10
FORTUNE.COM// FEB.1.
Now the catchall
phrase of artificial intel-
ligence is shaping up as
the defining technologi-
cal trend of the moment.
And yet, because the
claims of what it will
achieve are so grand,
businesses risk rais-
ing their hopes for A.I.
too high—and wasting
money by trying to apply
the technology to prob-
lems it can’t solve.
Consider the bubbly
warning signs. Venture
capitalists are beyond
eager to fund A.I. They
staked 1,028 A.I.-related
startups last year, up
from 291 in 2013, says
researcher PitchBook.
Twenty-six of those
companies had “A.I.” in
their names, compared
with one five years
earlier. Then there’s the
profusion of conferences
promising to explain
A.I. to the benighted
manager. At the annual
meeting of the World
Economic Forum in
Davos, Switzerland,
the agenda this year
included no fewer than
11 panels that reference
A.I., with names like
“Designing Your A.I.
Strategy” and “Setting
Rules for the A.I. Race.”
(Fortune has gotten into
this act too: Its 2018
Global Tech Forum in
Guangzhou, China,
was dominated by A.I.
discussions.)
The result is a serious
subject running the risk
of jumping the shark.
“If advocates are not
careful, they will have
successfully Bitcoinized
A.I.,” says Michael
Schrage, a researcher at
MIT’s Initiative on the
Digital Economy.
Make no mistake—
artificial intelligence
is more than a fad. It
represents a whole new
way of doing business
by turbocharging the
existing trends of auto-
mation, sensor-based
industrial monitoring,
and algorithmic analysis
of business processes.
Computer science was
already helping ma-
chines perform routine
tasks more quickly
than humans. The new
techniques of A.I.—com-
bined with ever faster
computing power and
the accumulation of
years of digitized data—
mean that for the first
time computers learn the
tasks humans require of
them rather than merely
doing as they’re told.
The result, says Tom
Mitchell, a machine-
learning professor at
Carnegie Mellon Univer-
sity, is nothing less than
“one of the major forces
for society and lifestyle
of the next decade.”
And commerce too:
Researcher IDC predicts
spending on A.I. will
near $80 billion in threeyears. Paul Daugherty,
chief technology and
innovation officer of
consultant Accenture,
reckons that figure will
prove low because “it
doesn’t account for the
investment companies
are making in transfor-
mation around A.I.”
Yet, as is the case with
any exciting technology,
there are limits to what
A.I. can accomplish.
Self-driving cars are
the perfect example.
We already have the
technology for them
to operate under ideal
circumstances, but even
John Krafcik—CEO of
Alphabet’s self-driving
car subsidiary Waymo—
admits they’llnever
be able to drive in all
weather conditions with-
out some human input.
What’s more, computers
are very good at learn-
ing clearly defined tasks,
like identifying people
in photographs or ac-
curately transcribing
speech. But understand-
ing human motivations
or drawing nuanced
conclusions from
text—insights at which
humans excel—remains
beyond the machines.
Says CMU’s Mitchell,
“We’re still in the very
early stages of trying to
productize this.”
What A.I. can’t yet
do ought to be of some
comfort to CEOs. Susan
Athey, a professor of the
economics of technology
at Stanford University,
reassures managers in
her executive education
courses of their worth—and also the limitations
of the A.I. scientists they
hire. “New Ph.D.s are
all bought in, but they
don’t have the experi-
ence of what doesn’t
work, which projects
not to do,” she says. A.I.,
says Athey, justifiably
“feels magical.” But it is
best at analyzing situa-
tions its designers have
prepared it to interpret,
as opposed to making
decisions on subjects it
hasn’t seen before. “It’s
just not right that your
A.I. will manage for
you,” says Athey.
A.I., in other words, is
no silver bullet. Jean-
François Gagné, CEO of
the Montreal software
startup Element AI,
reminds clients that A.I.
solutions are only as
good as the accumulated
data being fed into them.
“The opportunity every
organization is looking
at is the ability to have
adaptive systems,” he
says. “It is a journey. It
is not something you
can buy and suddenly
flip a switch. By the very
definition of A.I., it takes
time to learn.”
Gagné analogizes the
process of building a
useful A.I. to the differ-
ence between “teaching
your children the right
thing versus getting
the right behavior in
adulthood.” It will take
at least as long to know
if businesses were able
to properly grasp this
A.I. moment—or if it
was another extremely
expensive and elusive
money pit.“It is not
something you
can buy and
suddenly flip
aswitch.”