On October 15, BioTeam brought together members of Boston’s life sciences community at Democracy Brewing for our second annual Boston Roundtable, with support from AWS.
This year’s theme was AI in Life Sciences: What’s Working, What’s Not & What We’ve Learned. Guests from pharma, biotech, and academic medical centers joined four BioTeam speakers for lightning talks, live audience polls, and an open Q&A, all over beer, cider, and mocktail flights. Each talk drew on BioTeam’s consulting work, and the polls let attendees add their own experience to the conversation.
Four Lightning Talks
Brian Osborne explained how connecting AI agents to an organization’s internal knowledge through retrieval-augmented generation (RAG) and Model Context Protocol (MCP) makes information easier to find, and why preparing the underlying data is often the hardest part.
Wisdom Akpan looked at how teams can gain productivity from AI while keeping the hands-on expertise and critical thinking they need to evaluate its output.
Karl Gutwin demonstrated Delfini, BioTeam’s scientific data platform, which keeps the meaning and context of scientific data intact as teams share it and align it with common standards. Free demo access is available at delfini.bio.
Jennifer Wortman discussed how organizations can set responsible AI practices and still support the people eager to adopt new tools.
Over the coming weeks, we will publish a dedicated article and the full presentation video for each lightning talk. Follow BioTeam on LinkedIn to catch each one.
What the Room Had to Say
Our live polls gave attendees a direct say in the evening’s discussion. A few results stood out:
- Trust and transparency: 92% of respondents said they would trust an AI-generated answer more if it showed its sources.
- Data preparation: 73% of respondents expected data cleaning and tagging to take 25% to 75% of the work in building an AI assistant on their organization’s documents.
- Barriers to adoption: Data privacy was the top concern (33%), followed by cost (27%).
- AI governance: Only 33% of respondents said their organization has a written AI use policy that everyone follows.
These results reflect the people in the room, and they gave the Q&A a strong starting point.
The Common Thread
The talks, polls, and audience Q&A kept returning to one message: the AI model is one piece of the puzzle. The quality of the underlying data, the governance around its use, and the expertise of the people interpreting its output decide whether AI delivers value.
BioTeam works through these questions with life sciences organizations every day, and the evening showed how much teams gain from comparing notes.
Thank You for Joining Us!
Thank you to AWS for supporting this year’s event, to Democracy Brewing for welcoming us back, and to everyone who joined us for an evening of discussion and connection. We are grateful to be part of a life sciences community so willing to share experiences, challenge assumptions, and learn from one another.
Want to explore any of these topics for your own organization? Connect with us at bioteam.net.
