The Track
A Section Blog
The hidden reasons you’re not getting AI ROI
7 hard-won lessons from deploying AI at scale
This week, we got access to the motherlode of AI strategy advice at our AI Strategy Summit. Here are the 7 biggest takeaways every leader should read, then read again.
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.
Is AI the end of Saas?
Right now, I’m sure you can’t imagine life without your CRM or CMS. Edmundo Ortega bets you won’t be able to imagine life with one as AI continues to evolve.
AI could be the end of fast fashion
The retail industry is fraught with waste and sunk costs. Can AI fix that? Diarra Bousso is proof that it can.
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.
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’s progress may be holding your team back
On paper, the rapid release of new AI models and features looks like a win for knowledge workers. In reality, teams are drowning in AI overwhelm. Here’s how leaders can help them scale an ever-steeper learning curve.
