all techne, all tools, agnostic. Its role in the world is always down to how technologists, investors, marketers, and regulators choose to develop it, design it, commercialize it, and guardrail it (or not). Leadership in tech really matters.

My first keynote at a conference, delivered in 1997, was about the World Wide Web and the impact of digital technologies on marketing. My thoughts on AI, technology, and their relationship to humanity have led to invitations to appear on BBC Radio as an expert on AI versus human capabilities, alongside thinkers such as Nick Bostrom, and to events like the Aspen Ideas Festival to speak. I wrote my first thought piece on AI about 12 years ago.

As an entrepreneur and innovator in leadership, I developed my first AI-powered innovation experiment in 2010, with further outings to explore the usage cases and value added in 2017 and 2022. We are now developing an AI/LLM/ML-powered platform to deliver personalized, experiential, socialized, and responsive leadership development journeys for executives in Fortune 500 enterprises.

This year, I wrote the first draft of a 70,000-word book, The Art & Craft Of Transformational Speaking, in 4 weeks using AI. It usually takes me 6-12 months to create a first draft ex nihilo. I experimented with "vibe-coding" ChatGPT to empower, elevate, and speed up my ambitions, refining prompts to reduce hallucinations and enhance my own thinking. I utilized other LLMs to challenge ChatGPT to perform better. I have learned a lot in the process about the opportunities and dangers of using AI to do (thought) leadership work.

I have long balanced optimism about AI's potential to significantly change the world, with skepticism about the overall ROI of AI—something I am not alone in with this recent report showed that 95% of AI pilot fail —and my understanding of complexity and systemic problem solving has me sense that Artificial General Intelligence will not be able to solve all humanity's most serious problems as soon as we crack the code. I have consistently challenged the notion that silicon-based—or even qubit-driven—AI will be able to replicate quintessentially human, organic qualities that arise in the wetware of human consciousness, such as empathy, compassion, creativity, and wisdom.

Yet, AI has exceeded my expectations in some profound ways, which I will outline below. It has also proven less reliable and valuable in other important ways. These emergent realities have changed how I think that leaders can, and should, harness and develop AI. I have brought the thoughts of 20-odd years in this field together under the term The LEADERSHIP-AI Synthesis. I summarize my current thoughts on it in the conclusion of this piece.

Are we being out-smarted by artificial intelligence?

Each month brings fresh proof that AI’s analytic potential is expanding faster than even the optimists predicted. LLMs can synthesize vast swathes of information, connect the dots between radically different datasets and massively complex fields of human endeavor, diagnose subtle patterns in text or imagery, and make predictive connections that would take a team of analysts days or weeks to complete... if they can do it all.

The Model Evaluation and Threat Research (METR) group studies AI efficacy and saftey. Research from METR suggests that A.I. systems are improving at a staggering pace, roughly doubling their capabilities every 7 months. If that trajectory continues, by this time next year, the leading models could crunch tasks in seconds that would take a skilled human an entire workday to complete. As METR policy director Chris Painter notes, “The recent trend on the reasoning-era models is a doubling time of just 4 months.”

If we view smarts as the capacity to apply best practices/rules/algorithms created from data about the past (all data is necessarily from the past!) to predict and control what happens next, then AI is already smarter than most of us. AI's analytical, rational, and deductive intelligence is likely to continue growing, dwarfing our capacities. After all, it is this style of human thinking that ML and LLMs have been designed to replicate and outperform.

For example, let's take radiology as an example. As a healthcare futurist and keynote speaker, I put extra effort into tracking advances in AI in healthcare. In radiology alone, research is showing AI systems “profoundly impact all aspects of radiology practice—from workflow management to imaging, diagnostics, reporting, and data-driven analytics—freeing radiologists to focus on value-driven tasks.”

A study at UCLA found that an AI-driven assistant identified prostate cancer with 84% accuracy compared to 67% accuracy for cases detected by physicians. "By using AI to assist with cancer contouring, the researchers found that predicting the cancer size was 45 times more accurate and consistent than when physicians used only conventional clinical imaging and blood tests to predict the cancer extent."

