Pulling away from the lab, even for a few days, can feel like a risk. Schedules are tight, teams are stretched, and the work does not pause. But for today’s lab leaders, the opportunity to attend industry events and step outside their own environments is becoming less of a luxury and more of a necessity. Exposure to different operating models, access to leaders with decades of experience, and chances for peer-to-peer problem-solving are difficult to replicate within the walls of a single lab.
That reality was on full display as more than 200 laboratory professionals recently gathered in Phoenix, AZ, for the 2026 Lab Manager Leadership Summit. Across three days of keynotes, roundtables, workshops, and informal discussions, attendees carved out time from their day-to-day responsibilities to gain new perspectives, build meaningful connections, and find common ground with peers navigating similar pressures.
Looking across the sessions and conversations I had throughout the event, three takeaways stood out.
1. Change management hinges on understanding loss
Change remains one of the most persistent challenges in laboratory environments. New technologies, shifting regulations, evolving workflows—these forces rarely arrive without disruption. Yet the Summit’s opening keynote reframed the conversation in a way that resonated across industries.
“People don’t resist change, they resist loss,” said Curtiss McNair Jr.
Drawing on his experience leading a transformation from manually processing 95 million samples per year to a fully automated operation, McNair made a clear point: resistance is rarely about the change itself. It is about what individuals believe they are losing in the process.
For some, that loss may be competence—the fear that new systems will make their hard-earned expertise less relevant. For others, it may be a loss of control over their role and how they work. In some cases, it is identity, particularly when roles shift in ways that alter how individuals see their contribution to the organization.
Leaders who overlook these dimensions often struggle to gain buy-in, even when the change itself is objectively beneficial. McNair emphasized that effective change management requires acknowledging those perceived losses directly and then exchanging them with something that has value to them.
That might include new skills, reduced manual burden, increased impact, or opportunities to work at a higher level. But those gains must be articulated in a way that feels tangible and relevant to the individual, not just the organization.
This approach not only eases resistance but also builds trust. When leaders demonstrate that they understand what is at stake for their teams, they create the conditions for people to move forward with confidence rather than hesitation.
2. The current state of AI in the lab: A shift from curiosity to scaling
If change management is a constant, artificial intelligence represents the newest and most visible source of disruption in the lab.
At the 2025 Leadership Summit, many conversations around AI centered on exploration. Attendees wanted to understand what the technology could do and whether it had a place in their environments. Some had experimented with early use cases, but widespread adoption remained limited.
One year later, the tone has shifted.
The question is no longer whether labs should use AI; it is how to scale it.
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Many attendees shared practical, small-scale applications already in use. Inventory tracking and management surfaced as a successful entry point, along with basic workflow support and data organization tasks. These implementations often start with individual users or small teams looking to reduce friction in their daily work.
But scaling those efforts introduces a new layer of complexity.
During a roundtable, one attendee posed a question that captured the underlying concern: Can you fully trust AI?
Adam Steinert, chief technology officer at Yahara Software, responded with a broader perspective: Can you trust any technology in your lab 100 percent of the time?
The point was not to dismiss the concern, but to reframe it. Laboratories already operate within systems that require validation, oversight, and continuous monitoring. Instruments fail. Software produces errors. Workflows break down. Yet labs manage these risks through structured processes.
AI should be treated the same way.
As Steinert explained, that means developing clear strategies for where and how it will be used, establishing standard operating procedures, defining validation approaches, and ensuring staff receive appropriate training. Rather than viewing AI as a separate or exceptional category, leaders can integrate it into existing governance frameworks.
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The challenge now is less about experimentation and more about infrastructure. Labs must determine how to move from isolated use cases to organization-wide applications that are reliable, compliant, and aligned with broader operational goals.
Those who succeed will not necessarily be the ones who adopt AI first, but the ones who scale it effectively.
3. Career development requires intentional effort
One of the most striking insights from the Summit focused on something more personal: career development.
In a session led by April Day, senior director of clinical pathology at Geisinger Health System, attendees were asked a simple question: Do you know where you want to be in five years?
Most hands went up to signal "yes."
The follow-up question told a different story: Do you know what skills you need to get there, or the path required to achieve that goal?
Nearly every hand went down.
This gap highlights a common challenge, particularly for those early in their career or in middle management roles. Many have a clear vision of their future but lack a structured plan to reach it.
Day outlined a framework to close that gap, starting with a foundational step: defining the leader you want to become.
That requires identifying core values and using them as a decision-making filter. Without that clarity, it becomes easy to pursue opportunities that may advance a career in the short term but do not align with long-term goals.
From there, leaders can define the scale and scope of responsibility they want to take on, build the capabilities required for that future role, and intentionally develop a network that supports those ambitions.
Equally important is the idea of legacy—what impact you want to leave behind. This perspective shifts development from a reactive process to a purposeful one.
Day also challenged attendees to rethink the questions they ask themselves. Instead of focusing on limitations—What do I want? Do I know how? Is this in my scope? She encouraged a shift toward opportunity and growth:
What is the opportunity?
What do I need to learn?
What skills can I develop?
This mindset is not just about personal advancement. It directly influences how lab leaders support their teams. Leaders who take ownership of their own development are better equipped to guide others, create growth pathways, and build more resilient organizations.
Looking ahead
The 2026 Lab Manager Leadership Summit reinforced a clear reality: the challenges facing laboratories are not getting simpler. But neither are the tools, strategies, or communities available to address them.
For those who attended, the value extended well beyond the sessions themselves. It was seen in new perspectives, practical ideas, and connections that will continue to influence their labs long after returning home.
Stepping away from the lab, even briefly, can provide the clarity needed to lead more effectively within it. The next opportunity to do so is already in the works. The 2027 Lab Manager Leadership Summit will take place in Salt Lake City, April 12-14. To stay informed and receive updates, visit: summit.labmanager.com/leadership
