Data
Ideas and insights about data from MIT Sloan.
How to boost your organization’s AI maturity level
By
New research highlights four areas leaders must address as they embed AI across their business.
How to succeed with industrial AI
By
Applying systems dynamics principles to industrial AI can ensure faster and more impactful business outcomes.
Buy, boost, or build? Choose your path to generative AI
By
Three approaches to acquiring generative AI solutions for your company, and how to choose the right one.
How to spot real value in AI — and avoid the snake oil
By
A new book aims to help business leaders separate real AI value from overhyped claims.
How to find the right business use cases for generative AI
By
Three steps to finding use cases for large language models: Break down workflows into tasks, consider all costs associated with automation, and launch pilots.
3 ways businesses can use large language models
By
Organizations have options when it comes to using or adapting off-the-shelf large language models to handle tasks or business use cases.
Machine learning and generative AI in 2025
By
While generative AI is widely accessible and useful, businesses need to know when to use other AI tools, like traditional machine learning.
How to make data indispensable to your organization
By
Effective data leadership starts with modernizing data technology — and calls for taking action, no matter how daunting.
This Fintech Sandbox co-founder champions free data for startups
By
Sarah Biller builds tech organizations ready for a “permissionless, frictionless, contactless” financial services sector.
What leaders should know about ’bring your own AI’
By
Companies need a plan for when employees use unapproved, publicly accessible generative artificial intelligence tools for work-related tasks.