Foresight and innovation in
the global hotel industry

Five steps towards AI Maturity in travel & hospitality

Global Travel Industry Sector Lead, Accenture
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The travel and hospitality industry is using data and AI to maximize value from micro-moments and respond to real-time trends. Accenture's research found that AI-influenced revenue for travel companies more than doubled between 2018 and 2021 and is projected to triple by 2024. However, only 13% of travel companies surveyed by Accenture were considered AI "achievers" who are significantly ahead of the rest in using AI to reinvent core parts of the business. The majority of the industry, up to two-thirds, was underdeveloped in AI strategy and practice. Accenture identified five priority actions to build AI maturity in the industry: making AI a C-level priority, investing in AI training, building an AI core, championing responsibility, and looking at both the long- and short-term.

From capturing changing demand to pinpointing customer needs to managing revenue, today’s travel and hospitality industry is all about maximizing the value of micro-moments and responding to trends in real-time.

It’s why capitalizing on data for improved decision-making has become a critical capability in the industry. It also explains the recent growth in the use of artificial intelligence among travel and hospitality companies.

From P3’s intelligently personalized booking engines to IHG’s voice-controlled smart rooms, there’s evidence of companies across the industry embedding AI into their core business processes and customer experiences.

What’s more, Accenture’s research has shown that, collectively, travel companies’ AI-influenced revenue more than doubled between 2018 and 2021, and is projected to triple by 2024. Not only that, almost half of executives surveyed said the return on their AI investments exceeded initial expectations.

Dig a little deeper, however, and the research suggests that, while some hospitality companies are gaining a strong competitive advantage from the technology, many others in the industry are lagging behind.

Travel’s AI Achievers blaze a trail

Accenture identified a small group of “AI Achievers” that are significantly ahead of the pack when it comes to using AI to reinvent core parts of the travel and hospitality business.

That includes embedding AI in everything from pricing and marketing to revenue management and streamlined operations. Their end goal? Deliver the highly personalized experiences that travelers now demand in real-time.

However, AI Achievers make up just 13 percent of the travel companies Accenture surveyed. The research indicates there’s another 20 percent of companies are somewhat advanced in their use of AI. But that leaves a sizable majority – as much as two-thirds of the industry – that’s underdeveloped in both AI strategy and practice.

The size of this lagging group means the travel industry as a whole underperforms many other sectors in terms of average AI maturity.

This matters because companies that can’t fully leverage capabilities like machine intelligence struggle to identify relevant data and trends quickly enough to capitalize on them. Their use of outdated historical data means they risk missing out on opportunities to secure future revenue growth and improved customer experiences.

Five steps towards AI maturity

The good news? From our analysis of what makes AI Achievers tick, we’ve identified five priority actions any business can take to build greater AI maturity:

Step 1: Making AI a C-level priority

Initiatives lacking formal senior sponsorship inevitably struggle to compete for resources and attention. Most AI Achievers have executed successful AI programs by securing the support of the CEO and the entire executive suite.

Step 2: Investing in AI training

The higher the AI fluency across the workforce, the greater the return on AI initiatives. Around 70 percent of AI Achievers have mandatory AI training for employees across all levels, leadership included.

Step 3: Building an AI core

By creating an industrialized core of AI tools, teams and platforms, Achievers make it easier to integrate AI into existing solutions, increase operational efficiency, productize AI concepts faster, and deliver seamless end-to-end traveler experiences.

Step 4: Championing responsibility

AI development involves a whole range of moral, reputational and legal considerations. As a rule, Achievers look to avoid bias, protect privacy and build trust through transparency from the very start of the design process.

Step 5: Looking at both the long- and short-term

Doubling down on AI investments is essential for the long-term health of a business. But it may not be realistic for those still in a post-pandemic recovery phase. Careful prioritization can enable the business to deliver important short-term initiatives—such as a strong data foundation—without the need for a broader transformation.

Green light for travel’s race to AI maturity

Achieving AI maturity is essential for travel and hospitality companies looking to transform traveler experiences, support employees, streamline operations and become more sustainable. This will be pivotal to future growth in the post-Covid economy – both in capturing new customer segments and in recovering those lost during the pandemic.

Take Meliá Hotels which undertook a sizeable initiative in AI workforce training. Its CEO-championed AI drive saw the organization train 1,000 “change makers” to support the automation of administrative tasks and focus staff on guest service. Or Ireland-based Dalata Hotel Group’s integration with Arvoia. The latter’s AI platform allows Dalata to learn about individuals’ website behavior and so prioritize recommendations by relevance rather than price.

The group saw consistent month-on-month rises in average booking values and conversion rates as a result. Furthermore, several hotels have invested in AI-enabled food waste management systems to significantly improve reporting and data collection to further reduce food waste. Using a camera, a set of smart scales, and the same type of machine learning technology found in autonomous vehicles, the system ‘learns’ to recognize different foods being thrown away and calculates the financial and environmental cost of this discarded food to the kitchens. It then enables the hotels to adjust their food purchasing decisions accordingly.

Examples like these illustrate AI’s transformative potential across travel and hospitality. The immediate priority for companies in the industry is to acquire the AI maturity they need to lead – not follow – in that transformation.