ESTIMATED 2017 REVENUE
EARLY INTEREST IN AI
system, introduced in 1998,
suggested additional items for
purchase based on the observed
actions of similar users.
Any business task or consumer
experience that can be automated should be automated.
“Much of what we do with
machine learning happens
beneath the surface . . . quietly
but meaningfully improving
core operations,” CEO Jeff
Bezos wrote in his 2017 shareholder letter.
Yap (2011), a cloud-based start-up that’s expert at converting
speech to text, which reportedly
helped lead to Alexa
Last April, Amazon released the
technology powering Alexa as
a stand-alone service so that any
company can develop its own
intelligent voice applications.
WHY IT IS AHEAD
Amazon has been the first
to showcase the exciting
potential of AI in everyday life,
from autonomous drone
delivery to frictionless retail
checkout. And Alexa has been
a game changer.
The saving grace is that businesses of all sizes can avail themselves of some of these AI innovations. In fact, Amazon, Microsoft, and Google are counting on it. Their cloud-computing
platforms—Amazon Web Services, Azure, and Google Cloud, respectively—include enterprise
AI offerings such as image recognition, natural language processing, and language translation. All three companies see AI as the key to driving future growth of their cloud platforms; at
present, Amazon Web Services is a $16 billion business that’s increasing 42% year over year,
though that pace has slowed as Microsoft and Google begin to catch up. Then there’s IBM, which
calls its flavor of artificial intelligence “cognitive computing” and has effectively branded it as
“Watson” to sell as a service. While Facebook and Apple don’t offer their own platforms, they
publish academic papers on their research—and, in Facebook’s case, it open-sources some of
the technologies it’s created.
As a business tool, AI is still in its infancy. Recent studies by both the McKinsey Global
Institute and MIT/Boston Consulting Group reported that only about 20% of companies have
implemented the technology in a meaningful way. But unlike past technological inflection
points—such as the emergence of e-commerce in the 1990s—AI doesn’t naturally favor nimble
startups. Because AI craves data of the sort that can take years to accumulate, “there’s actually
an advantage to incumbency, because the more knowledge you have to train your AI, the more
valuable it is,” argues David Kenny, IBM’s senior VP for Watson and IBM Cloud.
What AI does share with past tech trends, however, is a tendency to be overhyped in such
a way that can obscure its real capabilities. In September, for example, an investigation by
data scientist Steven Finlay, the author of Artificial Intelligence and Machine Learning for Business.