DIGITAL PATHOLOGY When systems do not communicate


effectively, workflows slow down and confidence in digital platforms starts to be eroded. Pathologists must navigate multiple interfaces, reconcile data manually and work around incomplete integrations. The industry’s increasing reliance on


partnerships has added another layer of complexity. While collaboration between vendors is often necessary to build broader digital ecosystems, pathologists noted that marketing narratives around partnerships do not always translate into real-world interoperability. Importantly, the challenge extends


well beyond digital pathology software. Laboratories are increasingly expected to integrate information across laboratory information systems, genomics platforms, hospital electronic medical records and emerging AI tools. For vendors, this reinforces a growing


shift toward platform strategies and wider ecosystem partnerships rather than standalone products. The challenge for the market, however, lies in the economics of integration. Delivering the seamless workflows pathologists are asking for often requires complex bidirectional interfaces between laboratory systems, electronic health records and diagnostic software. In practice, these integrations can be costly to build and maintain, particularly within fragmented healthcare IT environments. For vendors serving small to mid-sized markets, deciding where to invest in integrations and which systems to prioritise is rarely straightforward. This dynamic helps explain why some


healthcare IT markets have gradually consolidated around the electronic health record (EHR), where purchasing from a single vendor can reduce integration complexity. The trade-off, however, is often reduced flexibility and fewer opportunities to optimise workflows for the specific needs of pathology laboratories.


In many laboratories, procurement decisions are not driven purely by technological preference but by operational feasibility. Even when beter tools exist, organisations may remain tied to incumbent vendors.


4. AI adoption is accelerating but expectations are pragmatic


One positive that emerged was that the rhetoric surrounding artificial intelligence (AI) in pathology has matured considerably. Rather than debating whether AI will replace pathologists, most interviewees framed its value in more practical terms: as a tool that supports clinical decision-making rather than replacing it. In practice, this distinction is already shaping where AI is proving most useful. Algorithms perform well in repetitive quantitative tasks such as mitosis counting and immunohistochemistry quantification. However, they can struggle with complex contextual interpretation, particularly in cases involving artefacts such as crushed tissue or poor staining that a trained pathologist immediately recognises. This reflects a broader shift in the AI


digital pathology market. Early vendor messaging often focused on autonomous diagnosis, but adoption is increasingly


being driven by workflow augmentation and efficiency gains. Importantly, the interviewees were


not fearful of AI. On the contrary, there was clear enthusiasm to explore how these tools could improve efficiency and support clinical workflows. Interest was strongest around practical applications such as triage, case prioritisation, preliminary analyses and workflow automation.


This shift will likely be welcomed


by the market, which is itself moving towards applications that augment clinical workflows rather than atempt to replace them. Growing interest over the past year in areas such as automated report generation, predictive analytics and prognostic biomarker detection reflects this change in focus. Rather than pursuing autonomous diagnosis, vendors are increasingly positioning AI as a practical tool that improves efficiency, supports decision-making and reduces routine workload within the pathology workflow.


May 2026 WWW.PATHOLOGYINPRACTICE.COM 19


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