Is the Role of the Large, Live Medical Meeting Changing?
The value proposition of the large live medical meeting has been straightforward: gather experts, present the latest science, disseminate new evidence, and send clinicians home with the latest information to be applied in practice.
This model has existed for decades.
Today, however, as technology accelerates and access to information becomes nearly instantaneous, continuing medical education (CME/CE) professionals face a fundamental question: What happens when information is no longer scarce and the latest evidence is readily accessible?
Recent literature suggests that generative AI is rapidly changing how healthcare professionals access and interact with new information (Harvard Medical School, 2024). AI systems are increasingly capable of summarizing literature, supporting clinical reasoning, generating personalized educational content, and facilitating just-in-time learning. Medical educators are now exploring how these technologies may fundamentally alter traditional educational models by shifting the value of education away from information acquisition and toward interpretation, application, and collaborative problem-solving (Triola & Rodman, 2025).
The traditional educational advantage of being physically present in a lecture hall to hear the latest information is beginning to erode.
This is not a criticism of live education. It is recognition of a changing reality.
If a clinician can obtain the core facts from a conference presentation within moments using AI-assisted tools, why should someone travel across the country, spend thousands of dollars, and take time away from patients to attend a meeting in person?
The answer may define the future of live accredited continuing education.
The purpose of the large, live medical meeting may need to evolve from information dissemination toward something technology cannot easily replicate: human convergence.
What Have Live Meetings Traditionally Done Well?
To understand where live meetings may be headed, it is important to understand what they have traditionally done exceptionally well.
Historically, conferences have delivered value in four key ways:
1. Information Transfer
Information transfer has long been the centerpiece of live, medical meetings.
Experts synthesize evidence, share research findings, and interpret emerging data. Participants receive information that would otherwise require significant effort, or have been near impossible, to gather independently.
For many years, conferences represented one of the fastest ways to learn what was new in medicine.
2. Professional Networking
The hallway conversations and in-person professional networking with peers, often, can be as valuable as the formal sessions. Clinicians exchange experiences, compare approaches, discuss challenges, and build relationships that extend far beyond the event itself.
3. Community Formation
Medicine can be professionally isolating. Live meetings bring together individuals who share common interests, specialties, and challenges. They reinforce professional identity and create a sense of belonging and shared purpose.
4. Collective Interpretation
New evidence rarely speaks for itself.
Healthcare professionals need opportunities to discuss implications, challenge assumptions, and collectively determine how emerging science should influence practice. Historically, conferences have provided an environment where this interpretation could occur.
Importantly, only one of these four functions is primarily about information. The other three are fundamentally human activities. That distinction becomes increasingly important as AI capabilities continue to expand.
The educational community often discusses what AI can do. A more important question may be, what can AI make unnecessary When viewed through this lens, traditional lecture-centric conference models face increasing pressure.
Consider a common conference experience: A clinician attends a 45-minute presentation summarizing recently published evidence. The slides were finalized weeks before the meeting. The audience listens passively. Questions are limited to a few minutes at the end.
Now, compare that experience with what is becoming possible through AI-enabled systems. A clinician can:
- Access evidence instantly
- Generate personalized summaries
- Ask unlimited follow-up questions
- Explore specific patient scenarios
- Compare competing studies
- Translate complex findings into practical recommendations
And they can do so without airfare, hotel costs, registration fees, or time away from practice.
The implication is not that conferences become obsolete; rather, information delivery alone may no longer justify in-person attendance.
Educational planners who continue to design meetings primarily around content transmission may find themselves competing against technologies that are increasingly faster, more personalized, and continuously available. The risk is declining attendance and declining relevance.
Why Might a Shift from Information to Experience Be Critical for Live Meetings?
As information becomes more abundant, the value proposition of live education must evolve into something else. The future of live meetings may depend less on what attendees learn and more on what attendees do together, shifting education from transmission of information to education as experience.
Information can be delivered digitally, but experiences require active participation.
Information can be personalized by algorithms, and experiences emerge through interaction.
Information can be generated by machines. Relationships cannot.
Effectively, the next generation of medical meetings may be designed around creating opportunities for meaningful human engagement rather than maximizing the number of presentations delivered.
So, what experiences are uniquely worth gathering for, in person? One possible answer is “collaborative intelligence.”
Collaborative intelligence recognizes that the most complex healthcare challenges cannot be solved by a single discipline, stakeholder group, or technology platform.
Collaborative intelligence requires diverse perspectives working together. Healthcare increasingly exists at the intersection of:
- Clinical expertise
- Patient experience
- Data science
- Technology
- Health policy
- Quality improvement
- Compliance
- Education
Many current educational meetings often keep these perspectives separated.
Clinicians attend clinician sessions.
Educators attend educator sessions.
Researchers attend research sessions.
Patients may be invited to speak but not often do they participate as equal contributors in problem-solving activities.
Collaborative intelligence challenges traditional models of education. Instead of organizing meetings around content categories, collaborative intelligence organizes interactions around shared healthcare challenges. Participants become contributors rather than audiences. The outcomes goal shifts from learning about problems to solving them together.
Human Convergence: What does it Mean?
The concept of human convergence may become one of the defining characteristics of future live education. Human convergence occurs when diverse stakeholders gather in real time to tackle challenges that benefit from multiple perspectives.
