AI in Practice: Where Automation Ends and Human Judgment Begins
Editor’s note: The following has been edited slightly for clarity from a live interview at the 2026 IQVIA Digital Innovation Summit using AI‑enabled tools and human oversight - because the best intelligence is collaborative co-intelligence.
Introduction
AI is no longer a future promise in life sciences marketing; it is actively reshaping how brands identify audiences, accelerate activation and personalize engagement at scale.
But leadership is not being claimed by those who automate the fastest. The organizations pulling ahead understand that AI’s real value lies not in replacing human judgment but in raising the bar for governance, accountability and decision‑making. When applied with discipline, AI becomes a force multiplier, pairing speed with discernment, personalization with empathy, and automation with trust. Done poorly, it simply amplifies noise.
In a recent discussion titled “Efficiency at Scale, Ingenuity at Risk?” Marc Minassian, head of Media & Innovation at Genentech, and Kristen Tappan, EVP, client leader at CMI Media Group, examined how modern marketers can harness AI’s efficiency without sacrificing ingenuity - and why co‑intelligence is shaping the future of healthcare communications.
Where AI is creating value today
A pattern is emerging across life sciences: AI is most powerful when it expands what teams can do, not when it attempts to replace strategy or expertise. The question is no longer whether AI works, but where it is already delivering meaningful change. While AI can accelerate performance, humans must remain responsible for defining success and setting objectives.
Often described as co‑intelligence or “human in the loop,” this combination of AI with domain expertise is where many organizations are seeing early traction. Yet a persistent misconception is that simply having a human involved constitutes sufficient governance. Presence alone is not the differentiator - defined and defensible ownership is. When models optimize toward the wrong signal or recommend a less than ideal “next best action,” teams must have the authority and confidence to intervene.
Kristen Tappan, CMI Media Group, started off the conversation focused on the need for clear governance:
“If you disagree with your AI, who’s the decision maker?”
Marc Minassian, Genentech, shared a concrete example of audience expansion gone sideways:
“When we launched AI audience expansion, we found really strong response, primarily from an audience that was age 65+. The signal looked strong until intent was examined by the team, and the decision to correct course was unambiguous: we found their post‑click intent was not as high as the people who were in our target demo. So, we made the call. The human made the final decision.”
The takeaway? AI can surface opportunities, but humans must own outcomes.
The skills that appreciate in an AI world
As AI lowers barriers to execution, expectations for expertise rise. Automation does not eliminate skill; it elevates the value of lived experience, initiative, and judgment applied at the right moment.
When the conversation turned to whether AI strengthens specialists or democratizes capability, Marc raised a thought starter:
“For creative and media specialists- do you think that AI will become ‘tools of their craft’ … or do you think AI will truly expand the boundaries for people who are not creative or media specialists?”
Kristen noted that the answer depends on organizational guardrails and internal skill sets but we need to be candid about examining the tradeoffs:
“We cannot keep up as humans without the technology... (but) AI does not have lived experience.”
What rises in value, she argues, is not just creativity but initiative:
“The folks that took the initiative to just play (with AI tools) and said, ‘I have this repetitive task that I want to do less of’ … these were great ideas. That skill of knowing ‘How To (with) Agentic AI’ is going to be the skill that hopefully everybody in the room is starting to dabble in and teach yourself.”
It is important to remember that AI rewards those who engage with it actively, not passively. As execution becomes easier, the organizations that benefit most from AI will be those who build the skills, confidence and accountability required to work alongside them with intention.
Personalization, empathy and the lines AI can’t cross
Personalization is often positioned as an unqualified good, but effective personalization demands discipline. As targeting becomes more precise, responsibility increases. Particularly in healthcare, even well‑intentioned personalization can feel cold, calculated, or intrusive without the right context.
Kristen probed the tension between efficiency and empathy:
“How does (AI integration) affect the way you think about good personalization versus efficient personalization? And are you more protective of the human side because of that?”
Marc grounded his response in patient experience:
“It always comes back to that in every conversation we have: How will the patient receive this?”
These concerns point to a broader boundary AI should never cross alone. While automation can scale execution, humans must remain accountable for meaning, sensitivity, and differentiation.
Some decisions simply cannot be delegated, as Marc questioned directly:
“Are there parts of a marketing engine or a campaign that you think should never be produced or managed solely by an AI?”
Kristen’s response underscores what AI fundamentally lacks:
“AI doesn’t understand cultural sensitivity. It doesn’t understand nuance … It does not have intuition that people have.”
Progress is not defined by how far AI can go but by where humans choose to lead.
Closing thoughts: Elevation over efficiency
The conversation between Kristen and Marc emphasized that the real promise of AI in healthcare marketing is not speed alone but the ability to apply judgment and discernment at scale - both prerequisites for lasting success. As automation accelerates execution, the responsibility to define meaning, context, and consequence only grows.
The organizations that will lead are those that use AI to elevate human decision-making with clearly established governance guiding on when to push forward, when to pause, and when restraint is the most responsible choice. In a category like healthcare, where trust and impact are inseparable, progress will be defined by deliberate AI applications and clear commitments to accountability for what’s best for patients and providers.
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