The Track
A Section Blog
Yes, you will lose your job to AI
How should your business use generative AI?
Learn how to implement generative AI at your business, depending on your customer readiness, stakeholder buy-in, and data access.
How Squishmallows became the top-selling toy of 2022
What do Lady Gaga, Warren Buffett, and your eight-year-old nephew have in common? They all collect Squishmallows.
But if you’re not a collector, you might be scratching your head and thinking, “Why are these run-of-the-mill stuffed animals so popular?”
In this post, we dive into how the viral brand was able to break $100M in sales with a great marketing strategy (using lessons from Scott Galloway, Marcus Collins, and more).
5 insights on learning from Section's Annual Outcomes Report
We surveyed your employees on the blockers that stand in the way of learning. Read our post to learn how to engage them in learning and prove the ROI of your programs.
Why did HBO Max rebrand to Max? 4 insights
The internet responded to the HBO Max rebrand with an overwhelming, "Why?" So we dug in to find out the strategy behind their confusing move.
How to build a custom GPT
Follow these step-by-step instructions to build a custom GPT model that completes specific tasks for you.
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.
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.
