Lab of the Future 2026 Recap: "AI Ice Cream" and the People Challenge of Digital Transformation

Building Data-First in R&D and the Rise of the Bilingual Scientist.

At this year’s Lab of the Future 2026 conference, Team KC’s Angel Kleiman and Felicia Loi were on the ground connecting with industry leaders and discussing what digital transformation really looks like in today’s R&D landscape. As consultants working closely with Biotech and Life Sciences organizations, staying close to where the industry is headed isn’t optional; it is a core pillar of how we support our clients.

While AI and Automation continue to dominate the conversation, the real story is much more nuanced. Angel and Felicia sat down with the team to share their highlights, takeaways, and hot takes:

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Here's what Angel and Felicia had to say:

Q: What was your goal for attending LotF 2026?

Angel: "We work as informatics software consultants with biotech clients in the life sciences industry. Conferences like Lab of the Future are a great opportunity to stay current on where the industry is heading. A lot of what we do involves helping organizations select and implement the right lab informatics platforms, and the landscape is shifting fast right now, especially around AI, automation, and data strategy. Beyond the sessions themselves, it's always good to connect with people we know in the space and meet new faces. Seeing what vendors are doing, hearing what challenges R&D leaders are actually dealing with, and bringing that context back to our client work is a big part of why I go."

Felicia: "Since this was my first conference in the space of lab automation and digital transformation, I was really looking to get a sense of what is happening in the industry right now. I wanted to gain exposure to current trends while also networking and participating in broader professional discussions. With AI being such a hot topic, I was curious to see what the industry is doing with AI and hear the conversations around AI adoption, like where it is already being used and how people are integrating it into research workflows. Overall, Lab of the Future gave me the opportunity to explore the latest advances transforming modern R&D. Keeping up with these trends and staying connected to where the industry is going and the challenges teams are facing are all an important part of our role as consultants."

Q: Did you notice overarching themes throughout the conference?

Angel: "The theme I kept hearing over and over was: get your data foundations right before chasing AI. Multiple speakers reinforced this. Novo Nordisk presented a phased delivery approach that explicitly puts data governance and data models before any AI capabilities, and Nevin Gerek Ince's slide on critical lessons for digital transformation literally led with "Start with Data Foundation, Not AI." One line that kept coming back throughout the conference was that you can't have your AI ice cream until you eat your data vegetables, originally from Julie Huxley-Jones and echoed by Leah O'Brien from Sanofi on Day 2.

The other major thread was workflow reinvention. Takeda's Christopher Arendt made the point that it's not enough to digitize existing wet lab processes. You need to fundamentally redesign how the wet lab works to enable the dry lab. That resonated with me because it's exactly the kind of challenge our clients face when they try to layer new tools on top of old ways of working."

Felicia: "One of the biggest overarching themes I noticed was that AI and machine learning are here and they are here to stay. The message throughout the conference talks was that this is something the industry needs to take advantage of and adopt, or risk falling behind if they refuse to adapt. There were a lot of interesting discussions around what future teams will look like, particularly the idea that teams will be made up of both humans and AI working together. In this sense, we are also starting to see the definition of a scientist evolve from someone with purely wet lab experience to a “bilingual scientist” who is comfortable working across both wet and dry lab environments.

Another major theme was the importance of partnerships. The idea that no single company can be the best at everything came up repeatedly. Entering into and investing in strategic partnerships will be the most effective way to advance innovation. A good example is the growing number of collaborations between tech companies and pharma organizations. We are already seeing examples such as the partnership between Lilly and NVIDIA, announced earlier this year, which highlights co-innovation between NVIDIA's AI and accelerated computing and Lilly’s expertise in discovering, developing, and manufacturing medicines."

Q: What’s the most interesting insight you took away?

Angel: "Two things sparked ideas for me. During Gene Lee's talk from ZS on next-gen research agents, I started thinking about using AI not just to analyze structured data but to actually structure unstructured data in the first place, and potentially even backfill gaps in existing datasets. That feels like a near-term, high-impact use case that a lot of organizations could act on today.

The other insight that stuck with me was from Amgen's decade-long data network journey. Matt Potter-Racine was candid that after ten years of significant progress toward data-first practices, truly transforming how people work is still fundamentally a people challenge, not a technology one. There is still limited real-world, complete end-to-end digitalization in CMC. That kind of honesty is valuable because it sets realistic expectations for organizations just starting out."

Felicia: "One of the most thought-provoking moments for me came during the second Keynote Q&A panel on Day 1. A question was raised about how large pharma companies plan to expand traditional vendor relationships as the industry innovates toward more autonomous labs. This question was posed in response to James Love’s presentation, in which he argued that we need to move away from recreating human processes with automation. Instead, we should be innovating workflows that are designed for automation from the start. This was an interesting perspective because it challenges how many labs are currently approaching automation.

It also highlighted an important dynamic in the industry. Vendors will need a firm commitment from large pharma organizations before making major investments in new automation capabilities (i.e., innovating the stacking of pipette tips for autonomous labs). Without that level of partnership, there is little incentive to push those innovations forward. For me, this insight reinforced how critical collaboration and strategic partnerships, both between vendors and suppliers and between organizations across the industry, are if we want to truly move towards the “next-generation” lab."

Q: Did you have a favorite talk, booth, or presentation?

