John Henry for the AI Era: Raging with the Machine

Author’s Note: I’m excited to share this piece, written with my close friend and constant collaborator, Jayson Council. This came out of conversations we’ve been having for the past year, trying to make sense of what’s actually happening as this technology shows up in people’s lives and work. Some of the ideas have been rehearsed here in different forms but the call to action is a distinct offering from the evolved through two of us.

One thing that’s stayed with me from a talk Jayson and I recently led at a tech company is the emotional reality underneath all of this. There’s excitement, sure. But there’s also real anxiety. I’ve heard some version of the same question more than once: am I being asked to train my replacement? That’s a tough place to be. It creates a mix of angst, resentment, and, at the same time, a kind of awe at what these tools can do.

I don’t think we can ignore that and expect people to just “lean in.” Engagement comes from trust. And the companies that are going to navigate this well are the ones that are clear about their values and principles in how they use AI. That means what they’re willing and not willing to do with it., and where human beings fit into that. That’s where trust gets built. And we think, over time, that’s what’s going to separate who actually wins here.

Part of why we wrote this is because this moment is being defined right now. And too often, a small group of people get to shape both the technology and the conversation about it. We’re not waiting on that. We’re stepping into it as it’s forming, asking questions, naming what we’re seeing, and trying to widen the frame. Because it’s our future too.

By Jayson Council and Dax-Devlon Ross

American folklore tells the poignant story of John Henry, the steel driver who raced a steam-powered drill to prove human superiority. Notably, John Henry was a Black man, embodying resilience and defiance in an era marked by racial and economic oppression. His victory was short-lived, as he ultimately succumbed to the very machine he sought to outpace. This narrative serves as a powerful reminder that the real tragedy lies not in the existence of machines but in humanity’s reluctance to collaborate with them.

Today, we are all John Henry. The steam drill of Artificial Intelligence is not just another wave of automation; it is the first technology that meaningfully questions the value of human contribution itself. Previous machines replaced muscle, while AI is beginning to replicate cognition. When a system can draft memos, generate strategy decks, analyze legal briefs, design marketing campaigns, and write code in seconds, the question is no longer, “Which jobs will disappear?” The question is: “What is uniquely human now?”

That question does not belong to engineers alone; it belongs to leaders. It requires us to revisit a framework many organizations have grown weary of: diversity, equity, and inclusion. Not as compliance, not as moral theater, but as survival infrastructure.

As AI reshapes industries and redefines the landscape of work, the stakes have never been higher. The disruption is not merely a question of job loss; it is a fundamental challenge to the value of human intellect across all sectors.

Owners of capital—the industrialists and entrepreneurs—may feel insulated from immediate threats, yet the digital divide exacerbates vulnerabilities for those without access to AI’s advantages. This moment demands a united response to reframe diversity, equity, and inclusion (DEI) in the context of AI, moving from a framework that has faltered into one that actively addresses systemic inequities.

The future scenarios we face hinge on our ability to collaborate with AI rather than resist it, ensuring that the benefits of innovation are shared equitably. In this new paradigm, the imperative is clear: we must consciously design AI systems that reflect our highest values and aspirations, or risk embedding historical inequities in the very fabric of our technological progress.

Raging Against “The Machine”

Today, we face a pivotal choice reminiscent of John Henry’s tale. We can continue to rage against AI, striving to demonstrate our cognitive superiority in a competition we are structurally set up to lose. Alternatively, we can choose to rage with it—embracing AI as a collaborative partner that amplifies our capabilities rather than diminishes them. The rise of AI now offers unprecedented opportunities, allowing individuals from diverse backgrounds, especially those historically marginalized, to engage as high-level programmers and innovators. This shift transforms the narrative from one of victimhood to empowerment.

The goal is not merely to outthink the machine but to ensure that it reflects our values and aspirations. By intentionally designing AI systems that embody equity and inclusivity, we can create a future where technology serves as a tool for collective advancement rather than a force of division. The time has come to recognize that in the age of intelligent machines, our greatest strength lies in collaboration, not competition.

Why Traditional DEI Stalled

Over the last decade, DEI entered boardrooms and executive suites at scale. Some of that work was meaningful; much of it was not. In many institutions, DEI became performative—reduced to metrics, training modules, and public commitments untethered from structural change. In others, it triggered defensive resistance. Framed as a redistribution of opportunity between groups, it was interpreted as zero-sum. Political polarization did the rest. Whether one believes DEI “failed” or simply stalled, one thing is clear: it did not achieve the systemic transformation its advocates envisioned. But AI changes the battlefield.

