Situations Where Simple Models Outperform AI Simple statistics are preferred when data is scarce, relationships are linear, transparency matters, decisions face regulation, stakeholders need explanations, costs and compute are limited, models must be robust and fast, risks of overfitting are high, and incremental accuracy from complex AI does not justify added complexity in practical settings today. Read the full Article here: https://www.dzinsights.com/blog/when-are-simple-statistics-widely-preferred-over-complex-ai-models