The Track
A Section Blog
The hidden reasons you’re not getting AI ROI
Where's the money going to be made in AI?
Not every AI investor will make their money back. In this post, we dig into the AI business models that will work, and those that will be the next Pets.com.
10 lessons from running a startup in 2023
This was a hard year for Section, but we’ve come out of it fitter and stronger. Here are 10 lessons that I’ve learned about running a startup – hoping they provide some inspiration to you.
How to prioritize AI projects
If your company is all-in on AI like Section, you might’ve spent the last few weeks coming up with exciting AI projects to tackle in the new year. After the fun brainstorming work comes the less glamorous step of figuring out what your organization actually has the time and budget to execute. We're sharing a simple risk-reward framework to prioritize your AI projects.
Quiz: How should your business be using AI?
You know your business should be using AI in some way. But does that mean using it to generate a few headline ideas, or introducing a whole new AI product? The answer depends on the state of your business.
Take our quiz to determine how to best use AI for your unique needs.
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.
How to find AI workflows that actually translate to ROI
AI is pointing out a big point of weakness in a lot of organizations: too few can actually name the value-generating processes that drive revenue. So Machine & Partners’ Ed Ortega is giving you his 5 step framework for doing just that.
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.
