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Pathology’s Goldmine: Use it or Lose it

by Rajendra Singh MD, Co-Founder, PathPresenter
Director of Dermatopathology and Digital Pathology,
Summit Health

Every day, pathology departments across the world generate petabytes of data — from whole-slide images and molecular assays to lab reports and genomic sequences. It’s one of the richest, largest and most valuable data ecosystems in all of healthcare.

Yet, much of this data sits idle — hidden in fragmented systems and locked away in silos with little to no interoperability within the department. When it comes to the institution, there’s often minimal connection between the clinical information housed in the electronic medical record (EMR) and the diagnostic or molecular workup data produced in pathology.

These systems speak different digital languages, rarely sharing a unified context. As a result, critical insights — like how a molecular alteration influenced treatment or how a diagnosis correlated with outcomes — are lost in translation. The potential to learn from every case, to link diagnosis to prognosis, remains largely unrealized.

To make matters worse, data access still depends on cumbersome manual processes. Teams spend countless hours creating Excel sheets or CSV files to match metadata with source images and reports, often relying on “honest brokers” to manage the datasets. This inefficient workflow has become one of the biggest barriers to progress, keeping pathology’s immense data resources underutilized — accessible only for limited, project-specific analyses instead of the integrated insights that could truly transform patient care.

Meanwhile, artificial intelligence is advancing rapidly — with or without pathology. Across healthcare, major institutions and technology companies are building massive foundation models trained on multimodal data that combine text, imaging, and molecular information. These systems are already detecting subtle patterns, predicting mutations, and generating diagnostic reports.

AI isn’t waiting for pathology to catch up. If the specialty doesn’t take ownership of its data, it risks becoming a passive supplier rather than an active leader in healthcare innovation. When someone else manages and monetizes your data, you don’t just lose control — you lose influence, identity, and relevance.

Data, after all, is the new oil — but raw oil is worthless without refining, governance, and strategic deployment. History makes that clear: nations that built infrastructure and controlled their energy ecosystems became global powers, while those that didn’t remained dependent on others. Pathology now stands at the same crossroads.

Departments that invest in standardized, interoperable data systems, digital workflows that generate structured insights, and governance frameworks that ensure privacy, quality, and fairness will become the backbone of precision medicine. Those that fail to do so will end up as data providers for someone else’s AI. The goal isn’t simply to adopt artificial intelligence — it’s to own the ecosystem that makes AI possible.

The next decade will determine whether pathology leads this transformation or is led by it. The departments that thrive will be those that recognize that data isn’t an IT problem — it’s an institutional asset. That digital pathology isn’t a cost center — it’s the foundation of strategic control. And that governance isn’t bureaucracy — it’s leverage.

The goldmine is already there. But unless pathology departments build the pipelines, governance, and strategy to manage it, someone else will.

Pathology’s future won’t hinge on who has the most slides, but on who can manage them best. The time to act is now.

About the Author

Dr. Rajendra Singh is Director of Dermatopathology at Summit Health and co-founder of PathPresenter. He serves as a member of the Digital and Computational Pathology Committee of the CAP, Editorial Board of the WHO for Classification of tumors, 5th Edition and the Board of Digital Pathology Association.