Angel: "I enjoyed Cindy Novak's (Avidity Biosciences) talk on building an integrated, autonomous lab, which really stood out to me. She made the point that automation doesn't fail because of technology; it fails because of the architecture. That distinction is so important and something I see play out with our clients all the time. Many organizations have pockets of automation, but very few have truly connected them into something cohesive. Cindy called them "islands of integration," which I thought was a great way to put it.

She also emphasized going back and tagging your historical data, saying it's worth the time and effort. That's advice many organizations skip over because it feels tedious, but it's the kind of foundational work that makes everything else possible. Her framing of data management as required infrastructure rather than administrative work really stuck with me. It ties right back to the broader conference theme that the future lab isn't defined by the instruments it uses; it's defined by how it connects them."

Felicia: "One of my favorite sessions was one of the live labs at the end of Day 1. There were three live labs available, designed as smaller, moderated group discussions rather than traditional presentations. This allowed for a much more open and interactive conversation. The one I attended was Does AI Drive Creativity in Drug Discovery or Just Exhaust the Search Space? The moderator prompted the group with some really thoughtful questions that first asked us to define creativity, then consider how that concept might apply to AI, and finally brought those ideas back to the drug discovery process.

A lot of interesting perspectives came out of the discussion, and I appreciated that it was not just speakers presenting their views. Hearing thoughts from other attendees, who came from different backgrounds across biotech and pharma, made it feel like a much more dynamic conversation and gave a broader view of how people in the industry are thinking about AI’s role in discovery."

Q: What was your “hot take” from the conference?

Angel: "There was so much great energy around AI agents, autonomous labs, and the future of science. At the same time, I think it's worth acknowledging that most organizations are still working with legacy instruments, unstructured data, and workflows that haven't been redesigned in years. The vision is exciting, but getting there is going to take a lot of foundational work that isn't as flashy.

I also noticed the question of "what does the scientist of the future look like?" came up in almost every session. It's clearly on everyone's mind. For me, the piece I hope we keep talking about is collaboration. Science is creative and iterative, and it depends on people challenging each other and building on ideas together. As AI becomes more embedded in how we work, I think it's important to make sure it's helping scientists work better together, not just more efficiently on their own.

One more thing that I wish had gotten more airtime: sustainability. Mark Borowsky raised it on Day 2, asking whether AI should be a net positive on human health, and whether powering AI at scale is worth it if the environmental cost is too high. It's a fair question and one I think the industry will need to take more seriously as these technologies scale up."

Felicia: "While this might not be a traditional 'hot take', a few speakers suggested that ELN and LIMS systems have already had their moment in the spotlight and implied that they will become irrelevant in the future. I don't necessarily agree with that perspective. I think there will always be a need for at least an ELN, especially in research. My take is that ELNs and LIMS won't become redundant, but they will be transformed. As labs integrate AI and automation, scientists will still need systems to track processes, record experiments, and ensure reproducibility. Research, in particular, is unlikely to become fully autonomous, so having structured, electronic records will remain crucial. Paper notebooks or scattered Excel files do not allow for easy parsing or big-picture insights."

Q: What conversations or themes from the conference do you hope will carry forward into broader industry dialogue? Is there anyone specific you had/heard these conversations from?

Angel: "One thing I kept noticing throughout the conference was that larger pharma companies are realizing they need to be more agile. A lot of the approaches they were talking about, like iterating quickly, staying flexible with architecture decisions, and designing for change, are things you'd normally associate with smaller labs and biotech organizations. I think that shift is really interesting, and I hope it keeps getting attention because the organizations that figure out how to move fast at scale are going to be the ones that see real results from all of this investment in digital transformation.

The other conversation I hope continues is about governance. It came up in multiple sessions, and many panelists honestly said they still haven't figured it out. That's not a criticism, it's just reality. As AI, automation, and data ecosystems get more complex, governance can't be something you bolt on later. It needs to be built in from the start and treated as an ongoing operational practice, not a one-time exercise. I'd love to see more organizations sharing what's actually working for them on this front."

Felicia: "One remark that really stuck with me came from Gisele Tavares during the closing plenary. She mentioned how surprised she was that humans, and the people themselves, were such a central part of the conversation across the talks she attended. I completely agree with this insight. When discussions about AI and machine learning come up, there is often a fear that these technologies will replace scientists. However, a common theme throughout the conference was that the role of scientists is evolving rather than disappearing. People will remain essential even as labs become more automated.

Another perspective that resonated with me was from Julie Huxley-Jones, who highlighted that science is iterative, interactive, and relative–not as much of a factory as we have originally believed. This really reinforces the point that, ultimately, it is all about the people and their ability to adapt, collaborate, and drive innovation. I hope to see more dialogue around the people side of automation and AI."

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Lab of the Future reinforced something we see every day in our client work. Success isn’t about chasing the latest technology; it’s about building a solid foundation. 

While wrapping up her final thoughts, Angel shared one quote from a panel that stuck with her:

" "We are the new unicorns." As someone who bridges the gap between the lab bench and digital every day, it was a nice moment of recognition that this combination of skills is increasingly valuable and in high demand. It's an exciting time to be doing this work."

Whether it’s establishing strong data models before introducing AI, rethinking workflows instead of layering tools onto legacy processes, or navigating complex integrations, these problems aren’t theoretical for us; this is exactly where we focus. And while there’s no one-size-fits-all approach, Karchem Consulting is ready to see where we can fit to support your team.

Curious to learn more? Contact us to get started.