From product leadership and user adoption to continuous iteration and scaling AI across a rapidly growing healthcare business, Tina shares practical lessons that apply far beyond healthcare.
For Local Infusion, AI was never the objective: it was the enabler.
Instead of searching for isolated use cases or deploying off-the-shelf AI solutions, the team worked backwards from the patient journey. Every workflow, every handoff, and every operational bottleneck was mapped before AI entered the conversation. That foundation made it possible to build solutions that improved care while fitting naturally into employees' day-to-day work.
Many organizations approach AI one tool at a time.
Tina explains why that mindset creates fragmented experiences and disconnected systems. Instead, Local Infusion focused on creating an AI-first operating model where data, workflows, and decision-making were designed to support automation from the start. AI became part of how the business operates; not another application employees had to learn.
Introducing new technology is rarely the hardest part of transformation.
The challenge is earning trust.
Rather than asking employees to embrace AI, Local Infusion focused on eliminating the repetitive work that prevented clinicians and operational teams from spending time with patients. By solving real frustrations first, AI became something employees wanted to use rather than something they were expected to accept.
One of the biggest misconceptions about AI is that it replaces people.
Tina argues the opposite.
When administrative work is automated and information becomes easier to access, clinicians gain more time to focus on conversations, patient care, and the moments where human judgment matters most. In that sense, AI isn't replacing the human experience, but creating more space for it.
No amount of product discovery can predict exactly how people will use a new tool.
Once AI is in the hands of users, new workflows emerge, unexpected use cases appear, and valuable feedback begins to shape the next iteration. Tina shares how continuous testing and rapid iteration have become central to Local Infusion's product strategy, allowing the organization to evolve alongside both its users and the technology itself.
As AI accelerates software development, the bottleneck has shifted.
Building features is faster than ever. The harder challenge is understanding customers, designing meaningful experiences, and identifying the problems worth solving.
For Tina, that's where product leadership creates the greatest value, and where organizations will increasingly differentiate themselves as AI becomes more accessible.
Stay tuned for more conversations with technology leaders building AI-native organizations, rethinking software delivery, and turning emerging technologies into measurable business outcomes on CTO2CTO.