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Over the past two days at Reuters' Pharma USA conference in Philadelphia, I heard many of the themes one would expect at this moment in our industry: acceleration, transformation, productivity, omnichannel orchestration, data modernization, and the growing role of artificial intelligence across the pharmaceutical enterprise.
But one discussion really stood out.
It was a panel session about a question that is as timely as it is profound: How do we ensure that AI, as it is implemented across the pharmaceutical organization, is empathetic? Or said more plainly: How do we train models and LLMs in empathy?
For our industry, this is not merely a philosophical question. It is a strategic one.
In life sciences, we are not simply optimizing transactions. We are engaging in moments that touch diagnosis, uncertainty, treatment decisions, daily disease burden, hope, fear, resilience, and trust. As AI becomes more embedded in commercialization, communications, support programs, content creation, and customer engagement, there is a legitimate concern that speed and scale could come at the expense of humanness.
That would be a mistake, a mistake that jeopardizes trust.
The future of AI in pharma will not be defined only by what these systems can do. It will be defined by how well they reflect the lived realities of the people we ultimately serve.
Empathy is important in every industry. In pharmaceutical and biotech organizations, it is foundational.
Patients are not consumers making casual choices. They are people navigating vulnerability, often in moments of physical pain, emotional strain, logistical complexity, and financial pressure. Care partners are absorbing burdens of their own. HCPs are working within constrained systems while trying to do right by the person in front of them.
Within this context, every commercial strategy, every support experience, every educational touchpoint, and every digital interaction either strengthens trust or erodes it.
That is why empathy cannot be treated as a “soft” concept sitting adjacent to the business. It is part of the business. It shapes relevance, adherence, satisfaction, reputation, and ultimately the credibility of the organization behind the medicine.
And as AI becomes more active in shaping communications and experiences, the question is not whether these tools can become more efficient. The question is whether they can become more humanly informed.
Much of the excitement around AI in pharma is warranted. The technology can accelerate content development, improve internal decision-making, support insight generation, and help teams work at greater scale. It can also create consistency in areas that have historically been fragmented.
However, there is risk in building these systems on a shallow understanding of patient reality.
If we train models primarily on transactional data, operational workflows, clickstream behavior, historical brand content, and structured marketing research outputs, we will get tools that are highly capable of pattern recognition -- but not necessarily capable of human resonance.
They may understand what happened. They may not understand what it felt like.
And in our industry, that distinction matters immensely.
A patient who delays seeing a physician is not just a data point in a funnel. A caregiver who struggles to help her spouse manage a dosing schedule is not just a friction point. A newly diagnosed person is not merely progressing from awareness to treatment initiation.
Behind every step is emotion: confusion, denial, relief, guilt, frustration, fear, fatigue, hope. If those layers are absent from the substrate on which AI is built, then the outputs may sound polished while still missing the mark.
This is where I believe I&A has an especially important role to play.
If the industry is serious about “digital empathy,” then one of the most valuable inputs we can provide is a truly robust patient journey -- especially one that captures not only the transactional journey, but the emotional one.
Most organizations these days are highly adept at mapping the transactional journey. A symptom emerges. A test is ordered. A diagnosis is delivered. Treatment options are considered. A prescription is written. A therapy begins. Follow-up occurs.
That perspective is useful, but highly incomplete.
The emotional journey is where the real depth begins. It reveals what patients and care partners are authentically experiencing at each stage: the hesitation before making an appointment, the profound shock of getting a diagnosis, the confusion around treatment tradeoffs, the silent burden of side effects, the exhaustion of coordinating care, the loneliness that can accompany chronic disease, the guilt a care partner may never say out loud.
When done well, the emotional journey gives us the texture behind the timeline.
And in the age of AI, that texture becomes even more valuable. It provides the context, language, signals, and nuance that can help organizations build tools and experiences that do not merely automate engagement, but humanize it.
Conducting excellent patient journey marketing research is never easy.
