Travel to new territories: Artificial Intelligence and Machine Learning


Tommy Kolega, CIO, Viadex: Global IT Infrastructure and Deployment Specialists

The term ‘artificial intelligence’ was first coined by John McCarthy in 1955/6.
This was visionary thinking at its most far-sighted:
Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it,” he said.
Well, he was right.


The reality of Artificial Intelligence
It’s time to stop being amazed by Artificial Intelligence (AI). Once you accept that technology moves at a very fast pace, but that every step forward is really nothing more than evolution, the catalyst for the next step forward, it all becomes less awesome and more practical; better ways of doing things.

So, of course we’re making machines do things smarter, of course they are taking on the appearance of thinking for themselves, and of course this raises concerns amongst some; especially when the popular visualisation of anything to do with AI involves bizarre droid-like beings with cold, hard stares and a barely concealed intent to take over planet earth.



The travel and tourism industry is now well along the way on the AI journey – harnessing algorithms in a more streamlined and automated fashion. This is the essence of AI, when stripped of its glamour and mystique; it’s just efficiency getting smarter.

Perhaps it’s less about technology evolving, and more about the evolution in capabilities and insights of the people and vendors who develop innovative solutions based on automation, and sophisticated methodologies to do with algorithms.


Establishing boundaries
AI will be subject to all sorts of genius manipulation in the months and years ahead. The ethics of AI must be debated and resolved and there will clearly be a need for universal adherence to standards and regulations.

I’ll be looking at this area in my next blog, but for the time being bear in mind that rules get broken; whether by those with maverick intent, or by geeks who simply can’t help prizing open the box. New frontiers and territories also get explored and opened up by innovative thinkers, finding ways of using AI for business efficiency and profitability; which both imply the delivery of better services to customers, and superior customer experiences.


Engaging with the customer
The travel and tourism industry is becoming increasingly competitive as technology enables operators to continuously improve efficiencies and interpret Big Data into compelling ‘next action’ communications to enrich the customer journey; the one that takes place before the customer journey. In its Travel and Tourism Competitiveness Report 2017, the World Economic Forum states:

“To achieve a Smart Travel approach, the travel industry must increasingly rely on technology and digitization to create a safe and seamless experience for passengers. Effectively, innovations over the past decade have led to a significant increase in automated technology to facilitate travel and make it more secure. With the available technology, passengers today are able to book their flights and check in online, have their boarding passes on their smartphones, go through automated clearance gates and even validate their boarding passes electronically to board planes. Such technologies should be applied to continue to enhance border security and travel facilitation.”

Although Artificial Intelligence and the application of Machine Learning were once the domain of research and education institutions, travel companies have for some time been using these concepts in various areas including recommendation engines, fare and booking forecasting and dynamic pricing.


The journey begins
Let’s take a quick step back to understand what machine learning is from a programming perspective, and how it differs to normal programming. The application of many machine learning algorithms is typically referred to as the basis of Artificial Intelligence. Machine Learning is the algorithmic discovery of finding meaningful patterns in data.

Machine Learning differs to normal programming because in the normal programming experience the code or rules are written for specific tasks using inputs and outputs. To cater for patterns in data would require millions of lines of coding for each specific pattern.  This is neither realistic nor practical. It’s verging on the impossible and certainly wouldn’t make any sense to entertain as a business proposition, with the pressure on time to market and costs; not to say efficiencies.


So how does machine learning apply in the real world?
Andrew Burt, formerly a special advisor for policy to the head of the FBI Cyber Division says, “What is challenging is that machine learning for the first time at scale is starting to occupy a significant place in the decision-making process”.

If real people were tasked with going through and tracking all the different types of user behaviours, buying patterns, fares on offer and pricing options it would be extremely time consuming and require lots of cross validation. Machine Learning models can be applied to each of these areas to analyse the data and produce meaningful insights to the consumer, providing a better customer experience and obviously better returns for travel companies, in a fraction of the time.

One thing is very clear, machine learning and artificial intelligence is now being used in mainstream applications and industries and will only increase in its nature and spread of where it is applied – all aimed at making decisions faster and more accurately for the significant improvement of customer experiences. I am fairly sure AI isn’t going to take over the world. I’m just as sure it’s going to dominate conversations and new business models in travel and tourism for a long time to come; in a very amenable way too:


I’d be interested in hearing your thoughts on AI. If you want to know more about how machine learning and artificial intelligence can help your business, please also contact me at