AI Is the First Universal Disruptor

Unlike previous social debates framed around race, gender, or representation, AI destabilizes something more fundamental: human leverage. For the first time, high-performing professionals across industries—lawyers, consultants, writers, analysts, marketers, engineers—are confronting the same reality: a machine can now assist, accelerate, or partially replicate the very skills that once distinguished them.

This is not a niche concern. It is not partisan. It is not demographic. It is universal. The white executive in rural West Virginia and the Black founder in Atlanta now share a common vulnerability: technology that does not inherently have their best interests at heart. That shared vulnerability opens a different kind of conversation.

Equity, Reframed for the AI Era

If DEI once centered on representation and access to opportunity, DEAI—Diversity, Equity, and Inclusion in AI—must center on how human value is preserved and amplified in an age of intelligent machines. Equity, in particular, takes on new meaning.

1. Access Equity: The Assistant Gap Closes

For generations, intellectual leverage was unevenly distributed. CEOs had research teams. Politicians had speechwriters. Best-selling authors had editorial staffs. High-net-worth individuals had advisors and analysts. Everyone else had to work alone. AI disrupts that hierarchy. Today, a first-generation college student with a laptop has access to analytical assistance that rivals what only elites once possessed. That is not cheating; that is access. AI levels what we might call the “assistant gap.” It democratizes cognitive augmentation. This is equity in action—not as redistribution of resources between groups, but as expanded capacity across humanity. But access alone is not enough.

2. Earned Equity: Judgment Still Matters

The individuals best positioned to use AI responsibly are not those who rely on it blindly. They are those who bring depth, rigor, cultural literacy, and ethical grounding to the tool. A seasoned strategist can interrogate AI output. A trained writer can refine it. An experienced leader can contextualize it. A culturally aware professional can identify its blind spots. AI amplifies what is already there. This is where the unfinished work of DEI becomes essential: cultural competency, bias recognition, ethical reasoning, and interdisciplinary perspective. These are not HR soft skills; they are interpretive frameworks. Without them, AI becomes a mirror of its training data—replicating historical inequities at scale. With them, AI becomes a multiplier of human insight.

What DEAI Actually Demands

DEAI is not a rebrand; it is a reorientation. It asks leaders to move upstream—beyond retroactive audits of biased systems—and toward intentional design at inception. It demands that:

- Training data be examined for structural bias.

- Design teams reflect diverse lived experiences.

- Governance structures include ethical oversight.

- Accountability mechanisms tie AI deployment to human outcomes.

- Leaders articulate a value proposition for humanity alongside technological adoption.

This is not about protecting feelings; it is about protecting legitimacy. When AI systems misidentify darker-skinned women at dramatically higher rates than lighter-skinned men—as research by scholars like Joy Buolamwini and Timnit Gebru has shown—the issue is not optics. It is accuracy, credibility, and harm. When credit algorithms replicate historical lending bias, the issue is not public relations. It is access to capital and generational wealth. Without intentional integration of equity and inclusion principles, AI does not become neutral; it becomes efficient at reproducing the past.

The Leadership Imperative

The leaders who thrive in this era will not be those who resist AI, nor those who adopt it blindly. They will be those who understand that AI forces a new question: What is our human value proposition? If AI can draft, analyze, and predict, then human leadership must prioritize:

- Judgment over speed

- Wisdom over volume

- Context over pattern recognition

- Ethics over efficiency

DEI, stripped of performance and politics, offers a set of tools for exactly this work. It trains us to consider who is missing. It conditions us to question default settings. It pushes us to widen apertures and interrogate assumptions. In an AI-saturated world, those are not ideological luxuries; they are competitive advantages.

The Reveal

This essay was written in collaboration with artificial intelligence. Not outsourced. Not delegated. Collaborated. The ideas are ours—shaped by decades of lived experience, leadership work, and engagement across industries. The tool accelerated the articulation. That is the point. We are not laying down our hammers to prove we can outwork the machine. We are learning how to lay more track—together.

Raging With the Machine

DEI, as previously practiced, may have exhausted its cultural capital. But its core insight—that systems reflect the values and blind spots of their designers—is more relevant than ever. AI is not simply a technological upgrade; it is a civilizational inflection point. We can allow it to encode the same inequities we failed to dismantle, or we can embed our highest human principles into its architecture.

Raging with the machine means refusing both nostalgia and naïveté. It means recognizing that technology is now our newest cultural member—powerful, scalable, and morally neutral until directed. And it means understanding that equity in the age of AI is not about who gets a seat at the table; it is about whether humanity remains at the head of it.