In recent years, artificial intelligence (AI) has become one of the
most talked about trends in corporate travel. But while travel managers are
showing increased interest and curiosity in AI, there is still much confusion
about what the term actually means and how it can be applied to business
travel.
In a survey of travel buyers conducted by Business Travel News (BTN) in
2018, only 16% of respondents said they had “good” or “excellent” knowledge
about AI. The majority admitted to having limited awareness about the subject.
The same survey also found minimal adoption of AI solutions in corporate travel
programs thus far.
What is AI?
“Artificial Intelligence” is a marketing term rather than a single
technology suite, according to Dr. Eric Tyree, Chief Data Scientist at CWT.
“Broadly speaking, AI is computers doing things that people thought only humans
could do, and so that definition evolves over time as computing capabilities
become more advanced.”
When English computer pioneer Alan Turing developed his test for AI, he
was looking for a machine that behaved in a way that was indistinguishable from
a human. The infamous Turing test, which is
seen as a hallmark of AI,
investigates the ability of a machine to execute tasks such that a person
cannot tell if the task is being completed by a human or a machine.
There are various technologies that are talked about as “AI”, with
differing methodologies and levels of sophistication used to execute tasks.
Towards the less sophisticated end of the spectrum there is “robotic
process automation” (RPA), which uses technology to automate simple tasks.
Because processes repeated by a machine are faster and more accurate, RPA can
be used to automate tedious and repetitive tasks, allowing people to be more
productive. Whether this constitutes ‘true’ artificial intelligence on the part
of a machine is a philosophical question, but RPA is undoubtedly a powerful
task automation technology.
Then you have “machine learning”, which uses examples to learn the underlying
patterns and drivers in data or a task. It improves processes by referencing
previous or example interactions. When there is a decision that the technology
needs to make, it makes it based on the patterns it has seen and its ability to
extrapolate from the patterns to new ones it experiences. For example, the past
ten times you called a travel consultant, you booked with airline X. On your
eleventh call, even though you do not have this specific information in your
profile, machine learning will infer you will most likely be booking airline X.
However, if you travel to a new destination not served by airline X, if the
training data is rich enough, the machine learning algorithm may correctly
infer your preference for airline Z which is similar or is an alliance member
with airline X.
More sophisticated machine learning techniques can be even be overlaid
on RPA to ‘teach’ machines the more subtle or complex elements of a task,
rather than explicitly programming it.
But while RPA and machine learning do enable computers to display some
human-like characteristics, there is of course much more to AI.
Really well-implemented AI is the ability for a computer to apply
human-like intelligence to a task – or series of tasks – to ensure the best
outcome. This is often accomplished by combining process automation, machine
learning, expert logic and other techniques to solve problems and complete
tasks that previously required human intervention.
The aim here is to use a variety of technologies to give the system the
ability to learn and adjust its processes to improve outcomes over time. This
enables AI to redefine and re-align processes by developing an understanding of
the business at hand. It is able to apply this understanding to a particular
process to make decisions, even if it has not undertaken this specific process
before.
Consider facial recognition as an example. When beginning to recognize
faces, an AI-enabled engine might have a low success rate at first. However,
with larger, richer data, explicitly logical enhancements and other
modifications (both human and computer implemented), it will become more and
more accurate, quick and sophisticated in recognizing faces – like learning to
ignore glasses, beards and makeup to more accurately recognize the true
underlying facial characteristics of people.
How May I Help? There are myriad ways AI can be applied to business travel
How is it being used in travel?
In the travel context, a wide range of AI techniques and technologies
are being leveraged to enhance or automate traditionally human-executed tasks,
to the point that we are unaware whether it is a human or computer conducting
it. Travel AI is starting to pass the Turing test.
“Most AI today is very observational in that it looks at patterns and
either tries to see those patterns in data it hasn’t seen before or tries to
extrapolate from what it has seen in data in the past,” Dr. Tyree explains.
“However, this is changing rapidly with the growing sophistication of AI
applications in travel, where ensembles of technologies are being used to
create human-like automation of tasks. Coupled with the growing power,
increasing speed and decreasing cost of computing, the amount of data available
is also growing exponentially, leading to the wider application of AI.”
There are myriad ways that AI could potentially be applied to change
the way business travel is viewed, managed and experienced. Here are some of
the exciting applications we’re seeing today, and a few that are around the
corner:
Facial recognition to speed up airport check-ins: Several airlines and
airports around the world are testing and implementing facial recognition
software that can verify travelers with a “quick photo capture”, allowing
passengers to board using a biometric self-boarding gate. This is expected to
improve safety and security, while creating a faster and more efficient
check-in and boarding process.
