Technology is changing how we work in the lab – at a pace that can feel overwhelming for those at the front line. Resistance to learning new systems is common. And understandably so. It can be frustrating to have to remaster a task in which you were formerly a "black belt."
In the light of increasing conversations on this topic, The Pathologist was curious to hear how different organizations are managing change right now. Here, six lab leaders share their strategies for introducing digital technologies into the lab.
Progress begins when you replace assumptions with curiosity
By Sean Downing, Chief Scientific Officer, Vector Laboratories
Change management is rarely about the technology or the process itself. It’s about people learning to trust one another enough to move in the same direction. In my experience, progress begins when you replace assumptions with curiosity. Teams often get stuck because they evaluate risk, urgency, and success through different lenses. This is very different from not agreeing on the goal.
The fastest way to unlock momentum is to bring those groups together early, feed their curiosity, and let them see the world through each other’s eyes. When IT understands why timelines matter to R&D, and R&D understands the constraints and responsibilities IT carries, the conversation shifts from “why can’t you do this?” to “how can we do this?” That shift from defensiveness to shared problem-solving is where real change begins.
Sustaining change requires something different: clarity, empowerment, and a culture where communication doesn’t disappear the moment a project plan is written. I’ve learned that alignment only becomes durable when ownership is shared, champions exist on every team, and people are trusted to make decisions without fear of being wrong. When mistakes are treated as learning opportunities rather than failures, silos lose their power, decisions are made faster, and teams start to operate with a rhythm that doesn’t depend on any single person. It falls on leaders to set the vision, remove friction, and create these conditions where teams will thrive, but they shouldn’t need to be in every meeting. Building a system where progress continues even when you’re not in the room is the real feat of strength when it comes to change management.
Technology must serve our scientists
By Misagh Naderi, CEO, Glint Lab
At Glint Lab, change is never implemented for its own sake. When we evaluate new workflows, we ask why this change, and why now? In early discovery, even minor adjustments can introduce data variability that jeopardizes months of work. Our unique challenge as a CRO working with preclinical teams in pharma and biotech is balancing the adoption of cutting-edge technology with the strict continuity required for long-term preclinical studies.
To strike this balance, we look to our people. Technology must serve our scientists, which is why our bench teams are always consulted before we onboard a new tool. Their day-to-day expertise catches the edge cases and dependencies that algorithms or executives might miss. In a fast-paced CRO environment, change management isn't a distraction from the science. It’s the mechanism that drives it forward.
Executive sponsorship is key
By Derrick Forchetti, Pathologist, South Bend Medical Foundation
Change is difficult for everyone, regardless of enthusiasm. For any organizational change to succeed, there must be visible commitment from the very top of the organization. Internal champions matter, but they cannot substitute for executive sponsorship, and without it, projects tend to fail, no matter how much support exists elsewhere.
It sounds intuitive, but it bears repeating: there is never a perfect solution. Every change involves compromise, and in some respects, the old way of doing things may genuinely outperform the new. The right question isn't whether a change is flawless, but whether it produces a net benefit, and that benefit may accrue to the organization as a whole rather than to any individual or department. Acknowledging those trade-offs openly, rather than overselling the change, builds the credibility leaders need to carry people through it.
Redesigning workflows for a global workforce
By Amanda Hemmerich, Global Director of Digital Pathology Innovation, IQVIA Laboratories
Digital pathology is introducing new opportunities to standardize processes, integrate advanced analytics, and enable remote and collaborative review across sites. But it also requires careful re-engineering of long-established laboratory practices. For us at IQVIA Laboratories, this underscores that change management is not just about adopting innovative technology, but also about redesigning workflows to ensure quality, reproducibility, and scalability across global teams and studies.
Successful adoption depends on the same rigor that has long defined laboratory-based sample testing: robust validation, clear standard operating procedures, and continuous training. From slide preparation and scanning to image management and interpretation, each step must be optimized for the digital environment, monitoring performance and long-term improvement with predefined quality control metrics.
In practice, digital pathology is expanding collaboration and innovation in drug discovery, enabling more data-driven decision-making and globally connected expertise. Whether implemented in a hospital or a clinical research organization, sustainable change depends on building a culture of continuous learning, cross-functional alignment, and disciplined oversight to ensure these advances translate into better, more consistent patient outcomes.
Our physician-led approach focused on the practical benefits
By Jordan Olson, Chief Medical Officer, HNL Lab Medicine
The implementation of digital pathology at HNL Lab Medicine followed established change management best practices, drawing on the Prosci Change Management methodology. The program prepares physicians for a fundamental shift in clinical workflow rather than simply introducing new technology.
We placed emphasis on building awareness and desire before implementation, asking a respected physician champion to communicate the clinical value of digital pathology to colleagues. Rather than presenting the transition as an IT initiative, the focus remained on the practical benefits that mattered most to pathologists: improved access to cases, greater flexibility, easier subspecialty collaboration, and reduced dependence on physically transporting slides. This physician-led approach – combined with clear and consistent communication about implementation timelines, expectations, and available support – helped reduce uncertainty while reinforcing the "what's in it for me" that is widely recognized as a critical component of successful change adoption.
The implementation strategy also reflected best practices for building knowledge, ability, and long-term adoption by allowing pathologists to gradually integrate digital sign-out into their routine practice before glass slides were retired. An extended hybrid period, multiple training formats, informal peer support, and occasional reduced case-load days acknowledged that developing confidence with a new clinical workflow requires time and organizational investment.
Equally important was establishing a clear endpoint for hybrid practice. Defining when digital pathology would become the expected standard prevented prolonged parallel workflows, reinforced adoption, and embedded the new process into everyday practice. By combining physician leadership, structured communication, practical training, individualized benefits, and a defined transition plan, HNL Lab Medicine successfully applied recognized change management principles to transform digital pathology from a technology implementation into a sustainable model of clinical practice.
AI-assisted workflows fail without decision architecture
By Luis Cano Ayestas, Physician-Scientist & Independent Consultant, Translational Medicine & Biomarker Strategy
The most common mistake in digital pathology change management is treating it as a technology problem. Organizations invest in platforms, training, and validation studies – and then wonder why behavior doesn't change. The answer is rarely technical. It's architectural.
Platforms today can produce AI-generated outputs that are reproducible, traceable, and transparent. That's a genuine achievement. But reproducibility doesn't equal actionability. A pathologist can receive a verified result and still face the hardest question unanswered: is this enough to act on? A scientist can access a perfectly versioned biomarker pipeline and still not know whether that output is ready to survive a program decision or a regulatory conversation.
The gap isn't in the technology. It's in the decision framework – the shared criteria that tell experts when to trust a result, when to escalate, and when to reject. Without that framework, AI outputs become one more data point in an already crowded room. People default to what they know, and the platform gathers dust.
Real change management means building that bridge. It means defining, in advance, what "good enough to act" looks like for each context – clinical, regulatory, or programmatic. And it means having someone who has already crossed it: a credible peer who can say, I did this, it worked, and here is how.
Technology moves faster than trust. The organizations that close that gap won't just be early adopters. They'll be the ones that invest as much in decision architecture as they do in platforms.
The Pathologist thanks Sydney Fenkell, VP, Communications, at Proscia, for her assistance in collating these contributions.
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