AI in the Racial Wealth Gap: Deciding our Future (Full report)
Published June 2026
The racial wealth gap in the United States is one of the most persistent measures of economic inequality. Tech optimists sell the story that AI will solve persistent societal problems, a new great equalizer. This report makes clear through people’s lived experiences that without safeguards, AI will widen the racial wealth gap — not narrow it.
This qualitative report is based on interviews with people of color who believe they have been impacted by AI decision making systems in their pursuit of jobs, lending, and housing. It illustrates their experiences and attitudes about the technology and its effect on their economic mobility. This research does not examine the impact that AI has on small business and the racial wealth gap. The report also includes specific recommendations for stakeholders across sectors — from landlords to the companies making AI to policymakers.
“I would like [policymakers] to know that behind all this technology and all these policies, there’s actual people whose lives are being affected by it, and I would hope that they have somewhat of a backbone and stand up for the actual people, not just their pockets.”
AI in the Racial Wealth Gap: Takeaways (PDF)
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- AI is scaling existing patterns of racial discrimination. Systems trained on historically biased data reproduce those biases across millions of decisions simultaneously.
- The harm is not domain-specific. Housing, employment, and lending are connected by shared AI-powered infrastructure. Exclusion in one domain actively damages access in the others.
- Communities of color are disproportionately exposed to AI’s impacts on wealth. 91% of Black Americans see AI as a job threat; 24% of Black workers are in roles with 75%+ automation potential; Black mortgage applicants are 80% more likely to be denied.
- AI hardens the structural barriers faced by first-generation wealth-builders. When AI has been given the authority to make life-altering decisions, it cannot take context into account in the same way that a human decision-maker could.
- People cannot fight what they cannot see. The transparency deficit means most participants had no idea AI was involved in decisions that shaped their financial lives — and no path to appeal.
- Generational wealth feels unattainable to many. The compounding weight of algorithmic barriers makes generational wealth feel structurally out of reach, not just personally difficult.
- AI could help close the racial wealth gap, with safeguards. With guardrails and equitable development and deployment, AI could be a beneficial tool to support economic mobility and increase generational wealth.
*The report references Colorado’s 2024 “high-risk AI” framework, which was repealed in 2026 and replaced it with SB 26-189 (the Colorado Automated Decision-Making Technology Act), effective January 1, 2027. Colorado Senate Bill 26-189, Automated Decision-Making Technology, 75th General Assembly, Second Regular Session (2026). The new law drops the duty of reasonable care, risk-management and impact-assessment requirements, and safe harbors tied to nationally and internationally recognized AI risk-management frameworks, and instead focuses on documentation and transparency duties for “covered automated decision-making technologies” and on individual notice, explanation, correction, and human-review rights after certain consequential decisions. The main text describes the repealed 2024 law because that broader model remains salient as a template for more expansive AI anti-discrimination regimes, even though Colorado itself pivoted to a narrower transparency-oriented approach.