AI Agents and Workflow Optimization: Moving Healthcare Marketing From Idea to Impact
Healthcare marketing leaders explore practical AI use cases, data readiness, governance, and team structures required to move from experimentation to real operational value.
// By Therese Lockemy, MBA //
AI adoption in healthcare is no longer theoretical. But its maturity varies widely.
Some organizations use generative AI for productivity boosts and content drafts. Others work closely with IT and data teams to explore how AI agents can reduce friction across marketing, operations, and clinical workflows.
During AI in Healthcare Marketing Week, a virtual summit hosted by eHealthcare Strategy & Trends, panelists in the session “AI Agents and Workflow Optimization: From Idea to Impact,” discussed what is realistic today, what remains aspirational, and what health systems must put in place before agents can safely scale.
(left to right) Drew Marlatt, VP, data products and technology, BPD; Carrie Liken, strategic account executive, Snowflake
“Tasks that we’ve seen high potential for today are things that are repetitive, are data-driven, and are relatively limited in the number of edge cases they could have,” says Drew Marlatt, vice president of data products and technology at BPD.
That perspective set the tone for a grounded conversation. AI agents may someday autonomously book appointments and coordinate referrals, but today’s value lies in disciplined, focused use cases built on strong data foundations.
Here’s what the panelists recommend for teams trying to move from experimentation to impact.
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