AI Workflow Enablement
1. The Problem Space
Cross-functional teams across Market Access, Medical Content, and Strategic Planning were expending significant hours on manual, fragmented workflows. Tasks such as simplifying clinical language, synthesizing payer landscape inputs, and extracting insights from raw transcripts were slow to execute and inconsistent across teams.
Simultaneously, the agency faced a critical compliance inflection point. Teams were eager to adopt generative AI to solve these bottlenecks, but unstructured, "rogue" usage of public LLMs posed severe regulatory and data privacy risks in healthcare marketing. The challenge wasn't a lack of AI capabilities; it was a lack of governed, workflow-specific AI that could scale securely across the enterprise without forcing massive behavioral changes.
2. My Role
I led the agency's AI product strategy, transitioning our operations from fragmented, unsecured generative AI experimentation to a governed, enterprise-ready portfolio of over 20 proprietary workflow applications. I served as the bridge between executive compliance constraints and the tactical needs of our cross-functional delivery teams.
3. The Approach
My product thesis was clear: The opportunity was not to build isolated AI chatbots, but to create a system of AI-enabled workflows that reduced friction across recurring tasks. If teams were given structured, governed tools embedded into real operating processes, adoption would increase while risk dropped to zero.
Health Literacy Editor
An AI-powered editor strictly grounded in NIH and HHS guidance that converts complex clinical language into plain language. Crucially, it was engineered to automatically explain every revision it made, providing medical reviewers with transparent, auditable logic.
Market Access Tactical Planner
A planning tool that ingests brand strategy, payer landscape, and market trend documentation to generate structured tactical recommendations. It eliminated the "blank page" problem, transforming fragmented documentation into decision-ready outputs.
Insights & Research Finder
An orchestration tool that processes KOL interviews, transcripts, and audio to identify major themes and surface direct quotes. Built to help teams move faster from raw qualitative research to actionable, statistically significant insights.
Veeva Multichannel Transformation
An automation pipeline that seamlessly translated multichannel loader files between agency and client environments by transforming key metadata and formatting requirements—eliminating human error from the migration process.
4. Outcomes & Impact
- Enterprise Scale: Designed, governed, and deployed a proprietary portfolio of 20+ AI-enabled tools across content, strategy, insights, and operations.
- High-Friction Adoption: Achieved ~75% adoption across core content teams for the Health Literacy Editor, driving a 25–50% reduction in manual manuscript drafting and simplification time.
- Process Velocity: Reduced digital publishing and migration timelines from approximately two days to one for complex Veeva CLM and Engage workflows.
- Behavioral Shift: Successfully normalized AI as a secure, repeatable operating layer, entirely eliminating the reliance on non-compliant, public AI experimentation.
5. What I'd Do Differently
The initial deployment prioritized speed-to-value by standing up individual tools tailored to specific team pain points. An updated architecture would require a centralized, shared orchestration layer. Formalizing common logic, standardizing grounding methods (RAG), and unifying output formats across all tools would vastly improve maintainability and accelerate future module launches.
Furthermore, I would instrument deeper usage telemetry. While we had qualitative feedback on time savings, hardcoding workflow analytics directly into the tool layer would allow leadership to quantify the exact operational leverage and ROI of every prompt execution.