Why I Propose "AI-Powered Transformation": When Organizational Middle Age Meets Technological Adoles

At the CHEERS 2026 National Reading Week conference, Yang Bin, a professor at Tsinghua University's School of Economics and Management, delivered a speech titled "AI-Powered Transformation: When organizational middle age Meets technological adolescence." He explored enterprise AI transformation, emphasizing that the real obstacle lies not in Technology itself but in the deep misalignment between organizational mindset and the APProach to change.

Yang Bin argues that the current predicament faced by global enterprises stems from the clash between "organizational middle age" and "technological adolescence."

"Believing that simply purchasing a top-tier large model and handing it over to the IT department will complete the transformation is a typical 'IQ tax' paid by entrepreneurs," Yang Bin stated.

In his view, disruptive innovation often emerges from the periphery, rather than from the center dominated by "organizational middle age." Regarding how enterprises should pivot in the AI era, Yang Bin believes that both AI large models and organizational mental models must be upgraded simultaneously—neither can be neglected.

During the speech, Yang Bin cited two extreme cases—NVIDIA and Kodak—to illustrate how enterprises either adapt to or fail in the face of new technology. Nvidia bet on a "zero-billion-dollar market" and ultimately achieved nonLinear explosive growth. Kodak, on the other hand, represents a classic counterexample: trapped by the typical "organizational middle age" mindset, the company shelved its in-house developed digital camera technology and ultimately collapsed in the digital age.

"'Organizational middle age' pursues immediate performance and mainstream consensus, which violently collides with the fast-iterating, surprise-filled, uncertainty-laden 'technological adolescence.' This either suppresses technological potential or triggers organizational disorder," Yang Bin said.

Below is the full text of Professor Yang Bin's speech (edited and abridged):

01 The Positioning of AI
I propose "AI-powered transformation" to correct a now-popular notion—that "+AI" or "AI+" brings serious misguidance to enterprises. If AI's impACT on organizations is treated merely as a technical issue, relying on IT departments to drive AI transformation, it will bring enormous trouble to enterprises.

The subtitle of today's speech is a Metaphor I coined: "Organizational middle age meets technological adolescence." This is not just a thought experiment I hope to conduct with everyone; this metaphor authentically and accurately reflects the greatest challenge facing countless enterprises worldwide—arguably the number one challenge, a vivid portrayal of what is unfolding right now.

AI is hugely popular, but many anxiety-peddling, sensationalist public accounts churn out "IQ tax" platitudes daily. AI neither achieved overnight success nor is anywhere near a "second half." AI Development will be a long process, and we have only just begun. If ordinary people listen to these misguided notions, it may not matter much. But if they enter the minds of entrepreneurs and dominate their choices and decisions, they will easily pick the wrong direction when driving transformation. Outdated mindsets will lead to severe consequences.

For instance, if enterprises believe that one single model will solve everything—that procuring or customizing the most powerful large model will strengthen the organization, or that CIOs and IT departments should lead AI transformation—this will lead to irreversible defeat. Compared to ordinary people, the IQ tax paid by entrepreneurs is far more costly. New technology often exhibits age-reversal effects; older indiViduals have lower sensitivity, and CEOs' cognitive ambiguities are not easily corrected.

Let me share a real case. Many consider 2012 the inaugural year of "Internet + Education." I recall in the autumn of 2013, during a Tsinghua SEM Advisory Board meeting, the board chair suddenly posed a question to a prominent Chinese entrepreneur in the internet sector: "You are a leader in the internet industry; what do you think about the future of Internet + education?"

The entrepreneur replied somewhat irreverently with a rather absolute conclusion: "I don't know what the future of online education looks like, but I am certain it will not be born in top-tier universities like Tsinghua." This was quite blunt, and I still ruminate on it from time to time. I think it may reveal a profound truth: the mainstream is often willing to make improvements, but real transformation usually comes from the periphery, from outsiders, not from the center—or, using my term today, disruptive innovation will not emerge from "organizational middle age."

02 "Model": One Model, One World; Emergence Inside and Out
Today, when people mention "model," they often think first of AI. Consider the "Hundred Models War." It is interesting that the English word "model" and the Chinese character "模" (mó) sound so similar, as if one were transliterated from the other. In fact, they are not; they have different origins in East and West, two branches blooming separately, each evolving to this day.

