It is a fact, and surely you heard it is happening. The time when machines learn has come. In the airline industry, machines can learn about fare gaps from themselves, and airlines are looking beyond historical trends for yield management. They are running predictive analytics and interpretations. But will they replace or empower revenue management and pricing analysts?
Artificial Intelligence (AI) is one of the biggest trends in the airline industry, in several fields. It has been applied to the hotel industry, flight maintenance, and airport management. Singapore Airlines is already using AI for competitive marketing intelligence, to build its brand and drive sales, using an Artificial Intelligence service to target new customers in a digital marketing campaign, based on online behavior.
But passengers are one step above airlines in airfare monitoring: applications such as tripcombi (formerly tripdelta) use AI to find hidden flight routes. It not only provides the results of an original travel search but also creates entirely new ones. The software finds loopholes like using nearby airports in considerations, turning return and single flights into open jaw flights, and breaking up existing airline alliances, saving prices and airfares in up to 90% .
Some airlines are innovating in their airline pricing strategy with big data. We’ve written about how EasyJet began using applied data science to revenue management and is starting to use AI to predict demand and analyze over 1.3bn searches made on its website each year, to optimize destinations and flight times.
There is plenty of examples. After considering those facts, a very relevant question arises:
Will Artificial Intelligence replace humans and our revenue management and pricing teams?
The answer to this question is not a matter of “YES” or “NO”. It is a matter of WHAT will be replaced.
Will Artificial Intelligence rival airline revenue management and pricing analysts? In October 2014, entrepreneur Elon Musk described Artificial Intelligence as “summoning the demon” as it was creating a rival to human intelligence as the biggest threat facing the world, The Economist reports.
But then, the magazine refutes these claims with interesting facts. Why would Google or Facebook go into an AI arms race without “fretting about being surpassed by their creations”?
“Their business is not so much making new sorts of minds as it is removing some of the need for the old sort, by taking tasks that used to be things which only people could do and making them amenable to machines,” according to The Economist.
The article answers with quite an explanation:
“Perhaps the best way to think about AI is to see it as simply the latest in a long line of cognitive enhancements that humans have invented to augment the abilities of their brains. It is a high-tech relative of technologies like paper, which provides a portable, reliable memory, or the abacus, which aids mental arithmetic.”
According to the World Economic Forum’s The Future of Jobs report, as we are heading to the year 2020, AI and machine learning will be a major driver of change in the mobility industry -where they classify the aviation sector.
In fact, 58% of respondents in the mobility sector claim that the primary barrier to planning the future workforce is “insufficient understanding of disruptive changes” while 83% believe a good strategy to manage change will be to invest in “reskilling current employees.”
Will the airline industry need Artificial Intelligence experts?
It appears so. American Airlines Head of Mobile Apps and Wearables, Phillip Easter, not only calls AI “the next Golden Age”, as it will dramatically improve how businesses interact with their customers. It’s calling their peers to get their workforce educated on what AI is and how it works.
He underlined the importance of getting the entire business behind understanding and implementing AI at the first AI Summit, gathered in London in May 2016. According to estimations collected from the event organizer, the use of AI in the business environment is growing fast and over the next 10 years, spending could increase from US$200m to over US$60billion.
Will it replace jobs?
Of course it will, and it is nothing new at all. AI will replace jobs just like rowers were replaced by engines. Like coachmen were replaced by chaffeurs, then by cab-drivers, then by uber-drivers. Some jobs will disappear just like phone operators disappeared. Some other jobs will be created, like programmers and car-mechanics. Some jobs will be changed forever, like when physicians got access to X-ray images.
It is an exciting time to be alive, and I’m sure in the future people will envy us for having witnessed these changes. In particular, Revenue Management and Pricing jobs will be incredibly transformed by AI and Big Data technologies. Do you remember how was the office without spreadsheets or email? Do you remember how was life without smartphones? Do you remember the world before Internet?. In a not so distant future we’ll be able to add the following question: “Do you remember how was revenue management and pricing before AI?”
There’s a classic movie (Matrix, 1999) where a character says “Never send a human to do a machine’s job”. It is a very interesting statement; for instance: nowadays i’ts hard to think anyone can do simple aritmetic better than a pocket calculator. However, I think the opposite is still true in most cases: “Never send a machine to do the job that a human should do”.
Now be honest to yourself: What percentage of the tasks that you are doing today could be automated? If you are not an AI expert, chances are that a well-experienced AI team could double that percentage. AI combined with Big Data analytics will allow the automation of a lot of tasks, but not all of them. That’s exactly the point where the power of man-machine interaction must be leveraged. Send the machines to do work of a machine, and send the humans to do humans work, leveraging AI as a tool.
Revenue management analysts and pricing analysts being replaced by computers in repetitive tasks is an inevitable result of the explosive increase in available data that we are experiencing. Years ago analysts would only have access to a few megabytes of data, that being enough to make decisions. A couple of hours a week performing repetitive tasks would not harm anyone’s schedule. Nowadays, you or your competitors are having access to terabytes of data, and the couple of weekly hours of yesterday might have turned into days or full weeks. It is certainly necessary to surrender some control of the repetitive tasks to the machines, trusting AI to do the work for you.
Concurrently, more data is an enabler to better and more detailed decisions. Those better and more detailed decisions can be made only if the methods for data analysis are different. There is more data, there are more opportunities, but your team’s size stays the same (at best!). Therefore, it is inevitable that you leverage the power of AI and Big Data analytics to make better decisions. Of course you can use the same old methods with more data, but would you let your competitors take the opportunities of AI-empowered methods for data analysis?
The amount of available data and the ability to process it with AI is growing exponentially. On the other hand, our human brain-power is not growing that fast, neither are your revenue management and pricing teams’ sizes. Again, it is inevitable that the nature of your work will change. Regarding our initial question “Will they replace or empower revenue management and pricing analysts?”, I can conclude that the definitive answer to this question solely depends on our creativity.
Some aspects of current Revenue Management and Pricing will indeed be automated soon, but some others will take a very long time to be automated, making those aspects remain more efficient if handled by humans. When we leverage the power of AI, new opportunities to better Revenue Management and pricing are limited only by human creativity, experience and wisdom, where AI alone is not guaranteed to win. That’s precisely where we must put our stakes. Let’s work as a team! What do you think about integrating AI to your airline pricing and revenue management processes? Where do you see the “low hanging fruits”?
Comments