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.

• AI analysis, part one: Travel tech giants