Robot hotel concierges creating a better guest experience: A number of
hotels have been experimenting with AI-powered robots to manage guest services.
A robot concierge named Connie, developed by IBM, has been deployed at the
Hilton McLean in Virginia in the United States. It has been introduced in a
pilot program designed to help guests figure out what to visit, where to dine,
and how to find things they need. The idea is that it will reduce the need for
guests to wait in line to ask a question, while freeing up employees’ time to
focus on other tasks.
More relevant booking search results: Just as Amazon and Netflix
suggest new products and movies based on your preferences and past selections,
AI is being used to show business travellers more relevant search results –
while ensuring they remain within their organization’s travel policy, of
course. This helps reduce the time they spend searching and booking, allowing
them to focus on their work and be more productive.
Quicker support with chatbots and messaging: If you’ve ever opened a
chat box when contacting your bank or talking to a retailer online, you’ve
likely experienced AI-enabled messaging. This is being applied to business
travel too.
CWT is rolling out a hybrid messaging model, which has an AI-powered
chatbot supported by an experienced human agent. Travelers can ask for
assistance by sending text messages via the mobile app, where CWT’s hybrid
travel counsellor, Reece, responds immediately. Reece answers queries quickly
because she already knows an employee’s name and travel information from the app.
More complicated questions are seamlessly transitioned to a live travel
counselor.
Easier and more actionable data and reporting: There is a lot of data
in corporate travel. The sheer volume and complexity makes it hard to use
effectively, especially if you’re not a data scientist. AI can help travel
managers, business unit leaders and other stakeholders who may not be data
experts, make sense of all this information. For example, CWT has a platform
that makes searching data questions easier. You type in what you’re looking for
into the search bar – similar to if you were using a search engine like Google
– and the tool quickly visualizes the data and builds the reports that you
need. It also has an underlying AI engine that improves its search capabilities,
getting smarter and more personalized through use.
Upwardly Mobile: AI enables hybrid messaging
Text message alerts for missing hotel bookings: Systems can be designed
to automatically identify trips with no hotel booked and proactively offer
travellers program-compliant hotel options, even with last-minute bookings. This
helps ensure they book in-channel and their accommodation data gets captured,
allowing for them to be easily located in the event of an incident or
emergency.
Predicting trip disruptions: Various solutions which use predictive
analytics to identify delay patterns across flights to forecast disruptions are
being developed. They factor in things like the historical on-time performance
of an airline, seasonality, flight timings, flight paths and air traffic,
congestion at various airports, and weather forecasts. With this information
they can predict the probability of a delay occurring, as well as the length of
the delay.
Enabling traveller wellness: CWT is using machine learning to analyse
travel patterns and other data to provide analysis and feedback on traveller
wellness and productivity. The aim to help travellers plan better and be more
effective when travelling, and to help travel managers ensure their programs
have the appropriate processes and feedback loops to ensure travellers are
healthy and productive.
Are we ready for a machine takeover?
While experts agree that AI will deliver cost savings, a streamlined
booking process, an improved travel experience on the road, enhanced duty of
care capabilities, and many other benefits, it’s not going to completely replace
travel counsellors or travel managers any time soon.
“Business travel is riddled with exceptions and complexity and it is
surprisingly hard to automate a lot of functions,” says Dr. Tyree.
Andrew Jordan, CWT’s Chief Technology Officer, believes people think AI
can do a lot more than it really can. “At the moment, AI mostly consists of
pattern matching,” he notes. “Computers can be very helpful in supporting
humans in some tasks; but we can’t simply put a robot in a call centre to
replace humans.”
On Repeat: At the moment AI mostly consists of pattern matching
To what extent and how quickly these technologies will make their way
into corporate travel programs will depend on several factors. Amongst these
are the appetite of travel programs to try something new, concerns around data
security, as well as an organization’s culture, demographics and booking
patterns. For instance, an organization whose travellers expect very high-touch
service or book a lot of complex itineraries might see fewer opportunities to
deploy AI-enabled solutions than a company with a self-servicing culture and
predominantly point-to-point trips.
“What travellers are looking for is ease and comfort in the travel
experience,” says Anikesh Patel, CWT’s Director of Customer Management for
India. “There is an expectation of personalization and intuitiveness – and
while organizations are happy to see technology used to reduce costs, they are
not prepared to compromise on the travel experience, whether it is supported by
travel counsellors or booking tools.”
Blog author: Siddharth Singh, Global Communications, CWT. Register to attend Business Travel Show for FREE and visit CWT at stand B230 www.businesstravelshow.com
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