Applied AI Governance

Responsible AI,
put into practice.

A resource for understanding what AI governance looks like not just in policy documents and frameworks, but in the day-to-day work of real organizations building and deploying AI.

What is it? About

The Approach

AI Governance: applied.

Like applied science or applied research, Applied AI Governance is about closing the gap between principle and practice. Most organizations already know responsible AI matters. The harder question is how to make it real (inside the teams, tools, and processes that actually ship AI products).

Research and regulation are foundational. Applied AI governance is about translating them into real-world practices that actually take hold inside organizations.

The Foundation

Academic research & whitepapers
Regulatory frameworks & policy
Ethical principles & guidelines
Industry standards & oversight

          Applied AI Governance
          Translating research into team practices
Embedding regulation into real workflows
Cross-functional stakeholder alignment
Governance that scales with the product

        

About

I've built this from the inside.

10+ Years working with data, AI, and policy

I'm Amy Smith, a data scientist turned Technical Program Manager with a knack for turning ambitious, ambiguous problems into structured, scalable programs. My career has spanned GIS analysis, data science, policy research, and most recently Responsible AI.

At Intuit, I served as a Staff TPM for Responsible AI, where I rebuilt the GenAI use case review process, cut LLM onboarding time by 66%, and led a portfolio of responsible AI initiatives across legal, security, data science, and product teams. I represented Intuit at Partnership on AI workshops and forums, bringing an applied, practitioner's perspective to industry-wide conversations.

Most recently, at Plaid, I serve as Senior Staff TPM driving the company's AI Governance strategy across Engineering, Product, Legal, Security, Compliance, and GTM. My work focuses on machine learning models and AI-powered product features, with a particular focus on responsible, ethical, and transparent AI adoption in FinTech.

This site is a space to share what I've learned from building governance inside fast-moving tech organizations: what breaks down, what gets buy-in, and what actually sticks.

Connect on LinkedIn

Speaking and Writing

Find me online

Harvard Data Science · Guest Talk

Career trajectories in data science & AI governance

A talk on navigating a nonlinear data career (from GIS to data science to Responsible AI program management) and what practitioners can learn from stepping outside their original domain.

Watch on YouTube

Medium · Essay

From GIS to Data Science to Technical Program Management

On how stepping outside your comfort zone repeatedly (not just once) is what creates genuinely unusual careers. A reflection on identity, skills, and the kind of growth that only happens when you say yes to something you're not sure you're ready for.

Read on Medium

Responsible AI, put into practice.