ESTIMATED 2017 REVENUE
EARLY INTEREST IN AI
Pioneering IBM engineer Arthur
Samuel coined the phrase
machine learning and in 1959
developed a first-of-its-kind program that could play checkers and
learn from its experience.
Help businesspeople be better at
their jobs, whether they’re doctors or tax preparers.
“We are the ones that woke up
the AI world here again,” IBM CEO
Ginni Rometty told the CNBC personality Jim Cramer in June.
The Weather Company (around
$2 billion, 2016) gave IBM access
to approximately 2. 2 billion forecast points worldwide, all transmitting data that Watson churns
through to fuel multiple client
In September, IBM and MIT
announced a 10-year partnership
in an AI lab; one research goal is
developing algorithms to solve
complex business problems,
a complement to Watson’s
WHY IT IS AHEAD
IBM may not have the revenue
momentum of its tech peers, but
it has established Watson as the
strongest brand in AI.
a system that uses Rekognition to match newly taken photos with ones from the archive. So
far, it’s helped identify 20 suspects.
It was also an extraordinary bargain. The initial setup cost the sheriff’s office only around
$400; the monthly bill from Amazon Web Services is about $6. “With every dollar I spend, I’m
accountable to the taxpayers,” says Adzima. “We’re spending such small amounts of money
and we’re getting a huge return on investment.”
BUILD IF YOU MUST
Facial recognition is a type of AI that’s applicable in various scenarios, making Amazon’s version immediately useful in many fields. In some instances, however, companies need to
employ AI that’s been carefully tweaked for a particular purpose.
“We don’t tend to ask our radiologist for art advice, or our lawyer for stock-picking advice.
You go to experts for different things,” says IBM’s Kenny. That’s why IBM tailors Watson for
specific industries, from education to supply-chain management. His point reflects a basic
truth about AI: The more ambitious you get, the less likely a plain-vanilla algorithm will suffice.
Real estate hub Trulia hoped to use AI to rummage through its collection of millions of photos of homes for sale and rent and distinguish among kitchens, bedrooms, and bathrooms—
and even notice when a kitchen features such price-boosting extras as granite countertops.
That’s not the sort of intelligence that’s available as a commodity.
“Trulia needs to innovate,” says Varma, the company’s data-science guru. To do so, he concluded, “we need to own the computer vision internally.” As a division of Zillow, the leading
digital broker valued at $5.5 billion, the company could reasonably aspire to treat AI as a strategic imperative and invest appropriately. Even though it’s an Amazon Web Services customer,
Trulia chose to hire its own machine-learning experts and develop its own proprietary models.
Sometimes the individualization can be minimal. The car-buying site Edmunds, which
offers prospective buyers resources such as specs, prices, and reviews, has integrated AI into
numerous aspects of its business, from forecasting revenue to securing its website. Much
like Trulia, it wanted to use the technology to help it sort through hundreds of thousands of
photos, in this instance, to identify the types of exterior and interior shots it has of specific
makes and models. “We got 90% there using Google off the shelf, and then we were able to
just tweak it at the end to be better about understanding vehicle images versus all the images that Google is looking at everywhere else,” says VP of product innovation Greg Shaffer.
GET EVERYBODY INVOLVED;AND KEEP THEM INVOLVED
Whether a company seeks lots of help or takes on more of the heavy lifting itself, AI’s worth
is deeply tied to the specifics of individual business challenges. Which means that it can only
be effective if stakeholders are as engaged and committed as IT staffers are.
“Organizations have the tendency to sit back, just like [after] they purchased technology
in the past, and expect tech solutions to do all the hard work for them,” says Sjoerd Gehring,
global VP of talent acquisition at Johnson & Johnson. “That’s the one thing that really doesn’t
work with AI.” Though Gehring’s job focuses on people rather than technology, he championed J&J’s effort, in collaboration with Google Cloud and recruiting software provider Jibe, to
incorporate AI into the way it finds everyone from medical researchers to truck drivers. The
company says that appropriate applicants are up by 41% since it began using a search engine
powered by Google’s machine-learning algorithms to match a million job candidates a year
with the 25,000 positions it fills.
After that, “it’s a continuous process of refinement and training to get your implementation better and better and better,” says Meg Sutton, director of retail client experience at H&R
*As of September 2017
THE GREAT AI
WAR OF 2018