Why Domain-Specific AI Often Outperforms General Models

Large general-purpose models often underperform in specialized domains like finance, law, and medicine due to gaps in domain-specific terminology and reasoning. Domain-specific AI systems close this gap through fine-tuning, retrieval, structured labeling, and targeted evaluation, yielding smaller but more accurate models. This approach reflects human-centered AI principles that combine general capabilities with expert domain knowledge.