Labcorp said on February 23, 2026, that it is expanding its long-running partnership with PathAI to deploy the AI-powered digital pathology platform AISight Dx across its national network of anatomic pathology laboratories and hospital collaborations, a move that pushes AI-assisted slide review out of pilot programs and into routine use at one of the largest diagnostic testing companies in the United States.
A relationship seven years in the making
Labcorp, based in Burlington, North Carolina, first invested in PathAI in 2019, and the companies have since worked together on AI-driven clinical trial support and the validation of pathology algorithms. The newly announced expansion builds directly on that foundation rather than starting from scratch, with Labcorp framing the rollout as the next step in a multi-year bet on digital pathology infrastructure. Dr. Marcia Eisenberg, Labcorp’s chief scientific officer, said the company wants a modern, AI-powered infrastructure for its pathology operations, while PathAI co-founder and chief executive Dr. Andy Beck described the deal as part of the company’s broader push to modernize pathology through software.
What AISight Dx actually does
AISight Dx is a cloud-based platform that converts glass microscope slides into digital images pathologists can view, annotate and share remotely, then layers AI tools on top to assist with key steps in the diagnostic workflow, such as flagging regions of interest or supporting quantitative image analysis. The platform is FDA-cleared in the United States for primary diagnosis and carries CE-IVD marking covering the European Economic Area, the United Kingdom and Switzerland, meaning it has cleared regulatory bars in multiple jurisdictions for use in rendering an actual diagnosis rather than only as a research or decision-support aid. Labcorp says the technology will also feed into its precision medicine testing products, connecting routine anatomic pathology more tightly with genomic and companion-diagnostic work.
Why digital pathology is having a moment
Pathology has lagged radiology in digitization for years because whole-slide imaging requires scanning physical glass slides at resolutions that generate enormous file sizes, historically a costly and slow process. That has started to change as cloud storage and AI image analysis have matured enough to make digital workflows cheaper than maintaining slide libraries and shipping glass between labs. Industry analysts tracking the sector have pointed to cloud deployment becoming the practical default for multi-site pathology operations that need consistent governance and remote access, a shift Labcorp’s nationwide rollout reflects at a scale few competitors can match given its network of labs and hospital partnerships.
The promise: faster, more consistent reads
Labcorp’s stated case for the rollout rests on turnaround time, efficiency and consistency. Digital slides let pathologists collaborate on a difficult case without physically shipping glass across the country, and AI tools can pre-screen slides for features worth a closer look, potentially shortening the gap between a biopsy and a cancer diagnosis. For hospital systems that rely on Labcorp for anatomic pathology services, the promise is a more uniform standard of review regardless of which lab physically processes a given sample.
What remains unproven at this scale
What Labcorp has not disclosed publicly is a timeline for how many of its labs will be converted, how many pathologists will be using AI-assisted review by a given date, or what metrics it will use to judge whether the rollout actually shortens turnaround times or improves diagnostic concordance between pathologists. The company’s announcement describes scope and intent rather than measured outcomes, which is typical of early-stage corporate AI rollouts in medicine but leaves outside observers unable to independently verify the platform’s real-world impact until Labcorp or PathAI publish performance data from the deployment itself. Pathology, unlike radiology triage software, often carries higher diagnostic stakes per read, since a missed or misclassified cancer on a tissue sample can delay treatment for months, which is part of why regulators required primary-diagnosis clearance rather than a lower-stakes 510(k) pathway for decision support alone.
What’s next
Labcorp’s move puts competitive pressure on other large reference labs and hospital pathology departments that have been slower to adopt digital workflows, and it gives PathAI, which has built its business on AI image analysis for both clinical and pharmaceutical research use, a flagship customer at national scale. Whether the expansion delivers on its efficiency promises will likely become clearer over the next year as Labcorp integrates AISight Dx across more sites and as independent researchers get access to real-world performance data rather than vendor and customer announcements alone.
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