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AI and the travel sector - Part 1: What small and medium businesses need to know

Updated: Jan 26

What’s the reality of AI (artificial intelligence) in the travel sector today – and how can businesses take full advantage of it? In the first of a special two-part series, data specialist Mark Bush, a Firebird Director, explains what MDs and owners need to know.

There is a great deal of noise around the future of AI (artificial intelligence) in all sectors at the moment – and travel is no exception. Last November, I was invited to join an expert panel on the subject for the annual AITO overseas conference. The audience showed a lot of interest, with plenty of questions for us. After the panel, that interest translated into delegates playing with Chat GPT and sharing the content it produced – with sometimes hilarious results.


What we didn’t get round to discussing in-depth as a panel – and what I’d like to expand on here – are the practical steps that small and medium enterprises (SMEs) can take around AI now, and why taking action matters. In fact, the benefits you can unlock for your team and business with what’s out there are immense.


Before we get to the practical steps for travel businesses – which I’ll cover in the second part of this two-part miniseries – no informative piece about AI would be complete without making clear what AI actually is. That’s where we’ll start.

“‘AI’ can mean many different things – Chat GPT is only one example”

 The term “AI” covers a huge area and can mean many different things. Chat GPT – the free online chatbot that launched in 2022, and which can be instructed to generate all sorts of content – including jokes for conference delegates – is only one example, albeit the one example that has sparked the loudest hype so far. Self-driving vehicles, algorithms that share recommendations to customers, chess-playing robots: they’re all AI too.


Although Chat GPT is just the tip of the iceberg in terms of what’s available to businesses, some commentators liken its release to the impact of the iPhone. After all, smartphones had existed for some time before the iPhone’s release in 2007 (the first smartphone launched as early as 1994) – yet when that product debuted it was as if smartphones suddenly came into being. Almost overnight, everybody wanted one.


It’s the same with Chat GPT: as the chatbot launched there was a sudden rush of interest and excitement in AI generally; the sense of a breakthrough. Suddenly more and more business owners were actively wondering what this breakthrough involved, and what it could mean for them. 

“All forms of AI rely completely on data”

 There are four important sub-domains of AI:


  • Machine learning: a form of AI that has been around for decades, which empowers computers to self-learn from data. This encompasses deep learning, an advanced type of machine learning, which uses instructions to closely mimic the human mind and its functions

  • Computer vision: a subset of AI that allows machines to visually gain information from objects in the environment – through facial recognition software, for example

  • Robotics: which act to manipulate the physical environment, as we see in the tech being used in automated warehouses

  • Natural language processing: a tool enabling humans and computers to ‘talk’ to each other – think smart voice assistants


These domains can work singly and discretely, but more often they work together. Smart voice assistants, for example, use both natural language processing and deep learning to function, whereas medical diagnostic tools may use computer vision and deep learning.


In the travel sector, a high-end SME might aspire to create a bespoke concierge-style app for their customers: one that can not only improve its knowledge of what clients want when they’re interacting with the company, but also recognise a customer’s surroundings when abroad to unlock nearby recommendations and respond to any verbal cues – such as queries or requests around trusted taxi services, local sights, highly-rated restaurants and so on. This application would most likely use deep learning, natural language processing and potentially computer vision as well. 

“To dismiss AI as faddish is to miss a major opportunity”

 Regardless of the domain or intended function of AI, every form it takes relies completely on data: its input and output. And on a practical level, the data employed for business analytics can be split into different types which, like AI sub-domains, also interlink. There’s descriptive (which summarises and describes), predictive (which predicts future trends and events), causal (which identifies the relationships between variables – i.e. X causes Y) and prescriptive (an advanced type of data that recommends how to move forward).


Without data of whatever type, AI can do nothing. The relationship is arguably reciprocal too: for AI has in many ways given our data a real purpose. It’s no wonder, then, that the volume of data we’re generating, consuming, copying and storing worldwide is already 60 times higher than it was in 2010.


And while some teams in travel are keeping their heads in the sand around just how influential our data (and therefore AI) can be in today’s market, to do that means missing a major opportunity. The same applies to businesses who are currently distracted by Chat GPT and its stablemates; and/or are dismissing AI overall as part of some faddish excitement.


In reality, AI is doing great things for businesses now, in various ways – though many more could stand to take advantage. And with AI tools becoming increasingly accessible and affordable to SMEs as they evolve, this is the ideal time to work towards the benefits.


In the next and final part of this miniseries, I explain how.


Mark Bush is a Director of Firebird with over two decades of experience in the travel and leisure sector, in senior IT, MD and CEO positions. In 2022, he deepened his knowledge of data science with an MSc in Business Analytics from NYU Stern.


Mark supports sector leaders to implement powerful Business Analytics and martech solutions in B2B, B2C and eCommerce, and is an expert in innovations employing MS Power BI, Tableau, Google Cloud Platform, BigQuery, GA4, Salesforce, Marketing Cloud, as well as programming in R and Python.


Learn more, and contact Firebird, at



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