Mastermind Session with Corinne Stroum

Anyone Can Build It Now. Owning It Is the Hard Part.

AI has dramatically reduced the effort needed to build software. Teams can now create applications, copilots, and AI agents in hours instead of months. But going live is only the beginning. Sustained value depends on clear ownership, governance, and operational discipline to manage AI systems at scale.

Building is easy. Ownership is difficult

AI development is no longer the biggest hurdle. Every solution needs an owner responsible for monitoring performance, handling failures, improving the system, and deciding when to retire it. Without ownership, successful pilots can become operational risks.

Solve the problem, not every request

Multiple requests for similar AI tools often point to one shared business problem. Instead of building separate solutions, identify the underlying need and create a scalable approach that serves multiple teams.

Success is measured by business outcomes

Usage alone does not prove value. Strong AI solutions reduce friction, streamline workflows, and help people work faster. Measure impact through outcomes such as time saved, operational efficiency, and improved results, not just adoption metrics.

Governance should help teams move faster

Effective governance should enable innovation, not slow it down. Clear standards, reusable templates, and implementation playbooks help teams address risks early and make secure, compliant adoption easier at scale.

Explore an exclusive conversation with Corinne Stroum on why AI succeeds when it solves the real problem, is measured against outcomes that matter, and is stewarded long after anyone can build it.

What This Session Unpacks

Healthcare organizations are racing to adopt AI. But when anyone can build a tool in minutes, the real challenge shifts from creation to accountability, governance, and lifecycle ownership.

In this session, we’ll explore:

Why a stated need is often a symptom, and how to solve the real problem instead of the requested one
Why repeat usage of a productivity tool can signal friction rather than success
How to quantify AI's impact against the business's metrics instead of the vibe that it feels useful
What changes when consumers arrive AI-prepared and the authority of the expert is eroding
Why application lifecycle management and stewardship matter more than the ability to build
How AI governance works best as an enablement function that finds the one-dollar problem before it becomes the hundred-dollar one
Why the future of AI in healthcare may be less about screens and more about ubiquity, physical AI, and aging in place

Who This Is For

As AI becomes easier to build, the real challenge is making it work reliably in production. This Mastermind session explores what it takes to move beyond successful pilots and create AI solutions that are trusted, governed, and built to last. The discussion focuses on practical lessons leaders can apply as AI adoption accelerates across healthcare.

Built for healthcare decision-makers: This session is designed for healthcare IT and product leaders, CIOs, digital transformation teams, innovation leaders, health plan operations executives, and anyone responsible for implementing AI safely and at scale.

Go beyond implementation: Deploying AI is only the first step. Learn why long-term success depends on clear ownership, strong governance, and operational practices that keep AI systems reliable, compliant, and valuable long after they go live.

A conversation grounded in real experience: Rather than focusing on theory, this discussion explores practical challenges in AI adoption, product thinking, governance, and human-centered design. You’ll hear what it takes to build AI solutions that people trust, teams can maintain, and organizations can confidently scale.

Want to participate in a future Mastermind session? Share your details below, and our team will be in touch with you.