The Fortune 500 data company onboards AI and machine learning capabilities to make hay with unstructured datasets.
AI, machine learning, and other new technology must replace subjective rules of thumb and one-size-fits-all programs for business transformation to succeed.
While AI is often overhyped, there are a number of practical applications that are available to finance chiefs.
In making software-buying decisions, finance organizations are too focused on gaining efficiencies and not enough on future digital needs, says Gartner.
No matter how much data is fed to machine learning and predictive analytics tools, the key is deciding which outputs are useful and how to act on them.
Research shows that finance departments are deploying the latest cutting-edge tools at a startlingly increasing pace.
A soon-coming world that's almost entirely digitized and connected will expose companies to vast new cybersecurity risks.
Intelligent automation boosts both day-to-day finance functions and the quality of finance's strategic insight, says Willis Towers Watson's Michael Burwell.
Machine learning and AI solutions are difficult to deploy, often overhyped, and may have little bottom-line impact: Gartner.
The $1.4 billion deal positions BlackBerry to capitalize on the demand for securing autonomous vehicles and IoT devices from cyber attacks.
Key executives at early adopters of cognitive technologies see a short time-window for honing their strategies and skills.
With automation having replaced many low-level workers, the white-collared set is now worrying about their own fate. But should they be?
