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We are all aware that the insights function has entered a new era. So we recently brought together senior insight leaders from across healthcare and the pharmaceutical industry in Boston to have an honest conversation about the state of their function.
No polished slides, no presentations. Just candid discussion about what’s working, what’s breaking, and what’s keeping them up at night.
What emerged was a picture of a profession under pressure, but that is quietly transforming.
Takeout 1
AI adoption is accelerating, but teams are still shaping their strategy
AI is firmly on the agenda within life sciences, but long-term strategies are still in progress. Everybody is using AI and pushing to understand where it genuinely helps the business and the work insight teams are doing, with rising pressure to adopt being driven by time and budget constraints.
But the efficiency gains are real and important. There was a great example of compressing a project from 14 weeks down to 15 days, at a quarter of the cost. This is particularly impressive in the healthcare landscape where traditionally timelines are a lot longer. In this particular example, the approach included AI-moderated research, digital twins and ad-board simulations with 90% directional accuracy. Everyone was surprised with the results.
However, the risks are still very front-of-mind. Hallucinations, training data that doesn’t reflect current reality, the ‘garbage in, garbage out’ challenge, outputs that sound authoritative but aren’t. Human validation remains essential for context, judgment, and knowing which story matters for which stakeholder.
Takeout 2
The idea that ‘AI is good enough’ could be an existential threat
There is an uncomfortable truth that surfaced. If your stakeholders believe AI output is good enough then they may stop asking you for input.
“If they think whatever we get from AI is fine, then I’m not needed.”
This is a real competitive threat facing insight functions. But the response isn’t to resist AI, it’s to own the layer that AI can’t replicate. Interpretation, judgement, and the human context that makes insight matter to a brand or organisation.
We also discussed how training AI models primarily on internal data risks creating an echo chamber. This can end up reconfirming existing decisions, rather than genuinely challenging thinking.
Takeout 3
Always-on insight is creating always-on noise
The volume problem is real where teams are generating more insight than ever. There is a concern that always-on / continuous insight can become noise without action. As budgets and perceived value continue to be scrutinised, the solution is not to deliver more, but to prioritise ruthless curation and communication of insight projects.
We discussed actively cutting back the volume of communications and beginning to track engagement. Are people actually reading what’s being sent internally and externally? It’s an uncomfortable question, but the right one.
If your insight isn’t being consumed, it isn’t driving decisions.
Takeout 4
Stories still beat dashboards
For all the AI discussion in the room, one truth kept surfacing. The insights that travel furthest in organisations are the ones with a human voice. There is particular value in hearing directly from the patient, whether that is through ethnography, case studies, or audio clips in reports.
“The lived experience always sticks.” … “It’s the stories from real people that really helps drive the point.”
In a world drowning in data, the scarcest commodity is meaning. Those who can translate customer reality into a story that moves a leadership team, that’s the irreplaceable skill.
Takeout 5
Measuring impact is still mostly about vibes
Perhaps the most honest admission of the session. Most insight functions still can’t consistently demonstrate their own value. Impact is still measured informally, often through anecdotes, thumbs-up/ thumbs-down feedback, or binary decisions.
“Previously it’s always been anecdotal.” … “At the minute it’s very, thumbs up, thumbs down kind of thing.”
In a budget and time-constrained environment, and with AI becoming more prominent, this is a clear vulnerability. But there is a push to address this with examples given of building basic frameworks and templates, encouraging their insight teams to make headspace for tracking recommendations made, decisions influenced, and outcomes changed.
But it was also noted that decisions are often influenced by many factors beyond research. Participants stressed that lack of a direct business outcome does not mean the insight lacked value, because priorities and budgets can often override recommendations.
Takeout 6
The future insight team looks different
The future operating model that emerged from the room was an ‘and/both’ approach, with insight teams not needing to choose between technical rigour and strategic influence, but build for both.
That means hiring data scientists who can interpret AI responsibly. And hiring strategic thinkers who can make insights stick. It means being the function that champions the customer voice and the one that governs how AI shapes what you hear.
The closing sentiment from the room was clear:
“You need the human element. That’s why this function can never go away.”
Conclusion
The insight function is being forced to evolve faster than ever. The leaders who will thrive are those who treat AI as an amplifier, not a replacement. And we have to double down on the things that make human insight irreplaceable. Curiosity, judgement, empathy, and the ability to make an organisation feel what its customers feel.
If you’re navigating any of these shifts, we’d love to continue the conversation. Get in touch with the STRAT7 Health team.
About the author
- Lizzie Eckardt
- Managing Director, STRAT7 Incite
She has worked in pharmaceutical market research and brand, marketing and strategy consulting for 20 years. Lizzie is passionate about the intersection of culture and healthcare and specialises in getting closer to lived experience of HCPs and patients. She is also an expert at making those experiences actionable and meaningful for her client’s brands. She has worked with a range of methodologies and loves to innovate and bring consumer approaches into the healthcare world.