Artificial Intelligence in Pathology. Explanations, Limitations, and Directions

Artificial Intelligence (AI) is rapidly transforming the landscape of pathology, promising enhanced diagnostic accuracy, efficiency, and reproducibility. This article provides a pathologist centric overview of AI, offering clear definitions, practical examples, and critical insights into its capabilities and limitations. It addresses the current state of AI integration into digital pathology workflows, including image analysis, pattern recognition, and decision support. Importantly, the discussion highlights key challenges such as algorithmic bias, data dependency, and interpretability-factors essential for safe and effective clinical adoption. The paper also reflects on common misconceptions and the human-AI partnership, urging pathologists to engage with these technologies thoughtfully. Ultimately, it offers guidance on how to critically assess, adopt, and contribute to the responsible use of AI in diagnostic practice.