Today, every AI large model compresses a world within it. The most wondrous aspect of this process is emergence. AI has scaling laws; complex systems that grow large enough, through compression and Generalization, yield emergent Intelligence. Speaking of emergence, it is fascinating that not only does emergence occur within large models, but if you observe the AI industry's development, the massive explosion of the last decade is also a form of emergence—this process is one of emerging, not planning.

Thus, AI exhibits the beauty of emergence both internally and externally; greatness is born of emergence. Great innovation is often not planned by organizations or leaders. UnderStanding this is crucial to grasping how AI transformation should be conducted.

Emergence cannot be planned, but it does have patterns—for example, how different parts of an ecosystem mutually enable each other, reaching a state of "readiness." The reason AI has exploded so Dramatically in recent years is that the internet prepared the Vast Data AI requires, while new GPU architectures provided the crucial computational possibilities.

Let us examine a case I teach on NVIDIA's strategic resolve—though "resolve" really means steadfastness combined with adaptive evolution. Jensen Huang's strategic vision lies in his willingness to embrace innovation (like CUDA) for what he calls a "zero-billion-dollar market"—unknown demand, technologies dismissed as useless by others but which he firmly believed would prove essential, eventually turning uselessness into great and widespread utility. This tolerance for uncertainty, combined with strategic patience and, of course, the serendipity of timing, ultimately enabled NVIDIA's nonlinear explosion in the AI era, becoming the convergence point of everything.

This cARRies important implications for understanding the core philosophy of "AI-powered transformation." AI-powered transformation is exactly this: context, not control; emerging, not planning. You will find that some initially "useless people"—non-mainstream individuals—will emerge, dEMOnstrating irreplaceable usefulness. But you cannot plan or control this generative process; you must embrace it. This is evident in Jensen Huang's story and many other AI-era innovation stories.

I would like to turn the clock back to 1943. That year, World War II was rAGIng. Coincidentally, two papers published in 1943 represent the respective starting points of two important Threads that extend to this day.

In that year, neuroscientist Warren McCulloch and mathematical logician Walter Pitts published a paper titled "A Logical Calculus of the Ideas Immanent in Nervous Activity." This paper became the starting point for the neural network algorithms that underpin today's breakthroughs in large models.

Also in 1943, a Cambridge professor who died young—Kenneth Craik, killed in a car accident the day before Victory in Europe Day—published "The nature of Explanation." This book is the origin of the term that enterprises and entrepreneurs love to use today: "mental model."

This gives us a fascinating insight: both models—the AI large model and the mental model—can be traced back 83 years to 1943. Craik sought to summarize the essence of human intelligence and identified the small-scale world models in the human mind. Interestingly, large models are "large scale," but what Craik wrote about then were "small scale" models, because human cognitive bandwidth requires compression into small scale for rapid thinking. How do we humans perceive people, events, technology, and change? Each of us holds such a small-scale mental model in our minds. Based on our respective mental models, we analyze, predict, and react to the vast external world. In other words, the Same people and events can yield different interpretations and reactions depending on the mental model. Therefore, for organizations to achieve AI transformation success, the intelligent large model is certainly important, and the mental model is equally important. Both models, together, are indispensable—this is a fundamental understanding of AI-powered transformation.

03 The Pi Day Proposition: What Mental Model Should We Adopt for the AI Era?
"AI-powered" is a concept I proposed on March 14 last year—Pi Day—as distinct from and even opposed to the "+AI" mental model. The plus sign is wrong; it belongs in the exponent position: "AI-powered." AI-powered transformation represents a new transformation model built on this new mental model.

Since its introduction, "AI-powered" has drawn enthusiastic responses. People from different industries hope to use this new mental model—which can be seen as new glasses, a new lens—to examine what AI truly means for themselves, their enterprises, and, more broadly, every individual and organization. Those in education and manufacturing alike agree that the plus sign may fail to capture the essence of this transformation; it must be replaced by "AI-powered thinking."

There is a Native American proverb: "Slow down and let your soul catch up." This is exactly what we need today. If we observe what is happening now, you will see that technology—the external model visible and tangible to all—is developing with incredible speed, changing daily. But at the same time, is the other "model"—the soul, or the mental model of people and organizations—keeping pace with such rapid steps?

