AI & Machine Learning

Until regulations catch up, AI-oriented companies must establish their own ethical frameworks.

Travel marketers need to recognize and embrace analytical sophistication.

What if, instead of perpetuating harmful biases, AI helped us overcome them?

Banks need a clear AI strategy to get digital transformation right.

Businesses that make and sell products that replicate human connection are serving a deep need, but they may also be changing social norms in ways that can’t be reversed.

Makers of AI applications should stop overpromising, be transparent, and consider certification.

One key strategy for AI success: retraining employees to have the skills your company will need.

Retail companies that neglect machine learning do so at their peril.

Prediction is appealing, but detection may be equally valuable for businesses.

Executives in the automotive sector believe that machine learning can help them achieve their marketing goals, but that doesn’t necessarily mean they invest in that ambition.

Consulting is vulnerable to technology and market forces that are disrupting services everywhere.

In the growth of artificial intelligence, technology is changing faster than society can keep up.

Viewing technology as a set of solutions misses opportunities to innovate in bigger, bolder ways.

Automation will affect jobs in four ways. The path jobs take depends on what kind of value they provide — and how.

Businesses are redefining how they create value, says MIT SMR’s 2018 Strategic Measurement study.

The future of AI looks much like the present, with machines helping humans to do their jobs better, not replacing them.

Leaders at the forefront of making organizations AI-driven have seven key attributes.

AI technology is not just an experiment.

A conversation with Airbnb’s Theresa Johnson highlights three tangible ways AI can help companies.

AI’s largest and most enduring contributions will be in non-technology sectors, and many of them will come from China.