View My Leadership Philosophy →
Abbie Pratt presenting her leadership framework for translating emerging technology into responsible decisions through clarity, execution, connection and responsible leadership.
Profile portrait of Abbie Pratt holding a coffee cup, with a quote explaining that AI policy communicates organizational beliefs while AI governance directs real-world decision-making.

Responsible AI Innovation

I think about responsible innovation in fairly practical terms. Organizations need room to experiment with AI and new technology, but they also need to understand what they are introducing, where the risks are and who is responsible for the decisions being made.

I’ve spent much of my career introducing new technology into large organizations. Moving quickly matters, but so does understanding what changes when that technology becomes part of the way people actually work.

With AI, that includes how decisions are made, what needs oversight, where accountability sits and how organizations respond when the technology or its use changes.

For AI, my work involves helping organizations balance experimentation with appropriate governance, clear ownership and an understanding of the risks involved.

What I’m Exploring in Healthcare AI →

HOW I LEAD

MY LEADERSHIP FRAMEWORK

Four principles guide how I translate emerging technology into responsible decisions, trusted adoption, and measurable impact.

01

Executive Decision Making

Leadership is about making decisions when information is incomplete and consequences matter.

02

Human-Centered AI.

AI changes work.
Leaders change organizations.

03

Governance That Enables

Good governance should remove uncertainty, not create bureaucracy.

04

Responsible Innovation

Innovation creates value only when organizations can trust what they build.

Health AI Articles
The role of AI in patient care - Compass from Harvard Med School
The role of AI in patient care - Compass from Harvard Med School

I found this interesting for my research. A new AI model from Harvard Medical School researchers is showing promise in predicting which cancer patients may respond to immunotherapy. The research also raises a bigger question for healthcare AI: when a model moves closer to influencing patient care, what evidence should we require before we are prepared to act onA new AI model from Harvard Medical School researchers is showing promise in predicting which cancer patients may respond to immunotherapy. The research also raises a bigger question for healthcare AI: when a model moves closer to influencing patient care, what evidence should we require before we are prepared to act on it?

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Thinking About Clinical Use of AI
Thinking About Clinical Use of AI

Recent work from Harvard Medical School researchers got me thinking about what happens as promising AI research moves closer to patient care. I look at some of the questions around evidence, clinical use and who is responsible for making those decisions.

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Ownership in Healthcare AI Governance
Ownership in Healthcare AI Governance

I don't think we need to have all of those answers while research is still developing. But as AI creates increasingly sophisticated ways of understanding disease and supporting treatment decisions, these are questions healthcare organizations will eventually have to answer.

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Featured Articles

A selection of recent writing exploring practical leadership challenges in enterprise AI.

What I’m Exploring in AI Governance →