The Track
A Section Blog

The hidden reasons you’re not getting AI ROI

Squishy vs. hard ROI: Why leaders need both
One of the hardest parts of AI ROI is figuring out how to report qualitative wins to execs who want quantitative reports. At our AI:ROI Conference, Michael Domanic shared the framework for approaching these two disparate kinds of ROI.

AI Agents Explained: The clear, no-hype definition
“Agents” have become one of the biggest hyped and most misused terms in AI. So here’s the real definition from someone who builds AI solutions for a living.

There’s plenty of AI ROI - if you’re willing to work for it
A theme emerged in the chat of this year's AI:ROI Conference: 11 experts shared their value-adding AI strategies but people were just looking for magic formulas. Here were the biggest insights we think they overlooked.

Is AI good enough to lay off your engineers?
Are AI coding tools good enough to replace humans? Here’s the verdict from a founder who had to make that choice.

What happens when 1M people are really good at using AI?
This week we made our AI coach ProfAI free for consumers to use, to build relevant, foundational AI skills. Our CEO Greg is taking over the newsletter this week to tell you why.

Most people are terrible at using AI [new data]
ICYMI, we released our latest report on the state of AI proficiency in the workforce this week. Greg is breaking down the key findings, and what they mean for you as an individual or a leader.

How the Royal Family’s AI-powered mental health agent overcame privacy concerns
Most orgs feel unready for the challenges that Gen AI brings to risk management. Yet many AI applications will have to navigate the line between user value and user privacy. So we sat down with specialist, Brian Kolodny, to understand how he traversed matters of privacy when building a mental health bot for the Royal Family’s foundation.

Our Guide to Building Enterprise AI Applications
Every company needs to be thinking about where AI slots into their product or service, but all the noise and hype makes it hard to determine what a valuable vs. novel use case looks like. Machine & Partners’ Ed Ortega is sharing 2 frameworks to narrow down your laundry list of AI ideas.




