Black Women and AI

By Better Together Agency

The short answer: Black Americans, and Black women in particular, are among the most enthusiastic audiences for AI. But enthusiasm and adoption are not the same thing. A growing body of research shows that the gap between curiosity and consistent use is shaped less by access to information and more by a rational, evidence-backed deficit of trust. For organizations deploying AI, that distinction changes everything.

Much of the public conversation about AI adoption tends to flatten the picture, framing some communities as early adopters and others as reluctant holdouts. That framing, when applied to Black women, misses the point entirely. The data tells a more precise story: Black Americans are leaning into AI with real enthusiasm, paying for tools out of pocket, and seeking out education at higher rates than the general population. What is shaping their adoption is not disinterest. It is a set of entirely reasonable questions about whether AI is safe, fair, and designed with their lives in mind.

The numbers here are worth sitting with. According to a May 2025 report from JFF, based on a survey of Black learners and workers across the United States:

• 66% of Black respondents want to increase their familiarity with and use of AI, compared to 48% of all respondents surveyed.
• 52% of Black respondents believe AI does more good than harm at the community level, versus 42% overall.
• 54% of Black respondents believe AI benefits society, compared to 45% of all respondents.

The investment signal is equally striking. 18% of Black respondents personally pay for AI tools, nearly double the 10% rate across all respondents in the same survey. This is a community that is not waiting to be convinced. It is already spending real money on AI access.

Optimism and investment do not tell the full story. The same JFF report identifies the top barriers keeping Black learners and workers from deeper AI adoption:

• 31% cite the cost of AI tools as a deterrent.
• 26% point to a lack of access to AI tools.

These are structural barriers, not a lack of curiosity. Meanwhile, a February 2024 Federal Reserve Bank of New York survey found that only 31% of respondents overall had used a generative AI tool. Notably, those who had used generative AI at work were more likely to hold a pessimistic view of its long-term impact on economic inequality, suggesting that exposure to AI does not automatically produce confidence in its fairness.

Note: The JFF data reflects Black learners and workers broadly, not Black women exclusively. Where data specific to Black women is available, it is cited separately below.

A 2025 preliminary study by the TIER Lab at Hunter College, CUNY, published through the Brookings Institution, surveyed Black women in the United States on their perceptions of AI. The findings are clear:

• 94% of participants said they are impressed by AI’s capabilities.
• 73% said they want to use AI in their jobs.
• 53% said they are anxious about AI’s future use.
• 67% believe AI is used to spy on people.
• 69% say AI does not make them feel safe.
• Only 6% believe organizations currently use AI ethically.

This is not technophobia. It is pattern recognition, grounded in a documented history of algorithmic bias, surveillance overreach, and exclusion from the decision-making rooms where AI systems are designed and governed. The Brookings researchers noted that distrust appears broadly distributed across age groups in their sample, rather than concentrated among older respondents, suggesting this is a trust issue, not a generational one. This finding is preliminary and based on a small sample; larger-scale research is still needed to confirm the pattern at scale.

Visibility in AI is not a symbolic gesture. It is a structural one. The Black Women Leading in AI directory is one example of the infrastructure this moment demands, a community-built resource that surfaces Black women already leading across AI research, engineering, governance, education, and policy, filling a gap that mainstream institutions have largely left open.

Better Together Agency’s Founder and CEO, Catharine Montgomery, is listed in the directory under AI Policy, alongside researchers, engineers, and governance leaders doing this work every day. Her inclusion is a reminder that this conversation is not just about demographic trends. It is about who is recognized as a builder, a policymaker, and a legitimate authority in AI. When that recognition is visible, the next generation of Black women in AI knows the work is possible for them, too.

Interest without infrastructure is a missed opportunity. Three concrete actions for organizations and CSR leaders right now:

1. Design for trust before you design for adoption. Communicate clearly how your AI systems are governed, audited, and held accountable. Transparency is a prerequisite for communities with legitimate reasons to be cautious.

2. Invest in community-led AI literacy. Brookings recommends that trusted community organizations, nonprofits, libraries, and Black-led media lead AI outreach, supported by public and philanthropic funding. This is a trust-building problem, and it requires community-centered solutions.

3. Support the leaders already doing this work. The Black Women Leading in AI directory is a starting point. Nominate, resource and hire.

Are Black women interested in AI?

Yes, and the data is clear on this. JFF’s 2025 survey found that 66% of Black respondents want to increase their AI familiarity and use, compared to 48% of all respondents. Interest is high. The conditions for full adoption are what need to catch up.

Why is AI adoption lower among Black women if interest is high?

The primary barriers are structural: cost of tools, lack of access, and a well-founded trust deficit rooted in documented histories of algorithmic bias and surveillance. The Brookings/TIER Lab study found that only 6% of Black women surveyed believe organizations currently use AI ethically.

What does the research say about Black women’s trust in AI?

A 2025 preliminary study found that while 94% of Black women participants are impressed by AI’s capabilities, 69% say AI does not make them feel safe and 67% believe it is used to spy on people. Trust, not interest, is the central variable.

Why does representation in AI leadership matter?

Representation shapes who gets hired, who gets cited, who gets invited to governance conversations, and whose experiences get built into AI systems. Directories like Black Women Leading in AI are one way communities are building that visibility infrastructure themselves.

What should organizations do to close the trust gap?

Lead with transparency about how AI systems are governed. Partner with community-based organizations to deliver AI literacy. And actively support Black women’s leadership in AI as a structural commitment to equitable design.

• Unlocking the Promise of AI for Black Learners and Workers, JFF, May 2025
• Exposure to Generative AI and Expectations About Inequality, Federal Reserve Bank of New York Liberty Street Economics, October 2024
• Beyond the Blank Slate: Why Black Women’s Trust Is Critical for Equitable AI, Brookings Institution, 2025
• Black Women Leading In AI, A Curated Directory
• Better Together Agency

Better Together Agency works with organizations on responsible AI, bias, governance and communications. Read our Biases in Generative AI research.