Stu Willson sits down with Natalia Quintero, Head of Consulting at Every, to unpack how organizations move from “AI playtime” — experimenting with ChatGPT and off-the-shelf tools — to full-scale production adoption that transforms workflows. Natalia shares Every’s discovery-first process, where teams identify the right use cases, co-design internal tools, and deploy AI that people actually use. From private equity firms to media companies, she reveals how “AI curiosity” becomes measurable ROI when strategy meets execution.

Chapters:

00:00 – Intro & who Natalia helps (PE, hedge funds, media)
01:30 – What is Every? Media + product studio + consulting, all AI-first
02:20 – From playtime to production: the maturity shift in AI adoption
03:45 – Practitioners, not consultants: building from lived experience
05:10 – Discovery before build: mapping workflows and opportunity
07:40 – Common client profiles: “we built something” vs. “we tried, now what?”
09:05 – Avoiding the wrong builds: high-value, low-friction starting points
11:20 – Everyone’s an AI manager: iteration, quality, and human judgment
13:00 – What makes a good AI problem: repeatable, auditable, ROI-positive
16:10 – The “hire-an-intern” test to find high-value automation tasks
17:20 – Leadership’s role in driving adoption (the Walleye example)
21:30 – Case study: AI-assisted investment memos and faster diligence
25:00 – Tech stack: ChatGPT, Claude, and building on enterprise LLMs
27:30 – The AI Champions model: enabling functional ownership
30:00 – Training teams for the last 15% of AI quality and context
33:20 – First steps for new teams: start with pain, not prompts
35:00 – Don’t buy every shiny tool; master your LLM first
36:20 – Who should reach out to Every (ideal clients) & closing

📩 Subscribe for Weekly AI Insights & Case Studies:

https://just-curious-ai.beehiiv.com/?utm_source=home&utm_medium=video&utm_campaign=NATALIA_QUINTERO_INTERVIEW

‍