The Track
A Section Blog
Is Deep Research worth $200 a month?
Why most organizations aren’t ready to deploy AI
In September, we re-ran our AI Proficiency Survey to over 5,000 knowledge workers across the US, UK, and Canada. Our biggest takeaway: The knowledge workforce is vastly unprepared for an AI-augmented future.
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.
How we used AI to improve course quality by 20%
One common misperception about AI is that it’s only good for making processes quicker. Education Product Lead, Kyra Atekwana, shared how it also improved our content quality by 20%.
How an agency is preparing for AI clients
AI has put a big question mark over the future of agencies. So we talked to David Freas, Managing Partner at Supermoon, about how he’s transforming his brand agency with AI agent teammates – and for AI agent clients.
AI can think now. What does that mean for you?
The next stage of LLMs is here: AI that “thinks,” or breaks down problems step-by-step like a human would. Here’s how we got here, and what it means for how you use AI.
3 drills to teach your team AI, using AI
L&D might be dragging their feet on training your team on AI (we’ve seen it firsthand). So, use AI itself as your team coach.
How to set an AI policy for your company
In this post, we'll cover the four parts to a strong AI policy – your stance on AI, operating norms, rules/guidelines, and real-life use cases.