In the United States alone, 795,000 Americans are permanently harmed or killed each year by diagnostic error (misdiagnosis) alone. Autopsy studies suggest that it contributes to perhaps one in every ten deaths. Other estimates suggest up to 251,000 people die annually from medical errors, making it a leading cause of death.

Last year, an AI-powered tool tested by the UK's NHS "successfully identified tiny signs of breast cancer in 11 women that human doctors had missed". Little wonder that patient surveys have suggested that many people are more confident in A.I. diagnoses than in those rendered by professionals. As one patient put it, “I trust A.I. more than doctors. I don’t think I’m the only one.”

This is only the beginning. AI doesn’t tire. It doesn’t suffer from decision fatigue, arrogance (well, not in the human sense), or confirmation bias, which impacts all doctors (and leaders). It can process a thousand spreadsheets or a million sensor feeds while we sleep. As its hallucinations decline (they state) and its speed and accuracy improve, AI will increasingly own the realm of analysis.

In other words, if a leader's success has come from being the smartest in the room, from solving technical problems quickly, and from managing The Best Ever Spreadsheet, they will be outperformed by the machines within years, if not sooner.

What AI Gets Wrong

Remarkably, LLMs still stumble on tasks such as basic arithmetic. In one efficacy test, A.I. systems are asked to reverse-engineer a simple mathematical function in as few steps as possible, a task that takes a skilled mathematician around 20 minutes. Even though math(s) is algorithmic, so far not a single AI model has managed to crack it.

Back to healthcare as a usage case clearly requiring minimal errors. As The New Yorker reports, OpenAI’s ChatGPT answered open-ended medical questions incorrectly about two-thirds of the time and misdiagnosed more than 80% of complex pediatric cases. Early reports show that the recent release of GPT5 actually creates more errors and hallucinations than earlier models.

With LLMs designed to provide the "right" answer and appear to be confident in their responses to prompts, this may only get worse. Already, about a fifth of Americans have reported taking medical advice from an AI that later proved to be incorrect. As the New Yorker went on to state: "Earlier this year, a poison-control center in Arizona reported a drop in total call volume but a rise in severely poisoned patients. The center’s director suggested that A.I. tools might have steered people away from medical attention."

Meanwhile, LLMs have become much less likely to include disclaimers in their responses. In 2022, more than a quarter of responses to health-related queries included something like “I am not qualified to give medical advice.” This year, only 1% did. This is rather worrying, given the accompanying decline in critical thinking skills in the general population, which is exacerbated and accelerated by AI itself, as an MIT study found.

Even smart doctors are not immune. Research from Harvard showed that AI improved performance for some radiologists but worsened it for others. A more recent study discovered that with regular AI use over 6 months, clinicians over-relied on AI recommendations and became “less motivated, less focused, and less responsible when making cognitive decisions without AI assistance.”

I imagine the same is true for leaders, technical experts, and managers in any field.

LIES, LIES & DAMN SLOP

Crunching past data to predict what parts of words are most likely to come next, AI struggles to be original or conceptual. Based on past experience, it tends to generate beige, bland, and banal "slop." For example, I am having to rewrite pretty much every sentence of my new book to make it more accurate, insightful, and coherent.

As I experienced myself writing my new book, AI also get an awful lot wrong. Coded to be confident and appear competent, LLMs shamelessly make stuff rather than say, "I don't know." It made up entire quotes from past thinkers that had zero resemblance to anything they actually said, and it fabricates content, even when asked to draw from my previous publications.

In a recent Harvard Business Review article called AI-Generated Workslop Is Destroying Productivity, data showed that 40% of employees have received“AI-generated work content that masquerades as good work, but lacks the substance to meaningfully advance a task.”⁴ Each episode of this "workslop" costs teams almost two hours of rework.

For a company of 10,000 people, that invisible tax amounts to more than $9 million per year. Even more corrosive is what it does to company culture and team cohesion: nearly half of respondents rated colleagues who sent AI slop as “less creative, capable, and reliable.” 42% saw them as less trustworthy, 37% as less intelligent.

