Until recently, technology hadn't done much to change that. The paper has moved into the system, but the work is still an intensive manual review.
In the last few years, capabilities have changed drastically, and this exact program-building problem is one we’re currently tackling at ScholarOne Conferences as part of our focus on AI-driven efficiency. It's only the beginning.
Technology trends shaping the landscape
Machines capable of human-like judgment and general reasoning first reached us through chatbots. Things have moved on rapidly from there, first to agents, which combined reasoning capability with tools and the ability to take action. Then came teams of agents — think orchestrators handing work to sub-agents working in parallel — opening up the scale of what AI could do.Perhaps the most important evolution, though, has been behavioral. Human-in-the-loop frameworks are only a few years old, but teams are becoming comfortable working with AI while reserving matters of taste, judgement, and connection to the people that matter.
For scholarly communities, where expert curation is the foundation of trust, this may be the most important shift of all.
What's happening in event tech
Beyond macro-level tech trends, there’s the event technology landscape. Covering trade shows, community events, professional meetings and more, this sector goes well beyond scholarly conferences, yet emerging themes from the last few years are surprisingly resonant for our space.AI and agent workflows have been big news in event tech, with much of the focus on the efficiency and scale they can bring to organizers.
But two other trends also stand out to me, and they speak to quality and data insights:
- Behavioral intelligence. Wearables and other on-site tools that capture very specific, granular detail about how attendees experience an event: which sessions they attend, how long they stay, where they gather.
- Enhanced experience. Think live translation that opens sessions to attendees in their own language, or in-event matchmaking technology that connects people with the colleagues and research most relevant to them.
What does all this mean for scholarly conferences?
Right now AI-driven efficiency is the primary focus, and it should be. There are some long-standing pain points in the events workflow that are a perfect fit for AI. My opening program-building example is one of them.That's where our current work at ScholarOne Conferences is concentrated. The AI Program Builder is now in beta testing with a select group of clients. It takes a first pass at the program, taking the bulk of the manual comprehension and coordination, so that committees can focus on the editorial decisions only they can make. Alongside it, we're exploring AI-assisted session building and testing an enhanced AI Duplicate Detector. Each tool targets a problem that costs societies significant time and money, and each one combines AI's judgment and reasoning with system integration and human oversight. The events committee still makes the calls — they just don't start from a floor covered in paper.
Beyond efficiency: insights and quality
The driver for efficiency is to free up conference staff so they can spend more time with their volunteers on delivering great events. I think AI can help there too.Once the big efficiency gains are in place, I see insights and quality as the next focus for AI in event workflows.
One question I keep coming back to: how are societies using their data beyond the conference? Could they use it to understand their members better, reach out to them more effectively, and strengthen the connection between conferences?
CME credit tracking is a good example. When I worked at a society, student volunteers stood at the door of each session signing people in and out for their CME credits. Today, wearables and badge scanning can do that automatically. That on-site data becomes far more useful when it's tied back to a person's profile. Right now, data from ScholarOne Conferences might show what abstract someone submitted and what they reviewed, but everything they did at the conference sits somewhere else. What if that went back into their profile too?
Combine that with data from other systems and you can build a rich picture of a person: what they submitted to the society’s journal, what they reviewed, what membership benefits they use, which conference sessions interested them, whether they came to the social events.
Today, those signals live in three or four different places, and nobody sees the full picture. Connected, they give the society a fuller profile of their community.
This is where enhanced experience and quality come in. The societies I've worked with talk constantly about using their data to build community and reach people where they are. Insights to drive quality. Think matchmaking tools built on rich, connected profiles, or improved content recommendations driven by event activity data.
The same connected thinking applies to the content itself. Conference content integrated into the full scholarly record workflow, capturing the valuable research and discussion that happens at conferences.
Where do you think conference tech is going?
Right now the ScholarOne Conferences team are iterating on the product with customer feedback like never before. Efficiency is our main focus, but we’re always watching what’s coming next.I want to know where you think the industry is going, what’s going to be important for event teams 6, 12 and 18 months from now. I’ve laid my thoughts out here, but your opinions influence my opinion and I want to hear them.
If any of this resonates, or if you see things differently, get in touch.