As AI moves deeper into healthcare, pathology is an area showing where the real opportunity lies by not replacing clinical expertise but building a better infrastructure around it.

AI is rapidly becoming one of the most discussed disruptive forces in Healthtech. Across diagnostics, drug discovery, clinical development, and patient care, AI is being positioned as a catalyst for speed, efficiency, and new insight.

But in medicine, the most important question is not whether AI can generate an impressive demonstration; it is whether AI can be integrated into real clinical workflows in ways physicians trust, institutions can govern, and patients can ultimately benefit from.

Pathology sits directly at the center of this discussion.

Pathology at a Turning Point

For decades, pathologists have played a critical role in diagnosing disease, classifying tissue, and helping guide treatment decisions. Yet much of the field has historically relied on microscope-based workflows, physical glass slides, and fragmented systems for sharing, viewing, and interpreting images.

As pathology moves from glass slides to digital workflows, the field is entering a new era. The scale of the opportunity is enormous. According to Patrick Myles, CEO of PathPresenter, roughly one billion glass biopsy slides are produced around the world each year, yet only an estimated 10–15% are currently digitized. That means the future of AI in pathology depends not only on better algorithms, but on the broader digitization of the underlying clinical workflow. AI has the potential to help pathologists work more efficiently, access more information, and contribute even more directly to precision medicine. But realizing that future requires more than algorithms. It requires infrastructure.

Dr. Rajendra Singh, Co-Founder of PathPresenter and a practicing dermatopathologist, put the challenge plainly during a recent AVANT BIO-hosted fireside discussion. Pathologists are excited about AI, he explained, but many still cannot bring it into their actual departments or daily workflows.

“People are very excited about AI,” Dr. Singh said, “but when they come back to the institution or the lab, they are not able to actually bring that AI into their own work.”

That gap between AI promise and clinical adoption is where the next wave of innovation in pathology is likely to be built.

From AI Hype to Clinical Reality

The promise of AI in pathology is significant. Algorithms are being developed to help identify patterns in tissue, support diagnostic workflows, predict prognosis, and potentially inform treatment decisions. But many promising tools still lack a practical path into the hands of pathologists.

Patrick Myles, CEO of PathPresenter, describes this as one of the core challenges the company is working to solve: getting AI into everyday pathology workflows.

 “The biggest challenge we’re addressing is how to get these amazing AI algorithms into the hands of pathologists so they can use them in everyday workflows,” Myles said.” PathPresenter has built an infrastructure platform and image management system that creates a simpler way for AI to get in front of pathologists”

The platform helps connect digital slides, scanners, lab information systems, AI tools, and clinical workflows so pathology departments can move from isolated technology pilots to more integrated digital practice.

AI adoption is not just a software challenge. It is an infrastructure challenge. For AI to move from conference demonstrations into clinical departments, images must be accessible, data must be usable, algorithms must fit into existing workflows, and physicians must be able to trust the tools in front of them. Institutions also need governance, compliance, and integration across the enterprise.

Myles describes a tipping point is needed in digital pathology to get from the current ~15% adoption to a critical mass. Digital pathology adoption is unlikely to accelerate because of any single force alone. AI, workforce shortages, regulatory progress, institutional ROI, and the growing need for remote collaboration all matter. But these forces only create real momentum when the infrastructure is in place to make digital pathology usable, trusted, and scalable across everyday clinical practice.

That is the difference between AI as a point solution and AI as part of a clinical operating environment.

The Pathologist Remains Central

Much of the public conversation around AI has focused on replacement: will AI replace doctors, clinicians, or specialists?

In pathology, Dr. Singh hears that question often. His answer is clear: AI will not replace the pathologist. It will expand what the pathologist can do.

 “The biggest hype is that AI is going to replace the clinician or replace the pathologist,” Dr. Singh said. “That is not going to happen anytime soon.”

For Dr. Singh, the reason is not only technical. It is human. AI can recognize patterns based on the data it has been trained on. But clinical medicine is not just pattern recognition. It requires judgment, context, responsibility, and an understanding that every biopsy represents a real person.

“When I’m looking at a slide for a patient, my first concern is that this biopsy is coming from someone’s wife, child, or daughter,” Dr. Singh explained.

That patient-centered mindset is not incidental to pathology. It is core to the practice of medicine.

AI may help pathologists perform their work more efficiently. It may reduce administrative burden. it may help identify subtle patterns or bring additional data into the diagnostic process. But the goal is not to remove the physician from the workflow. The goal is to allow the physician to spend more time on the work that matters most.

Dr. Singh noted, “Using AI to reduce the burden of paperwork, reporting, and documentation. Physician burnout is often driven less by patient interaction and more by administrative workload.”

That is an important reframing. The first wave of meaningful AI adoption may not come from replacing diagnosis. It may come from making the physician’s day more manageable, more efficient, and more focused on patient care.

Infrastructure Is the Enabler

At AVANT BIO, we are particularly interested in enabling technologies: the platforms, tools, and systems that help scientific and clinical innovation scale. In pathology, that enabling layer is becoming increasingly important.

Myles has described PathPresenter as the “connective tissue for digital pathology: the roads and bridges that allow images, systems, and AI tools to work together”. Today, PathPresenter supports image management and viewing across clinical, research, educational, and consultative use cases. Over time, the vision is broader: to become a core infrastructure layer for digital pathology.

Dr. Singh expressed a similar vision from the physician-founder perspective. Rather than remaining a software vendor, he sees the opportunity for PathPresenter to become a true infrastructure partner to institutions, helping them integrate data sources, AI models, workflows, and governance in a way that supports long-term clinical adoption.

A vendor provides a tool. An infrastructure partner helps shape how an institution works.

That distinction matters in Healthtech. The technologies that scale are not always the flashiest point solutions. They are often the platforms that make new capabilities usable, trusted, and repeatable across complex real-world environments.

A More Human Future for AI in Pathology

The most exciting opportunity in digital pathology is not simply improving how slides are viewed. It is expanding what pathology can contribute to patient care.

With digital workflows, integrated data, and AI-enabled tools, pathology may play an even greater role in prognosis, treatment selection, and precision medicine. Dr. Singh sees this as a future where the pathologist’s role becomes larger, not smaller.

 “The job of the pathologist is going to become even bigger.” Dr. Singh said. “They will not only give a diagnosis; they will also help clinicians decide the best treatment and understand the prognosis for the patient.”

Myles echoes this point, describing PathPresenter’s platform as a way to help pathologists sit at the center of precision medicine by making workflows more efficient, reducing reporting burden, and enabling better use of digital tools and AI.

This is where the human and technological stories converge.

AI is not the endpoint. Better patient care is the endpoint. For AVANT BIO, companies like PathPresenter are compelling because they sit at the intersection of clinical expertise, digital infrastructure, Healthtech, and AI enablement. They are not simply building tools for today’s pathology departments. They are helping define the operating environment for the next generation of precision medicine.