By definition, it often asks people to revisit lived experiences that may have occurred a week ago, a month ago, or several years ago. It asks them not only to recall what happened, but to articulate how they felt while it was happening -- which is often much more difficult.
That work requires more than a discussion guide. It requires skill, empathy, trust-building, and a methodology that makes it easier for participants to access and share their own reality. To truly walk a mile in their shoes.
This is precisely where the quality of the approach matters.
Too often, patient journeys are treated as straightforward exercises in sequencing touchpoints. But if the method does not create enough comfort, reflection, and depth, what emerges can be overly rationalized, incomplete, or flattened into a summary that misses the emotional truth.
The best journey work does not just extract answers. It helps people tell their story in a way that feels safe, natural, and authentic.
One of the most important advances in this space in recent years has been the integration of digital ethnography into patient journey work.
At ThinkGen, this has become a particularly powerful part of how we approach these engagements.
Digital ethnography allows participants to chronicle their experience over time, in their own environment, and in a way that is less filtered (or biased, even) by the pressure of a live conversation. Through periodic journaling, patients and care partners can document daily disease experience, treatment realities, small moments of friction, emotional highs and lows, and the practical work of living with a condition.
Importantly, participants can document their experiences not only through written entries, but also through photos, video, and other forms of media. To support this, we have developed a distinctive suite of exercises and templates designed to draw out authentic, in-the-moment realities in ways that traditional approaches often miss.
What emerges from a well-executed digital ethnography is not just a set of quotes. It is a multi-media quilt of the experience itself: a richer, more dimensional view of how life is actually being lived between and amongst the formal moments of care.
That matters because the truth of the patient journey is often found in the in-between: the kitchen counter covered in pill bottles, the parking lot after an appointment, the late-night internet search, the text exchanged with a spouse, the quiet adaptation of a daily routine around treatment burden.
Those details are often what create the deepest empathy.
And because the method allows participants to reflect in their own time and space, the result is often less performative and more real.
That said, technology alone is not the differentiator.
The yield from digital ethnography depends heavily on the design of the experience and on what happens after the entries are collected. In our work, follow-up one-on-one virtual depth interviews are essential for understanding the meaning behind what participants shared. The written and visual material gives us the raw texture; the interview gives us interpretation, context, and emotional specificity.
This is where empathetic moderation becomes indispensable.
The strongest moderators know how to create comfort without leading, how to probe without intruding, and how to help participants revisit difficult moments without making them feel exposed. That is not incidental to the quality of the work. It is central to it.
In a field where many providers can claim access to tools, the real distinction often lies in whether the humans conducting the research know how to unlock the truth those tools are capable of revealing.
There is another element of this conversation that deserves attention: how patient journey findings are delivered back into the organization.
A beautifully executed patient journey can still underperform if its outputs do not travel well across functions. Insights teams may understand the nuance, but commercial, marketing, and strategy stakeholders need formats that make the implications immediate, memorable, and actionable.
This is another area where new approaches are beginning to matter.
We are now seeing the opportunity to utilize AI not only as a subject of discussion, but as an enabler of better research translation -- creating new ways to present patient journey outputs that help stakeholders more vividly understand the patient experience and act on it. When used thoughtfully, AI can help elevate the communication of empathy, not dilute it.
That is an exciting possibility: technology in service of making the human story more visible.
One of the most useful reminders from the past two days is that empathy and innovation are not opposing forces. In pharma, they must advance together.
If we want AI to support better commercialization, better engagement, and better decisions, then we have to build it on a more faithful understanding of the people behind the data. That means investing in patient journey work that is rigorous, emotionally intelligent, and designed to surface lived reality -- not just stated behavior.
Empathy is not peripheral to trust. It is one of its core ingredients. And trust remains one of the most valuable assets any healthcare company can build.
As our industry moves quickly to adopt AI, the organizations that will stand out are not merely those that automate the fastest. They will be the ones that preserve -- and operationalize -- the humanity at the center of healthcare.
That work starts by listening better.
And in many cases, it starts with a better patient journey.
