This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.
Artificial intelligence - or AI - is one of today's most hyped terms. So, I'm going to try to clear up some of the confusion, separate the myths from reality and provide a few recommendations on adopting AI in the financial services industry.
To start with, AI really is a big deal. The Harvard Business Review calls it, "the most important general-purpose technology of our era." According to some pundits, AI could contribute up to US$15.7 trillion to the global economy in 2030 - or more than the current output of China and India combined."
Many companies have seen the opportunity and the investments are flowing in. According to McKinsey1, tech giants have already invested 20-30 billion dollars in AI technology. As a result, the big companies are developing their proprietary AI technology: IBM has its "Watson," Google has "Deep Mind" and Hitachi has "H".
So, what is AI? The Merriam-Webster dictionary defines AI as "a branch of computer science dealing with the simulation of intelligent behaviour in computers; the capability of a machine to imitate intelligent human behaviour." That's a very broad definition and a variety of computer systems would qualify. For example, many of us carry multiple AI systems, such as the Siri smart assistant in our smart phones or spam filtering engines in our e-mail apps.
There is another important term - Machine Learning (ML). In fact, this branch of AI has recently become a scientific discipline on its own, giving a machine the ability to learn and improve its performance, without the need for any human interaction.
Riding the third wave
Although AI may seem to be fairly new, it has actually been around in one form or another for at least 60 years. We are now riding the third wave of AI, and there are two main factors that make this wave so important. The first is a significant increase in computational power and a corresponding decrease in costs. The second is the massive pool of data that the Internet and mobility has made available, and which can be used to train AI models.
However, despite all the hype, according to IDC2, only one third of companies are planning to use machine learning or other AI technologies inside their enterprises. The reasons for their reluctance to embrace this set of techniques? Lack of familiarity and a talent gap.
In Hollywood movies, artificial Intelligence means computers or human-looking robots that can learn on their own and make creative decisions in new situations. That's still science fiction. So, what can AI really do?
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