Understanding the Artificial Intelligence Hype Cycle, in 5 Stats
At last week’s Google I/O conference, a few choice terms came up repeatedly. Machine learning. Artificial intelligence. Deep learning. They were mentioned so often that New York Times technology columnist Farhad Manjoo joked that “machine learning” had reached “70 trillion” utterances only a few hours into the conference’s first day.
Google is using AI to improve just about every realm of its vast technology empire. On Android, for example, the company announced an update to its virtual assistant with futuristic features like Google Lens, which can “read” photos in real time. It also announced a hyper-fast AI processor built to grow its cloud computing business, and a more “proactive” Google Home product.
Google’s CEO Sundar Pichai summed up the vision on the company’s blog, Keynote: “We are now witnessing a new shift in computing: the move from a mobile-first to an AI-first world.”
Google isn’t the only one pushing toward an AI-first world. We’re witnessing an arms race that involves just about every major technology company, from martech giant Salesforce to the ‘Chinese Google’ Baidu to old dogs like Microsoft. Even industries like retail and energy are already turning to machine learning to implement techniques like real-time pricing. AI is the next major step in computing, and it’s hard to imagine what industry it won’t impact.
If you’re not convinced, here are five stats that’ll help you understand the rise of artificial intelligence.
AI is 2 to 5 years away from mainstream adoption
In Gartner’s hype cycle, which ranks technologies based on how the market perceives them and how far away they are from mainstream adoption, machine learning is right at the tippy top. This means there is a lot of frenzied talk about all the possibilities of the technology, but not as much critical thought.
Boardroom meetings are bearing that out, according to research by Bloomberg.
That’s what you call exponential growth.
Yet that doesn’t mean that AI’s takeover is right around the corner. As you can see from the hype cycle, nothing in this emerging technologies graph is expected to earn mainstream adoption in less than two years.
According to the hype cycle, we are heading toward the “trough of disillusionment” for machine learning within the next year or two. Almost every hype cycle includes some skeptical backlash. Usually the backlash comes when expectations get too inflated, or because the technology is not as advanced as analysts predicted. However, based on the data out there, it’s possible AI could buck the trend.
Investment in AI will increase more than 300 percent this year
Along with what seems like every market research and consulting firm, Forrester is extremely bullish on AI, and this year is the beginning of a tidal wave. Accenture also found that 85 percent of executives plan to invest extensively in AI-related technology over the next three years.
Google has already pivoted from “mobile-first” to “AI-first.” And most martech companies are already touting their machine learning prowess, whether it’s legitimate or not. It’ll be interesting to look back on this year to see which companies doled out the cash to get on board, and which were left behind.
Businesses that use AI “will steal” $1.2 trillion from competitors every year
Speaking of getting left behind, Forrester does not pull punches when it comes to the impact AI can have. The research firm expects companies driven by insights (i.e., from data and AI) to significantly outperform those that don’t or can’t.
That difference will have huge consequences. Perhaps the big players will keep getting bigger since they have the resources to invest in better AI. Or maybe savvy young companies will use AI to outmaneuver old giants—something Netflix and Amazon have already done. There will be winners and losers.
60 percent of machine learning will run on Amazon, Google, IBM, or Microsoft by 2020
Like most parts of the software world, AI’s future is controlled by a select few. Since AI development is such a resource-intensive process that requires uniquely qualified engineers—and cloud computing—it’s been consolidated. Google, in particular, has positioned itself to own the space.
Everyone else has to follow one rule: If you partner and play nice, you can share in the benefits. Yet marketers should be happy that every martech giant is investing heavily in machine learning. Many ad tech platforms and marketing automation tools run on more basic machine learning programs. If companies like Salesforce are to be believed, the AI revolution should begin in earnest within the next few years.
Most marketers still don’t get what AI can do for them, but they’re excited anyway
Beyond basic algorithms, AI is still in its early stages. Not many people outside academia or the big tech firms truly have a strong grasp on the technology itself. Yet for the most part, marketers recognize that there is immense possibility, according to CMO Council.
Yet it’s also fair to be skeptical—as we’ve already seen, we are at the “peak of inflated expectations.” That’s why 24 percent of marketers don’t see the value in AI or already feel overwhelmed by data and technology. But it would also be unwise to ignore the incredible shift taking place.
For those overwhelmed by data, here’s an unavoidable fact: marketing runs on data. It’s not going away. We’re already in a data-first world—now the question is if AI can revolutionize how we use it.