Ep. 06 - Why Every AI Strategy Starts With Data ft Dawn Choo

Every AI system is only as good as the data underneath it. Yet most companies are racing ahead with AI without asking what is safe to give it or how they will know it is working.

In episode 06 of RE:WIRE, Amit Patel sits down with Dawn Choo, data scientist, educator and co-founder of Interview Master. Dawn started at Bank of America, built reporting at Amazon and worked as a data scientist at Meta before building an audience of more than 200,000 on LinkedIn around data and AI careers.

Together they get into why data literacy matters as much as AI literacy, how leaders make room for curiosity and how to tell whether AI is really paying off.

In this episode, Dawn explains:

• Data is never one and done: Why data structures keep changing and need constant monitoring.

• The roles behind the foundation: What data engineers, analytics engineers and data scientists each bring.

• Data literacy for business experts: Why you start with the people using the data, not the pipelines.

• Learning time as strategy: How the best data leaders block out time for their teams to learn.

• Measuring AI's real return: Why token usage is the worst way to measure ROI.

00:00 Intro

01:42 How Dawn got into data

03:30 The biggest misconceptions about data

05:24 Modernising data in big banks

06:35 The roles behind a data foundation

11:19 Data literacy for business experts

15:58 Are data roles melting together?

19:24 Is the org chart flattening?

22:06 When leaders don't understand data

24:47 Giving teams time to learn

27:43 How leaders foster curiosity

31:38 Treat AI work as experiments

34:01 AI agents and guardrails

36:51 Managing tokens and model costs

38:27 Is AI delivering real ROI?

41:37 Token usage is the wrong metric

Find Dawn:

Website: https://www.interviewmaster.ai

Newsletter: https://askdatadawn.substack.com

LinkedIn: https://www.linkedin.com/in/data-dawn/

Hosted by Amit Patel, Founder, Experience Haus

Find Amit: https://amitpatel.ca