Artificial intelligence is rapidly transforming genomics, making powerful analytical tools accessible to more people than ever before. But while AI can generate convincing interpretations, it does not replace the deep expertise required to evaluate genetic evidence, recognize uncertainty, and make clinically defensible decisions.
In this article, Wayne Delport explores why genetic interpretation is fundamentally different from many other AI applications. Drawing on recent research, ACMG/AMP variant interpretation guidelines, and real-world clinical examples, he argues that AI risks democratizing the appearance of expertise faster than the expertise itself. As genomic sequencing becomes increasingly routine, accurate interpretation—not data generation—has become the true bottleneck.
The article examines how AI can amplify confidence without increasing competence, why errors become more dangerous when they scale, and why expert oversight remains essential for safe and responsible clinical genomics. Rather than arguing against AI, it makes the case for AI-assisted workflows that enhance, rather than replace, the judgment of experienced genomic scientists and clinicians.
Wayne Delport is a bioinformatics and genomics technology leader with more than two decades of experience building scalable computational biology platforms and advancing precision medicine. As Co-Founder and CTO of Simplify Genomics, he leads the development of AI-driven genomic interpretation and search technologies designed to accelerate clinical decision-making and make whole genome data actionable in healthcare. Wayne has authored widely cited research in evolutionary biology, genomics, and computational methods, with thousands of academic citations across his work. His expertise spans cloud-based bioinformatics systems, genomic data infrastructure, and translating complex biological data into practical clinical applications.