As technology surges forward alone, are business models, organizational models, and the foundation underlying them—internal mental models—keeping up? To be honest, I believe the gap is significant, and there are reasons for it. A key reason is that the mindset reflected behind the plus sign is very stubborn. I call this mainstream mindset, which is destined to suppress AI transformation, "organizational middle age." During periods of environmental stability, organizational middle age ensures performance. From the outside, it appears calm and steady—until stability is disrupted, especially as it is now, colliding with "technological adolescence."

04 Technological Adolescence: Eager to Act, Challenging the System
The metaphor of "technological adolescence" originates from Carl Sagan's science fiction novel "Contact," published in 1985 and adapted into a film in 1997. Before meeting aliens, the female scientist played by Jodie Foster is asked: "If you could only ask one question of an alien civilization, what would it be?"

She replies that she would ask: "How did you do it? How did your civilization survive technological adolescence without destroying itself?"

Imagine "technological adolescence" as a metaphor: technology is now eager to act, growing and even changing form every day, developing capabilities the adults have never seen. It has strength but no rules; not intentionally, yet it challenges existing systems and habits, feeling omnIPOtent. On the other hand, a relatively mature mindset—whether human civilization's mindset or organizational mindset—collides with it. Note: we cannot say human civilization's mindset is immature; rather, it is the previous generation's maturity, unprepared for or lacking a new mindset that matches the new technology. Similarly, we cannot say organizational mindset is immature; it is precisely its maturity that manifests as "organizational middle age." Technological adolescence iterates rapidly, not yet fully formed; organizations are a stable middle age, suppressing change and prioritizing steady ouTPUt.

Last year, I repeatedly recommended Norbert Wiener's 1950 book "The Human Use of Human Beings." I argue the title should be translated to emphasize "the human use of human beings." In this book, Wiener wrote: "We have so profoundly modified our environment that we must now modify ourselves to continue to exist in this modified environment." This rings so true: technology has transformed the world, forcing us to change; and to change ourselves, we must first recognize ourselves—whether we are willing to change, and whether we change easily.

05 Organizational Middle Age: Learned Maintenance of Normalcy
Corresponding to "technological adolescence" is a symmetrical metaphor I propose: organizational middle age.

This is an insight I have developed over a long period regarding organizational management and leadership, distilled and succinctly termed "organizational middle age." This does not refer to organizational age, nor is it related to years since founding or size; it is a mindset. Its core is "learned maintenance of normalcy," characterized by four prominent features:

Immediate performance-driven: responsibility, delivery, output.
Mainstream consensus: preference for order and consensus.
Linear steady progress: emphasis on improvement, aversion to exceptions.
Cognitive narrowing: feedback based on trust, self-reInforcement.

Please do not misunderstand: organizational middle age does not carry the word "crisis" after it. Middle age bears heavy burdens; culture has formed a "model," power has reached equilibrium, and structures that work prefer marginal improvements over systemic reconstruction.

Now, let us conduct a thought experiment: you may have seen films where two people collide and their minds and bodies swap. Consider this scenario: what happens when a middle-aged mind enters an adolescent body, or vice versa? What interesting or contradictory conflicts arise?

It is worth pausing and thinking carefully. But perhaps, once you think about it, it is hard to stay calm. Because this is not just an imaginary thought experiment; it is precisely the dilemma most enterprises are facing today.

Due to "learned maintenance of normalcy," organizational middle age accumulates heavier and heavier baggage. What burdens does organizational middle age carry? I summarize them as the "Five Names": nominal identity, reputation, nomenclature, ranking, and nominal standing.

These "names" cause organizations to be "capitalized." You can refer to an article I wrote inspired by the first sentence of "The Story of Art": "Capitalizing Deification, Lowercasing Humanity." Once an organization is "capitalized," making changes often exceeds the CEO's control. Capitalized, solidified, trapped in a cocoon, organizational middle age truly cannot tolerate uncertainty, exceptions, or even pleasant surprises—nor does it welcome outliers or marginal figures.

New is a pleasant word, but new also means different. When something new emerges, the first impulse of organizational middle age is not to embrace the "new" but to eliminate the "different." A common practice is rushing to name the new thing—using old language to name it, bringing the new thing into mainstream Cognition, making it a "beneficial supplement" to the mainstream. Everyone, when something new becomes "a beneficial supplement to our mainstream," what is the subtext? The subtext is that by calling it a "beneficial supplement," there is no need to transform the mainstream itself. Essentially, there is no need to worry that this "different" thing will someday threaten or replace the mainstream, so organizational middle age can continue comfortably.

