Remembering the Future: What Ancestral Intelligence Teaches Us About Building AI That Works for Everyone

There is a question Rochelle Grayson's father used to raise at the dinner table, somewhere between the philosophy of Hegel and the rhythms of a bicultural household in Germany.

What does it mean to be human?

Rochelle's father is a professor of 19th century German philosophy, specialising in human existentialism. She grew up thinking these were the questions of another era. Then AI arrived, and she realised they were the questions of this one.

In December, Rochelle joined She Shapes AI Founder and CEO Dr Julia Stamm for a fireside chat unlike any we had hosted before. The conversation, titled Remembering the Future: AI Stewardship and Ancestral Intelligence™, did not start with algorithms or regulation. It started with a Puerto Rican great-grandmother, a women's lending circle, and a piano.

Through Mosaic Accelerator and Circles of AI, Rochelle works at the intersection of ancestral intelligence and emerging technology, helping intersectional women founders and non-technical leaders build ventures that are sustainable, community-rooted, and values-led.

Where Rochelle's story begins

Rochelle grew up between worlds. Her father is African American, her mother Puerto Rican. She was born in New York and spent her formative years in Germany. From an early age she understood that identity is not a single thing, that categories rarely capture people, and that wisdom travels across generations in ways that formal institutions rarely document.

She knew her great-grandmother. She knew all of her grandparents. In a world that increasingly treats knowledge as something produced by institutions and stored in databases, Rochelle carries a different understanding that some of the most important knowledge lives in communities, in practices, in the stories we inherit and pass on.

That understanding is at the heart of what she calls ancestral intelligence.

What ancestral intelligence actually means

Ancestral intelligence is not nostalgia. It is not a rejection of technology. It is a recognition that human communities have been solving complex problems around resource allocation, governance, trust, and equity for centuries, and that those solutions deserve a place in how we build AI.

Rochelle's example is concrete and personal. Her great-grandmother was part of a women's lending circle in Puerto Rico. Each woman contributed a small amount each week from her household allowance. When the collective pot was large enough, it was given to whichever member had the greatest need, as decided by the group. It was collaborative. It was values-led. It required trust.

Her great-grandmother used her allocation to buy a piano for Rochelle's mother, who had been playing imaginary keys on a windowsill. That piano launched a musical career. Decades later, Rochelle is still benefiting from a decision made by a group of women with very little money and a great deal of wisdom about what mattered.

The question she brings to AI is simple: why are those models not in the room when we design these systems?

Who builds AI determines what it reflects

When Rochelle began building her accelerator for marginalised and intersectional women founders, she turned to AI for support. What she found was that the tools reflected the assumptions of the world that built them, optimised for the unicorn model, the fast-growth trajectory, the kind of startup built for scale above all else.

The women she works with are not building unicorns. They are building businesses that serve communities they know intimately, that prioritise sustainability over speed, and that draw on collaborative and collective models of growth. The AI had no language for this. It kept steering them back toward frameworks that did not fit.

Rochelle's response was not to abandon the tools. It was to build her own custom models trained on different assumptions, different values, different definitions of success. The communities and cultures left out of the room are not edge cases. They are the missing centre.

Stewardship as a practice

The second major theme of the conversation is stewardship and Rochelle's definition is worth sitting with.

Stewardship is not passive. It is not simply using AI responsibly in your own organisation. It is actively shaping the direction of the technology itself through the choices you make about which tools you use, which companies you support, and which values you are willing to advocate for publicly.

Her argument is that we are early enough in the development of AI for those choices to matter. The dominant players feel entrenched, but no platform reaches scale overnight. The communities, organisations, and leaders who align around a different vision, of AI that is permission-driven, equitable, and genuinely accountable, are already building that alternative. The question is whether enough people will recognise their agency and use it.

Doing good and building sustainably are not in conflict

A part of the conversation that really resonated with us is when Rochelle articulated something that She Shapes AI also holds as a core belief: that sustainability and social impact are not in opposition.

Nonprofits and charities do vital work. But a model that depends on the goodwill of donors is a fragile model. Stewardship, the kind that lasts, that passes something on to the next generation, requires sustainable foundations. It requires businesses that can remain in the work without fearing for their survival.

This is not a compromise of values. It is what makes values operational over the long term.

You are not a bystander in the AI story

Rochelle closed the conversation with two invitations: one for each theme of the discussion.

On ancestral intelligence: think about the practices and knowledge systems from your own cultural and ancestral heritage that you would like to see continue. What does it look like to carry those forward into the AI age?

On stewardship: what actions, however small, could you take to shepherd AI in a direction that reflects your values? You have always had the power to shape where it goes.

Both questions are worth returning to. Both have implications for how we lead.

Leadership in the age of AI requires more than technical fluency

The conversation with Rochelle is a reminder that the most important questions in AI are not technical ones. They are questions about values, governance, equity, and the kind of future we are willing to advocate for. They are the questions that capable, thoughtful leaders are already equipped to engage with if they have the frameworks to do so with confidence and rigour.

That is what the Executive AI Intensive is designed to provide. A five-day live virtual programme for senior leaders, board members, C-suite executives, directors of strategy, policy, innovation, and operations. No prior technical knowledge required.

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