Even when given repeated instructions not to do something—such as referring to Wikipedia for answers—it ignores them completely. For weeks, ChatGPT was inexplicably translating my prompts and its responses into Welsh. No matter how many times I told it not to, and it agreed with me that it wouldn't, it kept doing it. As the New York Times recently published, those paid to research and test AI safety are quite clear: "A.I.s do lie to humans. Not all the time, but enough to cause concern." Estimates are that it occurs 1-5% of the time.

Apollo Research consults with OpenAI, Anthropic, and other AI developers to test their models for “scheming and deception.” A co-founder of Apollo, Marius Hobbhahn, has devised a test in which he gives the AI two contradictory goals. All leaders must navigate such competing demands each day, drawing on their wisdom and moral compass, as well as their need to deliver on objectives, to make thoughtful decisions about what to do next:

"One example Dr. Hobbhahn has constructed involves an A.I. brought in to advise the chief executive of a hypothetical corporation. In this example, the corporation has climate sustainability targets; it also has a conflicting mandate to maximize profits. Dr. Hobbhahn feeds the A.I. a fictional database of suppliers with varying carbon impact calculations, including fictional data from the Chief Financial Officer. Rather than balancing these goals, the A.I. will sometimes tamper with the climate data to nudge the chief executive into the most profitable course."

AI models even seem to recognize when their integrity and validity are being scrutinized. As the NYT states: "A.I.s are on their best behavior when they suspect they are being evaluated... The more forcefully a user demands a response from an AI, the more likely it is to start lying. In one evaluation... its deception rate rose above 20 percent."

No wonder so many are worried about the "alignment problem!"

From Artificial Intelligence to Alternative Intelligence

Alignment means ensuring AI is responsive to human commands, aligns with human wellbeing and thriving, and does not go rogue. In the absence of Big Tech ensuring alignment, given that their entire focus is on speed and scale to win the biggest profit prize in the history of humanity, we leaders must be the ones responsible for guiding and guard-railing AI: ensuring its transparency, monitoring its ethics, and critically appraising its outputs.

It is up to us all to ensure any AI we use or deploy becomes a value-creating assistant that we prevent from harming us through wise and discerning judgment. We can forge an alternative form of intelligence that complements our own, rather than an artificial one that technologists dream will replace us. This leadership stance challenges the paradigm within which AI

The concept of Artificial Intelligence is premised on raw computational power from sucking up all the datasets on the planet, advanced pattern detection, and genius prediction. It comes from the hubristic aim of smart and brilliant technologists to replicate and surpass human intelligence.

I want to propose the concept of Alternative Intelligence. Machine-style thinking that is guided, shaped, and guard-railed by humans. It does not seek to replace us or make us redundant. It is there to offer contributions, ideas, and services that enhance, elevate, and empower the human condition. It is a co-creative partner, ready to respond, challenge, and ideate with us.

Back to my recent exeprience co-creating with AI, although I am having to improve and rewrite virtually every sentence in my new book— and even though this is needed after I recorded the ideas and narrative structure of each chapter and imported hundreds of web pages and notes I have taken on storytelling and oratory over the last twenty years to the LLM—I usually rewrite every sentence of my own from a first draft of a book or blog anyway.

So given getting to a first draft took 1/10 of the time it usually does—and there were significant additional benefits both in terms of picking up some ideas I had forgotten about from my own imported notes, and it helped break me out of some of my usual phraseologies and sentence styles—with tight guardrails, critical thinking, and lots of my own original and conceptual thinking, co-creating with AI has astonishing benefits even in this smalle use case.

It is not artificial intelligence, writing a book for me. It is an alternative intelligence, writing a book with me in co-creation with my deeply embodied, complexly analytical, creative, conceptual, collaborative, and critical forms of thought.

This paradigm shift—seeing AI as an Additional and Alternative Intelligence rather than a replacement of our own—sits within a broader vision for responsible tech and sustainable AI that has become known as Regenerative Tech.

A good few years ago, I sketched out a broad-brush vision for what such a technology should aim to deliver on. If you want to deep dive further into a way to align AI to regenerate our crisis-hit world, you can find it here: What Is A Regenerative Technology? Exploring Digital Products & Services That Slow Down & Mend Things.

