Artificial intelligence has become embedded across biotech, reshaping everything from target identification to trial design. Data volumes are expanding rapidly across oncology, biomarkers, and translational research, and AI systems are increasingly expected to surface insights at unprecedented speed.
But technology alone isn’t responsible for moving science forward. “There are still three things AI simply can’t replace. Context, conversation, and trust,” says Sadaf Z. Malik, Senior Director at Crown Bioscience, who oversees commercial strategy supporting oncology science and biomarker research.
Malik sees AI as a powerful accelerator, but not a replacement for the human elements that determine whether innovation actually translates. Those three forces—context, conversation, and trust—will increasingly define competitive advantage in biotech.
When Data Outpaces Understanding
AI excels at identifying patterns across massive datasets, from multi-omics platforms to real-world evidence. In oncology especially, that capability is invaluable as modalities such as antibody-drug conjugates, radiopharma, and spatial transcriptomics generate unprecedented complexity.
However, AI-generated insights can fail to gain traction because the narrative around them is incomplete. “AI doesn’t inherently grasp the full nuance,” she says. In biotech, nuance and context means understanding scientific intent, patient biology, regulatory constraints, and commercial realities at the same time. Without that grounding, even the most elegant outputs risk stalling once they meet real-world decision making.
Leaders who stand out are those who can articulate why a signal matters, how it fits into a development strategy, and what trade-offs it implies. “AI amplifies context,” she says. “Humans create it.”
As AI becomes foundational infrastructure rather than a differentiator, the ability to translate outputs into meaning becomes a leadership skill.
Progress Still Depends on Dialogue
Automation can summarize reports and predict outcomes, but it won’t be able to replace the conversations that align teams around risk, opportunity, and direction. Dialogue has been the engine behind the most impactful advances Malik has supported, from biomarker strategies to cross-functional partnerships.
“The most meaningful progress happens when people challenge assumptions together,” she says. Those moments emerge through live exchange, probing questions, and the willingness to adjust thinking in real time.
With bispecifics, cell therapies, and in vivo engineering advancing in parallel, alignment across scientific, commercial, and operational stakeholders becomes harder to maintain. AI can inform those discussions, but it cannot navigate the trade-offs or build consensus.
Conversation does that work to turn information into shared understanding. As such, organizations that protect space for real dialogue move faster, not slower, because fewer decisions have to be revisited later.
Trust as a Strategic Asset
Biotech ultimately runs on trust between research teams, partners, regulators, and patients. As global partnerships expand and mergers accelerate, that trust determines how freely data move and how confidently long-term bets are made.
In oncology, those moments are inevitable. When they occur, Malik sees trust as the force that enables difficult conversations, course corrections, and continued investment. Far from a soft value, trust functions as infrastructure for innovation.
“It’s built through consistency, transparency, and genuine relationships over time,” Malik says. Algorithms may increase efficiency, but they do not repair setbacks or sustain collaboration when trials miss endpoints or timelines slip.
The Leaders Who Will Stand Out
As AI continues to reshape biotech, differentiation will come from integration rather than adoption speed. The most effective leaders will be those who blend advanced tools with human judgment, who can provide clarity in a data-saturated environment, foster real conversation amid complexity, and invest in trust as they scale.
“Progress doesn’t scale on technology alone,” she says. “It scales when people understand deeply and commit together.” In that sense, AI sharpens the importance of what it cannot replicate: context gives data meaning; conversation gives teams direction; and trust gives innovation staying power.
For more insights from Sadaf Z. Malik on AI in biotech, connect with her on LinkedIn.
