Simple, complete summary of Episode #323 (Jordan Morrow)

Big idea
Everyone should learn basic data and AI skills so they can make better decisions at work and in life. Data literacy means reading, working with, analyzing, and talking about data. AI literacy is the same idea but focused on using AI tools well (especially writing good prompts and checking AI answers).

Why this matters
Teaching people skills isn’t enough by itself — organizations must change how people behave and use data. That needs clear goals, good communication, and leaders who support it.

What to teach people

• Don’t try to make everyone a data scientist; teach role-specific skills that fit people’s jobs.
• For AI, teach prompting, how to check results, and how to make decisions using AI outputs.

How to run training programs

• Start small and practical: pick useful problems and show clear value.
• Make learning short and steady: 1–4 hours a week, or 15–30 minutes daily. Leaders should allow time for this.

How to measure success

• Don’t just do proof-of-concept projects; show proof of value (real time or money saved).
• Use new measures like “velocity to insight” (how much faster you get useful ideas with AI). Also check actual effectiveness and reduced mental load on employees.

How AI can help everyday work

• Use AI to speed up reports, prepare for meetings, draft hard emails, and suggest strategies in client reviews. But always check AI outputs.

Culture and change tips

• Make data/AI part of onboarding and meetings so it becomes normal.
• Communicate clearly, don’t overwhelm people, and show how data helps — it doesn’t replace experience or intuition.

Risks and how to avoid them

• Overusing AI can weaken thinking skills. Keep practicing thinking: read, journal, and spend small daily time improving skills.

Examples given

• Replacing a slow Excel review process with a trained AI tool that gives instant client insights for meetings.
• Using AI to write kind but firm messages for difficult conversations (e.g., a teacher emailing a student).

People to follow

• Sadie St. Lawrence (AI consciousness & ethics) and Jepson Taylor (AI research/startup).