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4 Statistics About the Impact of AI That Will Astonish You

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AI is still, for most people, an abstract concept, despite the proliferation of AI applications that currently exist in the world and that people interact with on a near-daily basis. The aim of this piece is to demystify AI, and bring it from the realm of the theoretical into the everyday. This means looking beyond the current applications for AI, and examining what the future holds and the implications that AI has for the business world.

Statistic Number 1: By 2025, revenue from AI software is expected to reach almost $60 billion worldwide

Aditya Kaul
Aditya Kaul

Research firm Tractica estimates that the revenue generated by AI software, either directly or indirectly, will skyrocket from $1.4 billion in 2016 to $59.8 billion in 2025 as a result of the dramatic increase in the number of use cases in various industries. “Artificial intelligence has applications and use cases in almost every industry vertical and is considered the next technological shift,” says Tractica’s research director, Aditya Kaul, “similar to past shifts like the industrial revolution, the computer age, and the smartphone revolution.”

AI is already in use in some key industries: advertising, automotive, financial, and healthcare, to name a select few. The fact that AI has multiple applications, from predictive analytics to chatbots to automation, will hasten its adoption amongst the remaining holdouts.

Statistic Number 2: More than 1000 vendors use the term “AI” when describing themselves or their products

In the beginning of 2016, “AI” was not even in the top 100 search terms on Gartner’s website; by May 2017, it was the 7th most searched topic, a clear indicator of how quickly it became a subject of interest – and how little people seem to know about it. According to Gartner, this has led to a rise in what they call “AI washing”, which is similar to the practice of “greenwashing”, where companies label themselves as environmentally friendly for advertising or goodwill purposes.

The problem with this is twofold: Firstly, very few companies have the expertise necessary to vet these AI products or companies, which could result in failed AI investments and wasted money. Secondly, it could lead to a situation where companies are reluctant to invest in AI after one bad experience – which would in turn disadvantage them severely once AI adoption becomes the norm.

Statistic Number 3: China is building a $2.1 billion research campus in Beijing dedicated to developing AI

China is rapidly emerging as a big player in the AI space, due not only to the significant investments made by the government but also to the advances made by tech giants Baidu and Alibaba, among others. The Chinese government is also pouring billions of dollars into the promotion and development of AI startups within the country, which will potentially shake up the current AI status quo. The campus is one part of the Chinese government’s recently announced plan to transform the country into a world leader in AI by 2030, and to grow the AI industry to almost $150 billion.

It’s not only the government that’s looking to invest in AI; U.S.-based tech companies are also looking to expandtheir AI footprints in China. Google recently opened up a research center in Beijing, and companies such as Microsoft and Amazon are actively hiring AI engineers in the country. AI, in other words, is finally beginning to move out of its Silicon Valley bubble.

Statistic Number 4: The average salary at Google’s DeepMind, headquartered in the UK, is over $345,000 per person

This number comes courtesy of a recent New York Times piece which, among other fascinating insights, revealed that AI specialists can be paid anywhere between $300,000 to $500,000 a year – even if they’ve only had a few years of experience or recently completed their Ph.D. DeepMind recently expanded to 400 employees, which cost the company $138 million. Big shots within the industry can often command salaries and incentives in the hundreds of millions of dollars, which makes it incredibly difficult for smaller companies to get the talent they need in order to compete.

According to one estimate, there are fewer than 10,000 people around the world with the necessary skills to conduct serious AI research, which explains why large companies (Uber, Google, Facebook, etc.) have been competing aggressively amongst one another in order to attract the best and the brightest talent. It will take a while before the market corrects itself and salaries begin to approach a reasonable level; until then, if you’re looking to hire an AI expert, make sure you have a good amount of cash handy.

Taken together, these four statistics paint a larger, more complete picture of AI. It’s no longer just about what AI can do in the future; it’s about what AI can do – and is doing – as we speak.

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