Cultural intelligence is essential to building ethical, inclusive, and high-performing AI. Insights from a CES 2026 panel on bias, trust, and AI design.
At CES 2026 in Las Vegas, the Female Quotient Lounge returned to kick off the year with a series of conversations about the future of technology. One of the highlights was a panel on culturally aware AI and privacy-first approaches, featuring Shi Shi, Director of Data Science at Equativ, Jackie Stevenson, Global Chief Strategy and Innovation Officer at M+C Saatchi Group, Nell Daly, founder of Revenge Capital, and Caitlin Keating, journalist and co-founder of Wise Fool Films. Together, they explored why cultural intelligence must be embedded as a core system input to build AI that is ethical, inclusive, and high-performing at scale.
Cultural intelligence should be the foundation for any marketer or AI leader. Shi opened the discussion by sharing her perspective: "I have a lot of first-hand data points that taught me that the same word, same gesture, same color, can mean completely different things in different cultural contexts."
The same behavior or data point can carry radically different meaning depending on context, and leaders must account for these differences. Jackie echoed this, emphasizing that cultural intelligence is operational, not just contextual: "For us, we've focused our whole company on cultural power and helping brands understand their current cultural power and what, by building on their cultural power, they can achieve in terms of their economic growth," she said.
Embedding cultural intelligence from the start creates authenticity in every interaction. Too often, leadership understands culture emotionally but fails to encode it structurally. Without cultural intelligence embedded in systems, bias becomes inevitable.
Key Takeaway: With AI scaling faster and globally, cultural intelligence is foundational. Ignoring it carries real costs for brands, platforms, and communities alike.
For Nell, cultural intelligence is more than a buzzword. Her lived experiences -from therapist to founder to funder - guide how she evaluates investment opportunities and assesses risk.
Revenge Capital was born out of encounters with cultural bias and discrimination. Nell highlights a stark reality: in the UK, only 1.8 percent of funding goes to women, and in the US, just 3 percent. For her, cultural intelligence is both risk mitigation and value creation, not just a DEI signal. She looks for founders who embrace it early rather than retrofitting it later, as early integration improves market understanding, reduces blind spots, and builds long-term trust.
"If teams aren't built from the ground up with diversity baked in, it's not just about social alignment with who I invest in. It's been proven to be much better business to invest in diverse teams," Nell added.
Key Takeaway: Founders who embed cultural intelligence into their strategies from the start move faster, break less, and create sustainable value.
Bias in AI has tangible consequences. Shi shared a striking example: US-trained ad models misread the stability of European markets as underperformance. What seemed like a small error in interpretation actually reflected a clash between speed, volatility, and long-term market dynamics.
Fixing bias begins with building cultural differences into models as a core input. This ensures systems understand context, can be tailored to markets, and deliver better outcomes. Ignoring culture has ripple effects: local publishers lose opportunities, local brands miss audiences, and platforms lose revenue.
Nell emphasized the importance of diversity, saying, "On a micro level inside your company, it's so important to have diverse teams who are picking up on these nuances. If you don't have diversity around the table - gender, cultural, and age - you're not going to understand what you're missing in the data."
Jackie added that companies may see AI performance improving on the surface, yet that may be quietly losing out on entire markets as a result.
Key Takeaway: Cultural intelligence matters internally and externally. Harm can hide in what looks like optimization. Embedding culture in AI and decision-making is essential to avoid quiet losses and create meaningful, long-term impact.
Trust is central to AI, yet it erodes when systems mistake raw signal volume for human intent. Data alone can misrepresent people, leaving brands blind to the audiences they aim to reach.
Jackie explained how cultural intelligence can bridge that gap: "Everyone is talking about trust and authenticity, and yet the data layers we are using when we connect one-to-one - the most important place a brand shows up for a consumer - are often very needs based. At M+C Saatchi, we want to add a layer of cultural data that can be used not just at the top in brand architecture, but that can be used right down when you're speaking one-to-one to a consumer and in performance marketing."
Shi emphasized the need for transparency and continuous evaluation, urging leaders to "use unfiltered data to represent every pocket of traffic, include cultural intelligence in AI solutions, and monitor outcomes to ensure things stay on track." She added that it's equally important to communicate both what is learned and any concerns that arise along the way.
Key Takeaway: Embedding cultural insights ensures AI scales efficiently while respecting and reflecting the human intent behind the data.
The question isn't whether AI can optimize or scale, but how culture shapes purpose. Shi explained, "Physics, mathematics, and engineering are tools that improve how we live, and AI is doing all of that these days. But, culture, humanities, art, and love are what we are living for."
AI can handle vast amounts of data and complexity, but humans create meaning and value. Cultural intelligence is not an add-on: it is the foundation guiding how AI interprets and acts on information. Cultural data serves as a guardrail shaping AI decisions rather than replacing human judgement.
In practice, AI systems should scale while humans remain responsible for valuing, interpreting, and contextualizing results. Leadership in the next era of AI belongs to those who embed humanity and cultural intelligence at the core of their systems. Trust, ethics, and long-term impact don't emerge from dashboards; they come from a deep understanding of culture.
AI does the scaling; humans do the valuing. Together, they create systems that are effective, inclusive, and ethically grounded.
Summary
As Director of Marketing and Communications at Equativ, Amy leads the company’s owned content, social media, and public relations strategies. Collaborating with stakeholders across the organization, she writes on topics ranging from Equativ’s product innovations to broader industry trends.
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