True innovation is not about the performative tolerance of error but about tolerating difference, tolerating crudeness, tolerating growth. What we most need is to linger a little longer in that uncomfortable state of namelessness, patiently waiting for those strange, unnamed things to grow. They will name themselves eventually, but not now.

Schumpeter said that entrepreneurs are responsible for rewriting the production function, but once rewritten, the entrepreneurial state ends; thus, "entrepreneur" is not a noun but a verb. I quote him here and add my insight: once something is DeFined as a noun, in my view, it enters "middle age." When I conversed with Professor Mintzberg, "organizing"—with its fluid sense of ongoing action—became our way of discussing organizations in the AI era, rather than nouns. These days, some say the One-Person Company represents the future of organizations. I think that is premature; the core characteristics of future organizations—whether "P" (person) or "C" (company)—require even greater imagination and creativity.

06 The Collision: Two Typical Conflict Scenarios
When organizational middle age collides with technological adolescence, two typical conflict scenarios erupt:

First: the middle-aged mindset suppresses the potential of the adolescent body, preventing technology from exerting its true power. This is a once-in-a-lifetime qualitative opportunity.

Second: the adolescent mindset rampantly charges through the middle-aged body, challenging various systems. If all this happens quickly, it leads to organizational disorder, and the adolescent force gets expelled.

Neither scenario is what we want. True lasting success—"built to last," beautifully translated in Chinese as "everlasting vitality"—is what enterprises seek. Here, I offer a new interpretation: lasting vitality means keeping the organization perpetually in a "youthful" state, dynamically adapting to technological adolescence, enabling mutual continuous evolution in a hyper-dynamic environment.

Organizational middle age represents a mature mindset matched to previous generations of technology. To return to adolescence is to live again, to enter the next generation's adolescence, which means the organization must be "reborn"—what I will later describe as "breaking attachments and reconstructing."

07 The Trap of the "+": Organizational Middle-Age Mindset
We often say "+AI" or "AI+", and behind this plus sign lies the organizational middle-age mindset. It represents a quantitative, controllable, short-term results-oriented way of thinking. This mindset cannot comprehend the nature of AI's technological adolescence.

For instance, it fails to understand that AI is not a mature tool today; it changes every day, baseline capabilities keep rising, and paradigms could shift dramatically. For this moving-target technology, the clear objectives required by Porter-style transformation do not exist, and control-heavy approaches to change will not work. Technological adolescence will also force organizations to deconstruct and reconfigure growth. If we see through the mindset behind the "plus sign," it assumes that the "+AI" transformation process is a hArmonious "better upon better"—which is an unrealistic Fantasy. If it were truly harmonious, it would not be called transformation.

Real AI-powered transformation involves significant discomfort, pain, and conflict, especially within people's minds, breaking away from familiarity and comfort. This rupture is not felt in the "plus sign," which is why I say the plus sign misleads; we must puncture this illusion. AI-powered transformation demands breaking away from the five familiar and comfortable "names"—"not being misled by names"—and breaking away from familiar and comfortable "ego attachments"—"breaking attachments and reconstructing." Break first, then build, but building is not top-down, nor can incumbent leaders or CEOs plan and control it. Instead, create the "context" for change, enabling all organizational and ecosystem members to engage together in "generative emergent transformation."

08 Why Must AI Transformation "Break Attachments"? Why Does the Kotter Model Fail?
I propose "generative emergent transformation" to seriously challenge the Kotter model of change. Why is it that John Kotter's classic, somewhat linear, top-down, control-driven change management model is extremely difficult to succeed in the AI era, destined for failure?

Why do I keep emphasizing "unlearning" in the AI era? You must unlearn; you must deliberately forget; you must break attachments—break ego attachments, break name attachments, break winning attachments. Why?

During the Spring Festival, those commercial offensives still using red envelopes to buy inFluence, traffic, and users remain immersed in the organizational middle age's many familiarities and comforts, still using that handy hammer, treating technological adolescence as a nail. Unlearning has not occurred. This is the "+AI" or "AI+" approach, not the AI-powered transformation strategy.

