Many aspects of artificial intelligence - the technique of training a machine to learn in a way which resembles a human being - may not be entirely new, but with the increasing availability of relatively cheap and flexible computing power the technology is becoming far more accessible. A number of tech companies and vendors are now offering APIs and frameworks that allow businesses to create their own intelligent services. Most businesses are at very early stages of adoption, however there are a growing number of examples where the smart technology is being used to optimise back office and consumer-facing systems and processes. Here are just some of the enterprise use cases around machine learning and AI that we are seeing...
We may be years away from the "AI-enabled Coworker," but the first implementations of machine-learning capabilities are finding their way into the everyday data-analysis tools used by businesses of all types. Cognitive assistance promises to reshape business processes, but only if app development and deployment tools are adapted to support machine learning.
We may be years away from the "AI-enabled Coworker," but the first implementations of machine-learning capabilities are finding their way into the everyday data-analysis tools used by businesses of all types. Cognitive assistance promises to reshape business processes, but only if app development and deployment tools are adapted to support machine learning. While it has become fashionable to hypeAIas the next game-changing technology promising to have an impact greater than either mobile or cloud, the reality is that machine learning will be a long time coming to everyday business analytics. As with any sea change, cognition is likely to sneak its way into applications and processes in drips and drops. It looks like 2017 could be the year many businesses get their first hands-on experience with cognitive-learning business apps.
Most understand the sage advice not to use technology for technology's sake. But in the age of wow-factor digital technologies like advanced analytics, machine learning and artificial intelligence (AI), it can be hard to resist. In this Q&A, Dragan Rakovich, DXC Technology's chief technology officer for analytics and a Distinguished Technologist, offers advice on how to focus the cool technology on valuable business outcomes. Q: Why are analytics such an important component of any digital transformation? A: Data analytics and machine learning help CIOs focus on increasing business value to their clients and delivering important business insights in the context of business processes.
Artificial intelligence is more than just hype now, the technology has already found its way into multiple areas of our lives. It's in the digital ads we view online every day. The technology is also increasingly powering our businesses. AI's ability to enable new ways of competing – including transforming business models, together with understanding possible risks and ethical issues – mean that embracing this new technology should be part of every future-facing CEO's job spec. Unfortunately, this isn't always the case, with many leaders still seeing it as something to be delegated to CTOs.