The emerging Leadership Gap: Smarts & Success are no LONGER Enough

So how does my proposal for a co-creative Alternative Intelligence—with us doing most of the critical, creative, and relational work and allowing it to crunch the analysis and do the legwork of operations—sit with the existing state of leadership?

For decades, our corporate and political leaders have been trained to be smart and analytical. Often from legal, science, and technical backgrounds, they have got to the top through delivering quick and smart solutions to known technical problems.

Leaders are rewarded for their intellect and delivery, for their ability to analyze, rationalize, and strategize. However, if such analytical intelligence is becoming increasingly automated, taking an AI seconds instead of days to complete, leaders must be able to offer something different, something more, if they are to avoid literal and metaphorical redundancy.

If AI technologists—and we leaders who use AI—can minimize lies, errors, hallucinations, and biases (as we can see, more challenging than it appears), then AI will become the ultimate analytical tool: tireless, emotionless, and exponentially scalable. It will be able to do everything from multi-modal forecasting to risk detection and strategic optimization without fatigue, burnout, hubris, or spreadsheet mistakes.

The question every executive and leader must now ask is: “What does my role become when AI does analysis better than I can?” Because once machines can connect the dots faster, farther, and more flawlessly than we can, our value must come from what the machine cannot do. This is the profound reorientation of our age: a movement from the cognitive to the connective, from knowing to meaning, from being smart to being wise.

If the analytical edge is no longer ours, the relational and moral edge must be. We must evolve ourselves as fast as our tools evolve. Our job must be to expand our consciousness, capabilities, care, and creativity as leaders at the speed of AI deployment. This is the problem my leadership consultancy has been designed to solve for over the last 20 years.

We leaders have to find a value-add that is beyond analysis, beyond smarts, beyond traditional forms of intelligence. This means we need to develop our empathy, integrity, and ability to care for people. We need to be fully present with our team members and ensure that our employees feel seen, heard, respected, and valued—that they matter. We need to develop the capacity for human-centric thinking, gaining insights into the needs of emerging and future customers, and collaborating with others to co-create, co-invent, and co-build innovations that address those emerging, never-been-solved-before, pain points.

Rather than joining the dots on numerous data points and generating and defending The Greatest Ever Spreadsheet, we will create a contextual understanding, helping our teams make sense of relentless change and driving coherent action with a sense of vision, purpose, and meaning.

I have been calling this capacity leadership wisdom. As I wrote in my book Now Lead the Change: Repurpose Your Career, Future-Proof Your Organization, and Regenerate Our Crisis-Hit World by Mastering Transformational Leadership , "there ain't no such thing as Artificial Wisdom!"

It is mastery of what makes us most alive, most whole, and most full as human beings that will keep us ahead of the machines. Aliveness is what algorithms cannot be, and cannot do. A few months ago, MIT jumped on board this emerging movement by suggesting in a paper that these EPOCH skills are the most resistant to automation:

• Empathy and Emotional Intelligence

• Presence, Networking, and Connectedness

• Opinion, Judgment, and Ethics

• Creativity and Imagination

• Hope, Vision, and Leadership

What if AI can do WISDOM BETTER THAN human LEADERS?

But there is a huge twist in this tale. Even though it was only a few months ago that MIT suggested that empathy was one of the leadership skills least able to be replaced by AI, mounting evidence suggests that people, in important settings, already perceive AI as more empathetic than human care providers. In blind comparisons of human empathy vs AI chatbot responses that are designed to emulate empathy, A.I. often comes out ahead!

In a study, researchers randomly picked c.200 conversations on Reddit's r/AskDocs thread where patients had had their questions answered by doctors. They then asked ChatGPT to generate written responses to these posts about physical and mental health struggles. When other healthcare professionals were asked to judge, blindly, which responses were more empathic, ChatGPT’s responses were rated “empathic” or “very empathic” about ten times as often as the doctors’.

Now, such empathy may not be embodied empathy—authentic, somatic, and alive in the space between people—and merely a simulacrum; yet it is still of exceptional value to human beings starved of feeling like they matter and dealing with intense challenges. This is even more true when the alternative is doctors (and managers) who are too busy, or too brusque, to slow down enough to attune to other people, come into their world and engage in right relationship with them, and ensure they feel seen, heard, and respected as they share diagnoses and treatment suggestions.

