Data, AI, & Machine Learning

Health care companies are using digital tools to put doctors’ focus back on patients.

To fully benefit from supply chain analytics, companies need to be able to act on insights quickly.

AI offers a potential solution to the problem of training employees how to find and use data.

Logistics partners use supply chain intelligence to meet the demands of the high-tech industry.

Tough new EU data security laws mean that consumers’ data is about to become more valuable.

Though customer service is a key analytics focus, it offers potential for security improvements too.

How is business actually using artificial intelligence?

It pays to ask yourself whether your job is common and repetitive enough to be done by a machine.

In this webinar, MIT SMR authors discuss steps supply chain executives can take to make supply chain analytics a transformational and competitive resource in their organizations.

A new phase of technology-enhanced work is upon us.

The value of enterprise-level AI depends on what an organization’s people do with it.

In the first half of 2017, these MIT SMR articles attracted the most readers.

A panel at the 2017 MIT CIO Symposium discusses how artificial intelligence will transform how we work.

A featured excerpt from The Mathematical Corporation by Josh Sullivan and Angela Zutavern.

For companies relying on algorithms in daily transactions, transparency is a difficult issue.

What to do when company data is breached.

Managers already struggle to put data to intelligent use; AI may add to their difficulty.

The challenges of leading companies through the AI revolution were examined in a recent symposium.

Large amounts of data don’t inherently remove sampling bias; in fact, they may make it worse.

Some companies are using assessment tools to help identify employees with leadership potential.