Mobile technological innovations such as Siri, the iPhone’s digital assistant, Google’s latest Google Home product, or, Alexa, the smart home hub introduced by Amazon, are, to most people, the limits of today’s Artificial Intelligence (AI).

SwissCognitiveThese technologies have irrevocably transformed our day-to-day living. They are now entrenched in most aspects of our personal and professional lives. Electronic calendars prevent us from missing important appointments; fitness trackers can effortlessly measure our steps and workout goals; Skype translators can break down language barriers; and efforts to introduce self-driving vehicles incrementally are making waves in the automotive industry, changing the way we drive forever.

More than a hype

Today’s hype around AI is now stronger than ever. For the first time though, there is now capital backing up this hype. According to CB Insights, in 2016 global funding for AI start-ups was $5bn , nearly nine times higher than in 2012, with the business community collectively having woken up, smelt the coffee and paying attention. Having transcended merely being the talk of the town in the tech industry, today’s advances in artificial intelligence have gone beyond what many would have thought possible. For example, the algorithms of the world’s largest social media site, Facebook, can now track and tailor your entire internet browsing history, purchasing interests and commercial activity in less time than it takes a human being to blink, much to the delight of advertising agencies around the world.

Breaking down silos

The founding purpose of this technology and the potential it has to allow organisations around the world to integrate it into their businesses are now closer than ever before, propelling a multitude of sectors forwards. Ground-breaking innovations are already having a positive impact on both businesses’ bottom line and productivity levels. From manufacturers to white-collar workers, it is irreversibly changing business models as new services and ways of working continue to emerge. Machine-learning AI for example promises to automate many mundane, repetitive tasks, not necessarily promising to do them better, but faster and eventually, much, much cheaper. […]