September 24, 2026
Artificial intelligence and synthetic data typically dominate market research discussions. Yet, a surprising tool is emerging as the industry’s most powerful resource — human empathy. That was one of the big takeaways at the recent Quirk’s Event in New York City, where market research and insight leaders gathered to discuss the industry’s future. The overarching consensus? As data collection becomes faster, deep human understanding will become the ultimate competitive edge.
From healthcare strategy to brand communications, speakers across sessions challenged organizations to rethink how they capture, analyze and act on consumer intelligence. The conference highlighted a fundamental shift away from static, project-based reporting to continuous, ethical, action-oriented insight ecosystems.
Carly Hochman and Alexa Stabile, both vice presidents of analytics at GCI Health, were on –the ground at the Quirk’s Event capturing insights. Here are their key takeaways and how communicators can put new strategies into action.
1. Move From Research Output to Decision Impact
A new industry priority emerged at the conference: organizational impact over research output. This means a shift from isolated research projects to instead create connected, always-on insight ecosystems that continuously inform decision-making. However, continuous data means little if insights are not effectively communicated. When continuous data collection is paired with compelling storytelling, research becomes a driver of high-confidence business decisions.
Put it into action:
Focus on Impact and Accountability: Frame every insight around the specific business action it should inform. Simultaneously, track how research directly influences strategy and business decisions to demonstrate value.
Scale Always-On Ecosystems: Match qualitative, quantitative and AI tools to specific business questions within a continuous tracking framework, leveraging human insight to filter noise and power a central knowledge base.
Package High-Impact Insights: Tailor delivery formats (swapping static slides for visual, interactive storytelling) to present high-conviction, actionable insights that empower swift and confident client decisions.
2. AI-Enabled Research Requires Human-Led Rigor
AI is expanding what research teams can do — accelerating synthesis, enabling richer qualitative data and generating insights at greater speed and scale. But speed and scale alone do not build executive confidence. As teams ask where AI belongs in the research workflow, researchers must define where it adds value and where human participation and judgment remain essential, particularly in interpretation, quality assurance, scientific rigor and health equity. Clear governance and transparency ensure that modern research is not only more efficient, but also credible and trusted.
Put it into action:
- Define the AI-Human Operating Model: Identify where AI can accelerate research, synthesis and analysis, and where human oversight is required for interpretation, contextualization, bias assessment, quality assurance and scientific rigor.
- Use AI To Scale Qualitative Depth: Deploy AI-moderated conversational tools to capture rich patient and HCP narratives at the speed and scale of quantitative research while preserving authentic human engagement where it is essential.
- Establish Guardrails for Equity and Trust: Define when real human participation is non-negotiable, particularly when researching diverse or underrepresented populations. Make AI’s role transparent and ensure outputs remain evidence-based, authentic and appropriately validated.
3. Deep Human Insight Is the New Competitive Advantage
As AI accelerates research, the differentiator is not collecting more data — it is uncovering deeper human understanding. Across multiple sessions, speakers challenged researchers to “see what people do, not just what they say,” emphasizing immersive research to uncover unmet needs rather than relying solely on stated preferences.
Put it into action:
- Design Research Around Human Behavior: Incorporate conversational questions, behavioral observation and qualitative techniques into research gathering to uncover the emotions, motivations and barriers driving patient and HCP decision-making.
- Bring Humanity Into Every Insight: Pair quantitative findings with authentic patient stories, quotes and experiences so that stakeholders understand not only what audiences think, but why they behave the way they do.
4. Uncover Expectations Before You Try To Exceed Them
Communicators often focus on solving an audience’s needs while overlooking their expectations (e.g., do they expect immediate help for an urgent issue; do they expect longer more complex treatment regimens). Without grounding strategy in what audiences anticipate, organizations risk delivering standard solutions that fail to resonate. While meeting expectations establishes basic trust, intentionally exceeding expectations delivers distinct value that sets a brand apart and creates meaningful engagement.
Put it into action:
- Audit Baseline Expectations: Before launching research or strategy, map out the existing baseline expectations of specific audiences. Once these are understood, shift the focus to key differentiators.
- Design Beyond Touchpoints: Identify specific, high-friction moments in the audience’s journey where exceeding standard expectations can turn a routine moment or interaction into a memorable, trust-building experience.
- Align Timelines with Urgency: Tailor the speed, format and depth of your communications to match the emotional urgency of the situation (e.g., immediate, bite-sized reassurance for acute moments versus comprehensive, long-term guidance for complex care decisions).
As AI continues to transform the research landscape, speed and scale alone are no longer enough to drive meaningful strategy. The ultimate competitive edge comes from pairing smart AI tools with human-led rigor and storytelling to ensure data builds trust and creates meaningful impact.