Emerging technologies employing artificial intelligence and integrated data analyses are addressing longstanding issues of underrepresentation in clinical trials. These tools aggregate multi-source patient data, including electronic health records and population health databases, to improve recruitment strategies and patient matching. By overcoming obstacles such as mistrust, resource limitations, and geographic barriers, AI-driven methods offer promise to expand inclusivity, increase trial diversity, and thereby improve the generalizability of medical research findings.