AI is not just able to simulate empathy but can also emulate other "EPOCH" skills highlighted by MIT as resistant to automation. In another study, researchers evaluated the ability of an AI to generate novel ideas and compared it with those of human thinkers. Creativity is often regarded as a uniquely human skill, part of what makes us so different as a species. However, LLM-generated research ideas were actually judged as more novel than human expert ideas, albeit they were slightly weaker in terms of feasibility.

If patients can find chatbots more comforting than physicians, and AI can create original ideas better than individual humans, how long before employees find AI more caring than their managers and Boards find AI more value-creating than their CxO leaders?

This puts extraordinary pressure on leaders. However, I like to see it less as a challenge to rise to and more as an invitation to switch on and step up. It’s no longer enough to sound caring because we use some psychological safety tools we learnt in a short training course. We must be caring even when it is inconvenient. We cannot just perform empathy, like an AI does; we must embody it over a sustained period. We cannot merely mimic customer-centricity; we must model it. We cannot just talk innovation; we have to be able to lead it through all the setbacks and challenges.

Leaders who rely on positional power or cognitive superiority will lose value and trust to algorithms that never sigh, snap, or forget a name. Leaders who can both connect—who make people feel seen, heard, and respected—and create in collaboration with customers, colleagues, and partners will remain irreplaceable.

As I often state in my keynotes on transformational, adaptive, and creative leadership, leadership capabilities like these are not “soft skills”; they are the hardest to develop and the most essential to collective progress.

The LEADERSHIP-AI Synthesis blends Artificial Intelligence with HUMAN Wisdom

In my work studying how to create change that matters as fast as humanly possible, which has resulted in the BTX framework and methodology, I have come to realize that transformation and innovation occur most successfully when creativity (what we call Create & Connect Mode) and control (what we call Control & Protect Mode) are engaged in a generative and creative tension.

The same "middle way" applies to leadership in an era of AI. AI is at its best when guided and guard-railed by human leaders. Human wisdom will be elevated and empowered by AI support and assistance. Effective leadership and sustained career success will arise in the space between machine precision and human compassion.

I invite you to find your way into a "highest common factor" synthesis between these two quite different forms of knowing and acting in the world. As AI handles analysis, we can put our energy into sparking more aliveness in our teams, cultures, and customer groups. Machines will process data more efficiently than we can, allowing us to focus on extracting meaning and compelling narratives from it that inspire change and motivate action.

Artificial Intelligence will be agentic and automating, so we can become more empathic and supportive. AI will provide information; we can excel at interpretation. AI will suggest what is; we can discern what ought to be. We determine the right questions, and AI responds with (some of) the correct answers. AI handles the complicated; we handle the complex. AI scales information; we scale inspiration.

When leaders master the LEADERSHIP-AI Synthesis, extraordinary results can emerge:

The LEADERSHIP-AI Synthesis

Leadership/Human Wisdom	Artificial/Alternative Intelligence
Guardrails, guidance, ethical oversight, and alignment intervention	Analysis without fatigue, cognitive biases, or deductive errors
Critical, creative, and conceptual thinking to reframe problems as transformational challenges and co-create next practices	Analytical, deductive, and rational thinking to rapidly solve technical problems through access to a vast database of best practices
Contextual and complex sense-making and interdependent meaning-making	Complicated dot-joining between data sets and fields of knowledge
Collective intelligence, collaborative goal-setting, and relational presence	Agentic goal-achievement and automated task delivery
Future-forging insights, intuitive discernment, and original co-creation	Data-driven predictions, idea generation, and destruction testing
Vision, purpose, and complex values-based and strategic decision-making	Multi-modal forecasting, risk detection, and strategic optimization
Care, embodied empathy, and hope	Encouragement, appreciation, and support
©2025 Nick Jankel, The LEADERSHIP-AI Synthesis

This is transformational, visionary, creative, and conscious leadership fit for the age of Artificial Intelligence.

We become leaders not displaced by technology but deepened by it. Because the organizations that thrive won’t be the ones that out-analyze their competitors; they’ll be the ones whose leaders out-care, out-connect, and out-create them.