Machine learning

The global value of insurance premiums underwritten by AI have reached an estimated $1.3 billion this year.

The issue here isn’t the source of the data; it’s that somewhere along the way, users’ functional and emotional goals aren’t being met.

Almost one-third of financial-services jobs could be displaced by automation by the mid-2030s, according to PwC.

IT and data leaders are constantly challenged to keep up with new trends in emerging and disruptive technologies, and to determine how each can best aid the organization.

Reinsurer developed AI, big-data-driven product in its internal innovation lab for its insurer clients.

Cigna Ventures is leading a $23 million investment in GNS Healthcare, a specialized artificial intelligence company.

The improvements insurers are seeking in terms of data-driven decision making can’t be denied.

CEO hopes the simplicity of the digital bank will help attract younger customers to the 150-year-old Manulife brand.

Carriers need to reimagine the entire customer experience, creating a living feedback system for customers so that they can know where they are meeting expectations.

Job postings for AI workers increased by nearly 30 percent in the past 12 months, making these professionals among the most sought after.

Northside Hospital in Atlanta is adopting machine learning technology to enable the organization to predict when insurance companies will end payments.

It need not (in fact it should not) be an overly complex burden that adds controls and obstacles to getting things done, but a practical thing, designed to proactively manage the data that is important to your organization.

Atidot, Galaxy.AI, PHR Plus, Traffk and Zesty.ai are among the top innovators for intelligence-based technologies to improve accuracy and automate decisions, says a new Gartner report.

AI has the potential to make our lives safer and easier, if we train the systems to be inclusive and use them wisely.

To reap the full benefits of AI, there’s an entirely different type of AI we should be exploring that’s been largely ignored. It’s specialized (or augmented) intelligence systems.

Artificial intelligence is being hailed for its ability to improve internal processes and enhance customer experiences, but opportunities to use the technologies have been slow to take hold.

Here are some changes - attitudinal and operational - that organizations need to undertake today to get the most out of ML and AI in the near future.

Director of the former RiskBlock Alliance discusses name change and expanded digital focus including IoT, AI and analytics.

Two recent articles in highlight the simultaneous offer of promise and peril that AI brings. One article describes the meteoric rise of a start-up; the other the failure of another.

The National Institute of Standards and Technology is seeking industry input on ways to develop standards for artificial intelligence.