For organizations to realize the potential value of AI, according to McKinsey, their AI strategy must align with their corporate strategy. They need a “clear data strategy that supports and enables AI,” and they must invest in staff and technical training to ensure they have the skills to implement AI at scale.

I keep those imperatives in mind when I work with business and IT leaders who wonder how AI might help their organizations. My advice to them: To get the most out of the technology — to make AI work for you — it pays to take a phased approach to implementation.

When it comes to data analytics, there is a lot to be learned from what higher education institutions are doing with this technology. Schools are facing constant financial and competitive pressure — not unlike most businesses. They need to retain their customers, the students. This can be difficult because of competition from online educational options…

Creating a solid use case for data is like cooking a great meal. You need the correct ingredients, or data. You also have to take special needs into consideration (is anyone allergic to any ingredients? is the data sensitive, subject to regulation?). With both food and data, you want to know where it’s sourced (is…

Twenty years ago, investors and analysts asked businesses, “What’s your web strategy?” Fifteen years ago, it was, “What’s your mobile strategy?” Today, it’s, “What’s your AI strategy?” Artificial intelligence gives businesses powerful new ways to get deeper insights into customer experiences, needs, wants, habits, risks and more. Yet as with the web and mobile, recognizing…

A modern vehicle processes an estimated 25 gigabytes of data each hour. Much of that is for internal operations, such as navigation and continuous optimization of the drivetrain. But an increasing amount of data involves driving conditions, such as hard braking. Today, fleet owners and insurance companies use that data internally to detect unsafe driving…

Retailers are practically swimming in data. No matter whether a retailer is all-online or runs a brick-and-mortar store — or whether it’s a tech leader or laggard — virtually everyone handles a wide variety of data: inventory information, customer payment data, loyalty programs that incorporate buying histories, employee payroll data and countless other sources of…