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.
When to use a specialized AI tool vs. an LLM
If you’re hitting the limits of your LLM because you need more data or niche training, you’re likely doing a lot of high-end knowledge work – and that’s where specialized AI tools come into play.
We tested two Deep Research tools. One was unusable.
Two LLMs have released Deep Research features without much of a splash. So if you’ve been wondering about them (and don’t want to pay the $200/month price tag), read on for our Chief of Staff’s take on ChatGPT vs. Gemini.
How to drive AI adoption at scale
If you missed Olya Taran’s session at The AI Strategy Summit, you missed one of the most practical frameworks of the day on one of the biggest problems leaders still face: Getting widespread AI adoption. We’re laying it out for you.
Your team doesn’t know what to use AI for
Change management is likely not the biggest bottleneck to your AI deployment anymore: Our latest AI Proficiency Report shows that people want to use it, but they can’t figure out what it should be used for.