In AI-powered transformation, the base "x" must first transform from capitalized to lowercase. The capitalized base is a typical characteristic of organizational middle age. Only a lowercased "x" has a future. If the base does not undergo qualitative change under AI's influence, it becomes a base less than one. When the base is less than one, what happens? The power collapses and shrinks. Therefore, placing AI in the exponent position requires, first and foremost, qualitative change of the base, forcing the base to break attachments and reconstruct—this is the mental model shift I have been relentlessly promoting since Pi Day last year.

AI-powered transformation subjects the base to a first-principles, essentialist examination and truth-seeking. If you view this base as a set, you will find that different components within the set—whether capabilities or knowledge—undergo a "core-focusing" effect under AI's influence. Some elements that better embody human essence, business essence, and contribution essence will be retained and become more central; others will be, and "should" be, replaced by AI.

Because of AI-powered transformation, differences in the base are magnified, leading to the K-shaped divergence everyone is beginning to observe, which will become even more complex in the future.

Because AI-powered transformation occurs with AI itself in adolescence and in the exponent position, it will inevitably catalyze emergence—both internally and externally, both base and exponent will experience corresponding emergence, ultimately giving rise to unprecedented new things and new rules. Future organizations may be dynamically networked communities of free "super-assemblages."

Emergence is more complex than we imagine but also simpler—it just contradicts our habits: we must try not to control but trust the power of the AI system. Fear of losing control will suppress emergence.

09 AI+ vs. AI-Powered: A Comparison of Power and Culture
Let me specifically highlight some important distinctions between "+AI" and "AI-powered." First, an insight regarding power and culture.

Why is "+AI" so popular? Because in the "+AI" mindset, existing power and interests are not challenged, nor is there readiness for fundamental changes to existing culture and basic assumptions. Marginal improvements demand limited power restructuring.

And AI-powered transformation? The breaking of attachments, reconstruction, and generative emergent transformation demanded by AI-powered change will inevitably require shifts in power and renewal of culture. This is very difficult for incumbents, for those who hold power or interests. This is precisely why improvements disguised as transformation are more easily accepted by vested interests and incumbents.

10 Practicing AI-Powered Transformation: Marginal Figures and Frontier Domains
How should AI-powered transformation actually be practiced?

The traditional top-down approach—knowing the goal, proceeding step by step, creating a sense of crisis to awaken the organization, selecting change Agents, producing short-term wins and celebrating grandly—Kotter-style transformation, frankly speaking, this highly performative, CEO-centered change model is extremely difficult to succeed in the AI era.

I recommend everyone watch Jensen Huang's "drunken truth-telling" at a Cisco annual meeting this February, full of fascinating and even "out-of-control" expressions. He gave a very vivid description of generative emergent transformation. For example, when many organizational members present ideas to him, he said, "Say yes, and then ask why"—let a thousand flowers blossom. Actually, I would say "flowers" should be in quotation marks; some are weeds, but that is precisely the point: you must allow things—whether eventually gorgeous flowers or weeds you cannot yet identify—to bloom and grow first.

Generative emergent transformation strongly encouRAGes internal, spontaneous, AI-native squads to explore new businesses, to Operationalize previously non-existent ventures using methods never used before. Organizations and leaders must tolerate a degree of chaos, maintain curiosity, even with a sense of playfulness—because you do not truly know what it will bring to the organization, nor can you clearly explain it to others, the board, or those pursuing ROI. No, it is not yet a noun; it cannot be clearly articulated.

But I believe one thing: the future forms of business and organization are completely unknown to us now; they need to be grown. Last year, CHEERS Publishing created an opportunity for me to dialogue with Professor Mintzberg based on his book "Structur in Fives." I shared my organizational innovation concept of "marginal figures and frontier domains." He responded with the story of flies and bees, arriving at the same destination via different paths—equally fascinating; you can find it and watch.

Speaking of marginal figures and frontier domains, consider the most important asset driving anthropic's rising Valuation: Claude Code, an AI programming assistant developed in 2024 and launched in 2025. Then look at openclaw ("Lobster"), which drove a massive leap in agent AI from late last year to early this year.

Behind both of these works, which arguably accelerated the AGI timeline, are two marginal figures who enriched their heterodox thinking in frontier domains. Through such living, unfolding cases, you will clearly see the manifestation of "marginal figures, frontier domains, emergent masterpieces." These two works, which can be called great, were not the result of planning—this is a distinctive feature of AI-powered transformation.

