The top areas where insurers will spend new money are predictive modeling and link analysis/social network analysis.

This combination ensures accuracy over time and enables the ability to analyze information and provide it quickly.

Consumers report broad concerns about the fairness and acceptability of using computers for decision-making in situations with important, real-world consequences.

One of the most popular conferences for IT leaders is the MIT Sloan CIO Symposium. This year’s event will be all about data management, analytics, AI and disruptive technologies.

China's SenseTime's goal is to get AI in front of a swathe of industries and as many people as possible,

Insurers must decide which business problems they need to address first, which require more data, and how to operationalize models in their core production system.

Dogan Kaleli, leader of the program business, finds opportunities to pilot various emerging techs in his role and beyond.

The importance given to understanding and preventing bias and unfairness is evident in the mainstream artificial intelligence conferences.

A new report, as well as several other studies, confirm a frustrating problem: The AI hype is making it impossible to figure out how much businesses really need it and are using it.

The visionaries are leveraging the data that sits in the ecosystems around them—and are applying AI on top of the data to turn it into predictive insights.

For upstarts, these represent opportunities to disrupt the old guard; for established firms, these approaches can stave off new competitors.

One of the top data and analytics technology trends this year will be the ongoing growth of natural language processing and conversational analytics, according to research firm Gartner Inc.

Specialty insurance company's tech leader says managing technical debt is a challenge for carriers navigating a changing world.

Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the top trends that will drive advanced analytics adoption, says Gartner.

Single-tenant SaaS has the same long-term scaling problem as on-premise deployments: every client’s system running on a slightly different branch of the codebase.

As clever as artificial intelligence may seem, it does not duplicate the human brain, learn on its own or operate free from human bias.

Those organizations that haven't given thought to AI investments run the risk of quickly losing competitive advantage, consultancy says.

It’s no longer a question of if companies should use data; rather, the concern lies in how companies can effectively apply its insight.

Companies that have vast amounts of data can easily step into the space and start competing with insurers. Here's how to dodge the threat.

Wage growth is starting to accelerate, and CIOs could find themselves paying premiums for certain roles in high demand such as data science, AI, security and cloud technology.