There exists in Silicon Valley the hype (and hope) that artificial intelligence will create billions in wealth, save countless lives and transform business as usual. Despite the hyperbole used in discussions about AI, there is a very real wave of investment happening in the space.
Since 2011, nearly 140 companies working on artificial intelligence applications have been acquired, according to CB Insights. Nearly 40 of these acquisitions happened in 2016. Major tech giants like Microsoft, Apple and Salesforce are heavily involved in these efforts, thanks to their appetite for artificially intelligent products. But as CB Insights notes, Google is giving everyone else a run for their money.
Google has acquired 11 companies related to AI as of writing. Notably, one of those acquisitions was DeepMind Technologies, the brains behind the AI brain that beat a human champion at the board game Go in 2015. Thanks to successes like that, Google’s CEO Sundar Pichai is pursuing a strategy to position Google as the leader in an “AI-first” world.
Google’s products dominate the desktop and mobile worlds, helping marketers search, advertise and learn more about their audiences. As Google goes all-in on AI, the effect on digital marketers will be profound.
That’s why we think it’s valuable to highlight Google’s most important AI efforts to date. Our hope is that this will provide marketers with a clearer picture of how to adapt as the company integrates machine learning, deep learning and other AI technologies into its products.
How Google Went All-In on AI
Artificial intelligence as a research field has existed for decades. But the field only recently exited a series of AI “winters” in which investment and interest in AI was low among the public and private sectors. Thanks to this trend, Google, which was founded in 1998, didn’t truly begin to explore AI’s potential beyond small experiments until 2011.
In 2011, as documented by The New York Times, Google’s Jeff Dean met Andrew Ng, who was working on neural networks as part of what would become the Google Brain project. Dean and Ng, who now heads Chinese internet giant Baidu’s AI department, made progress on using neural networks to make Google products better. The team made major improvements in speech and image recognition results using AI.
Inspired by early successes, Google began to acquire AI companies in 2012. Notable among its 11 AI acquisitions to date was Google’s purchase of DeepMind Technologies in 2014. With a mission to “solve intelligence,” DeepMind’s researchers built an AI system that defeated a human champion in Go, a board game, in 2015, and the top-ranked Go player in the world, Lee Sodol, in 2016. Google also began making massive improvements to its products, such as Translate, through deep integration of AI.
While a tool like IBM’s Watson is a system with many applications from marketing to healthcare, Google is—similar to Salesforce—attempting to bake AI into most of what it does. This has major implications for marketers who use Google products and services to run campaigns. Especially when it comes to Google’s key product: search.
How AI Impacts Google Search
In 2015, concurrent with its developments in language processing, image recognition and translation, Google deployed a deep learning system, nicknamed RankBrain, to parse some search queries. Reports WIRED:
As of October [2015], RankBrain played a role in “a very large fraction” of the millions of queries that go through the search engine with each passing second.
With the appointment of AI expert John Giannandrea as head of search in 2016, Google has indicated that machine learning and deep learning are going to be instrumental in how search works. As AI plays a bigger role in responding to search queries, there are dangers that the technology won’t be transparent about how it arrives at the “best” results.
It’s likely consumers will benefit from better, faster and more relevant results should Google maintain its search dominance. But the producers of that information, from blogs to brands, may have even less insight into how their content reaches consumers via search than they do now.
This picture becomes even more complicated when you consider that Google has introduced its AI-powered Assistant. This bot answers questions and performs tasks as ordered via text and voice. It comes standard in Google’s Pixel phones, following the lead of Facebook and Apple, which both have AI-powered chat or assistants. Google’s Assistant finds information and performs tasks for you without leaving the company’s ecosystem. This is all powered by natural language queries you type or speak.
How This All Comes Together
Google uses AI to power products like Translate, providing better free services for users. This benefits consumers. Given AI’s benefits to Google products, the company’s investment in Brain and AI as a whole are producing fruit in other areas of the company. The developments to date have made possible AI-powered search and an assistant that delivers answers based on natural language queries. This technology now powers a substantial portion of the Google experience across mobile, desktop and voice.
Google’s corporate mission is to organize the world’s information. And thanks to its use of AI, how that information reaches consumers is changing. Digital marketers base entire campaigns on how the world’s information is structured. We know that consumers want timely, relevant information that answers their questions, so brands strive to deliver it via organic, earned and paid online channels. Those brands that do this effectively are better positioned to win business.
But what if AI determines how useful your information is to consumers? If you’re creating valuable, relevant messages, this shouldn’t be a problem. But consider currently how big an effect Google’s algorithm changes have on companies worldwide. Now introduce AI-powered queries across platforms and you can see the landscape is becoming more intuitive for consumers and more complex for brands.
The companies that aren’t prepared for this new paradigm will find it extremely difficult—and costly—to determine what messages work and where they work best. This is not a new problem, but it is one that has significant potential to grow worse before it gets better.
To cope, marketers, executives and entrepreneurs must avoid the assumption that searching for information online will remain fundamentally similar to how it was in the past. They must educate themselves about AI-powered technologies that companies like Google are implementing across their products. And they should embrace opportunities to transform their own businesses with these technologies.
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