Alzheimer’s disease (AD) clinical trials continue to face major hurdles in patient identification, resulting in delayed timelines, underpowered studies, and escalating costs. This perspective explores these challenges through the lens of a memory clinic, where hundreds of cases often translate into only a handful of enrollments. We highlight the potential of artificial intelligence (AI) to address this gap by powering chatbots for awareness and pre-screening, decision support tools for case identification, and algorithms for matching patients to trial-specific criteria, automating and streamlining the recruitment process. We also examine critical considerations in developing such AI-driven tools, including data standardization, privacy protections, and ethical safeguards. With thoughtful implementation, these innovations could accelerate more inclusive and efficient AD trials, ultimately bringing therapies to patients faster.