AI systems cannot fully replicate this process. Technology can facilitate discussion, but it cannot fully replace lived experience. Consider a healthcare challenge such as improving adherence to a new therapeutic regimen.
A clinician understands clinical barriers.
A patient understands practical realities.
A data scientist identifies patterns in outcomes data.
An educator understands adult learning theory and behavior change principles.
A compliance professional understands regulatory considerations.
The solution emerges not from any one perspective but from the interaction among them. The value lies in the conversation itself. This is something fundamentally different from traditional conference lectures. It is also something uniquely suited to live environments.
What Could a Reimagined Live Meeting (or Conference Session) Look Like?
What might this look like in practice?
Imagine replacing a traditional 60-minute lecture with a structured collaborative session.
Instead of:
- 50 minutes of presentation
- 10 minutes of questions
Participants experience:
- 10 minutes of framing
- 40 minutes of facilitated interprofessional collaboration
- 10 minutes of synthesis
The educational objective changes.
Participants are no longer expected to simply absorb information; they are expected to contribute expertise, challenge assumptions, and collectively generate solutions.
The session becomes a laboratory rather than a classroom, and the outputs become as important as the content.
Participatory Education: What Is This Approach?
Educational research consistently demonstrates that active participation enhances learning. Yet, many conference formats remain largely passive. Malcolm Knowles’ theory of andragogy suggests that adult learners are self-directed, bring significant prior experience to educational activities, value learning that is immediately relevant to real-world challenges, and are motivated by opportunities to solve practical problems (Bundy, 2024; Knowles, 1984).
Collaborative intelligence extends active learning beyond audience response systems and small-group discussions – it positions attendees as co-creators of educational value. Participants help generate insights, identify solutions and shape future directions. The educational activity becomes something created collectively rather than delivered by experts.
This approach aligns closely with adult learning principles, which emphasize relevance, experience, reflection, and application (Bundy, 2024). More importantly, it aligns with the realities of modern knowledge acquisition. If information is readily available, education must focus increasingly on interpretation, application, and innovation.
What Might the New Return on Investment for Live Meetings Become?
Conference organizers and CME/CE professionals often focus on attendee evaluation data. Future meeting attendees may increasingly focus on return on participation. Versus asking: “What information did I receive?” They may ask: “What happened because I was there?”
The most valuable conference experiences may become those that produce outcomes such as:
- New collaborations
- New solutions
- New partnerships
- New perspectives
- New initiatives
If collaborative intelligence becomes an increasingly important educational model, planners may need new design principles. This model should also include perspectives beyond traditional faculty: patients, technologists, data scientists, policymakers, and other stakeholders often provide critical insights.
How Can Planners Evaluate Which Sessions Should Be Live?
Educational planners can begin evaluating sessions using a simple question: Could this experience be replicated effectively by AI or digital content alone? If the answer is yes, the session may not require a live format. If the answer is no, the session may represent a strong candidate for live engagement.
Examples include:
- Peer-to-peer consultation
- Interprofessional problem-solving
- Stakeholder collaboration
- Relationship development
- Consensus building
- Innovation workshops
These activities derive value from human interaction rather than information delivery.
What Is the Future Role of AI in Live Medical Meetings?
Generative AI is unlikely to eliminate the need for continuing education. Instead, it may fundamentally redefine where educational value resides.
Emerging literature suggests that AI can enhance medical education through personalized learning pathways, simulation, decision support, content summarization, and administrative efficiency (Shiferaw et al., 2025). At the same time, researchers continue to highlight concerns related to hallucinations, accuracy, overreliance, automation bias, and the preservation of critical thinking skills (Generative Artificial Intelligence in Medical Education, 2025).
As AI assumes a larger role in information retrieval and synthesis, educational planners may have an opportunity to shift live learning toward activities that emphasize human judgment, interdisciplinary collaboration, ethical reasoning, empathy, negotiation, and innovation – capabilities that remain difficult to automate. Recent scholarship increasingly points toward hybrid models in which AI augments human learning rather than replacing it (Triola & Rodman, 2025).
What Would You Show Up For?
Analyzing what you would show up for as a learner, yourself, helps cut through assumptions about traditional conference design and challenges planners to focus on irreplaceable value. Most clinicians no longer need to travel for access to information, but they’ll likely travel for connection, collaboration and inspiration. They’d very likely travel to solve problems with people they would not otherwise encounter. Meetings that thrive in the coming decade may be those that intentionally design for these outcomes, and collaborative intelligence offers one potential framework for this evolution.
References
- Bundy, L. (2024). Embracing andragogy: The benefits of tailoring medical education for adult learners. Springer Healthcare IME.
- Generative artificial intelligence in medical education: Enhancing critical thinking or undermining cognitive autonomy? (2025). Journal of Medical Internet Research, 27, e76340. https://doi.org/10.2196/76340
- Harvard Medical School. (2024, October 15). How Generative AI Is Transforming Medical Education. Harvard Medicine Magazine
- Knowles, M. S. (1984). The adult learner: A neglected species. Gulf Publishing.
- Shiferaw, A., et al. (2025). Generative artificial intelligence in graduate medical education. Frontiers in Medicine, 11, 1525604. https://doi.org/10.3389/fmed.2024.1525604
- Triola, M. M., & Rodman, A. (2025). Integrating generative artificial intelligence into medical education: Curriculum, policy, and governance strategies. Academic Medicine, 100(4), 413–418. https://doi.org/10.1097/ACM.0000000000005963