11 A Counterfactual Business History Thought Experiment: Kodak's Lesson
To think about AI-powered transformation, we can look to the future, but also revisit history. I invite everyone to conduct a counterfactual thought experiment in business history, a method I frequently use in my teaching.

Imagine: in 1975, Steve Sasson, a master's student newly arrived at a very large company, met his boss in the hallway and asked what he should work on. The boss told him to experiment with CCD, a new optoelectronic component, and see what he could make. Tinkering alone, he assembled a rather bulky box. This box took 24 seconds to "CLIck" and capture an image, then another 24 seconds to retain it, and another 24 seconds to display it on a monitor. In 1976, he presented it to company management; everyone said it was good, novel, while raising countless questions. In the end, the device was shelved.

Now, let us counterfactually hypothesize: for some inexplicable reason, after seeing this new invention, the company happened to acquire a platform in Japan, exactly allowing Sasson's team to develop within that platform, avoiding direct confrontation with the mainstream. What would have happened next? Of course, history did not unfold this way; I am merely asking you to conjecture counterfactually.

Perhaps—just perhaps—Sasson, this marginal figure and polymath, combined with a frontier environment outside the U.S., might have changed the fate of the company that collapsed dramatically in 2012. I have seen interviews; Sasson had a bit of the marginal figure energy, and digital technology was in its adolescence at the time. However, Kodak then exhibited very, very typical organizational middle age. That middle age performed well for over 20 years afterward—until it collided with technological adolescence.

12 Unknown Unknowns: Maintaining Curiosity and Inclusiveness
I mentioned earlier that I dislike the "second half" framing because we are nowhere near it. Regarding the future of business and organizational forms, we must be scientific and avoid herd mentality. To be truly honest, we must use the term: unknown unknowns.

Using the stages of internet development as an analogy, AI is still at the email stage. Agents emerging may be like the World Wide Web, but we are still at the stage of not even knowing about search engines. The future is full of anticipated unknown unknowns. We are not simply waiting for these to arrive but must co-create them together. Therefore, maintain curiosity and inclusiveness; do not rush to converge and control.

13 From "AI-Native" to "AI-Powered": Immigrants Can Also Become Evergreen
I would also like to gently discuss the term "AI-native." I used "AI-native team" earlier, and I suspect that when people hear it, they exclude themselves. Yes, the term "AI-native" sometimes makes it difficult for most people to accept; they feel they certainly do not qualify. At our age, we are either AI immigrants or AI refugees. So the term "AI-native" can easily pronounce a death sentence on middle age, at least shaking heads and saying, "Your future is bleak." This creates a strong sense of defeat and powerlessness, suppressing confidence in organizational change. I have even heard some entrepreneurs say, "Better to replace the blood than transform." Replacing blood means pinning all hope on the AI-native population. This is not practical, unfair to others, and lacks confidence.

This is also one of the purposes of my proposing the AI-powered transformation concept: to give everyone confidence that immigrants like us have the opportunity, through not being misled by names, breaking attachments and reconstructing, and generative emergence, to change our mindset, change our actions, change our organizations, and become youthful again. As long as you and I are willing to change, we will not fall behind; the middle age of years can possess an evergreen mindset.

14 The Entrepreneur's AI-Powered: Mission, Mental Strength, and Taste
The leadership of entrepreneurs in AI-powered transformation lies in contributing the most unique mission, mental strength, and taste to the organization. One of my favorite sayings goes: the farthest expedition is the journey inward. Transformation is difficult, full of turbulence. Five foundational types of "soulware" are critical:

Growth mindset, infinite game mindset, neoteny, wooden rooster state, and the wisdom of "slowing from the heart."

Those who possess these five types of soulware will develop great mental strength. I coined a term for them: "Heart-Men." Heart-Men, transcending Homo sapiens, will have no trouble finding their place in the future, no matter how they coordinate with AI to form super-assemblages. CHEERS published Demis Hassabis's Biography, and I had the honor of writing the preface for the Chinese edition, titled "Above AI, Being Human." I observe too much anxiety and a sense of loss among people today; this should not be the attitude of organizations and people toward AI. AI-powered transformation is human-centered transformation, strengthening human agency, fostering more universal neoteny and wooden rooster states, enabling freer growth and development, always initiating new infinite games, and living a life that slows to the heart. Organizations and people alike should love humanity more—letting AI, that wondrous pinyin "ai," truly mean what it sounds like.