The ubiquity of artificial intelligence is evident in the
fact that the abbreviation “AI” is now a common and recognizable term.
A Google
search for “AI” turns up more than 820 million results, with articles from
sources as diverse as The Wall Street Journal, the Verge and Vanity Fair and
topics such as AI for healthcare, astronomy and human resources.
Microsoft recently announced a reorganization that bolsters
its focus on AI, with CEO Satya Nadella calling this technology something that
will “shape the next phase of innovation.” An article in Harvard Business
Review calls AI “the most important general-purpose technology of our era…”
In travel, AI is starting to touch every business sector and
every step of a traveler’s journey, from the ideas and images in online
searches to the pricing of flights and accommodations to experiences
in-destination.
And the subset of artificial intelligence known as machine
learning holds the promise that these systems and the capabilities they offer
today will only continue to get better – faster, smarter, more helpful – with
the addition of each bit and byte.
This month we’re digging into artificial intelligence to
learn how it's being used in travel and to understand its future potential.
For part two, we explore a variety of examples from one of
earliest and best-known AI brands: IBM’s Watson.
Background
It’s been more than seven years since IBM’s Watson computer
entered the spotlight by beating two acclaimed – and human – competitors on the
quiz show Jeopardy.
In the years since, IBM has been refining the technology’s
ability to ingest, understand and evaluate information in its “natural language”
form. Today Watson is being deployed for a broad range of applications across
industries such as healthcare, automotive, education and travel.
Dee Waddell, IBM’s global managing director of travel and transportation
industries, says this is just the beginning. But the key to “smarter”
artificial intelligence that, in case of travel, can provide a better passenger
experience and better business results lies in a combination of next generation
technologies and broader accessibility to data.
“Eighty percent of the world’s data really is within
companies - still only 20% of the data in the world is searchable,” he says.
“So our point of view is that the incumbent travel companies,
whether it be providers or resellers, we believe that they're in a position of
power because they have access to such a broad range of data. So we think it's
time for what we're calling the incumbents to drive the disruption of our
industry.”
Waddell shared a variety of examples of how IBM Watson is
currently being deployed across travel sectors.
Offer and pricing optimization
The process of online search, particularly for air travel,
can be incredibly complex, with potentially hundreds of combinations of routes
and fare classes for any one trip. Determing what offers to put in front of a
customer involves a balance of personalization to the needs of the traveler and
revenue optimization for the airlines.
Artificial intelligence is enabling this by creating
dynamic, real-time pricing for air and ancillary products.
While he cannot share brand names, Waddell says IBM is
working with a number of airlines around the world to test a new cognitive
personalized pricing and offering system developed specifically for travel.
“We’ve got 24 patents behind this that are either granted or
pending,” he says.
“And what's great about this engine that we've created is it
really never stops learning and adjusting. We’re able to ingest the
information, understand the selection, the decision by the consumer and then
continually optimize. What we’ve seen in leveraging this is it has a faster
level to an optimization for the experience as well as in the revenue side of
it, the offer acceptance.”
Waddell says some of IBM’s clients have seen a double-digit
percent uplift in revenue per passenger and in engagement scores.
And the cognition can be applied to offers throughout the
traveler’s journey – by customers service agents, airport operations, on-board
personnel, etc. – and across multiple channels such as mobile, web, email and
more.
Customer care
Traveling can be a stressful experience. Mechanical issues,
weather disruptions and other challenges cause problems for both passengers and
travel providers.
Brands know that the way they handle complaints and concerns
from customers can be a critical competitive differentiator – and an effective
way to engender loyalty.
Artificial intelligence can be used to help brands offer an
optimal response by enabling contextual and sentiment analysis of both text and
voice communication. This data can then be used by customer service
representatives or even in an automated system such as a chatbot to give an
optimized response to the traveler.
Watson “can actually take that [text or voice] through an
engine that will provide personality characteristics and insights. I think
there's over 50 data points that you can gather and glean to then leverage for algorithms
and optimization,” says Waddell.
Japanese rail line JR East is using IBM Watson to analyze
the tone, personality and emotion of customer inquiries, for example regarding
fares, schedules and seat availability.
“So this is really about showing empathy for the individual
and this is what the Watson engine can do,” he says.
“We've seen an agent response time up by about 10% ... we see
consistency of quality across agents, which drives improving customer
satisfaction.”
The AI listening and analysis is not limited to call
centers, it can also be deployed for posts on Twitter and Facebook, emails and
through a mobile app or website.
Maintenance and
compliance
Artificial intelligence is also enabling more efficient management
of airline maintenance, which in turn impacts passenger experience, safety and
airline revenue.
Korean Air is using IBM Watson to analyze structured and
unstructured data from ground operations, cabin crews, manuals, etc.
“We have an ability to ingest maintenance information and to
be able to help accelerate the root cause analysis,” Waddell says.
“Also the ability to then predict when will a part have a
propensity to fail, which parts are in stock and how do I then make sure that I
can have that part there so as to minimize delays on an airplane.”
Waddell says the technology has shortened maintenance lead
times by about 50%, reducing delays and cancellations and driving higher
customer satisfaction.
IBM is also working with IATA to add efficiency to air cargo
compliance procedures. By ingesting IATA regulations and policies, Watson can
automate the detection of irregularities and expedite resolution.
