By Andrew Rubinacci, Chief Advisory Officer of FLYR for Hospitality
If I had a dollar for every time I heard artificial intelligence or “AI” mentioned over the last year, well, you know the rest of that saying. And much like when you repeat a word so many times, it starts to lose its meaning – the discussions surrounding the blistering proliferation of artificial intelligence technology have begun to lose some of their impact. Working within the realm of hospitality technology, I understand – rather intimately – the transformative effect of digital tools that leverage the power of AI and machine learning (ML).
But I am also acutely aware that a certain fervor begins to sweep across the masses at key inflection points for the widespread adoption of new technology. Often, being an “early adopter” of anything new and untested feels precarious and high-risk, but being a “late adopter” of something that promises to change the way we live and work feels equally (if not more) damning. No one wants to be late to the party of the century, and in moments like this, it feels as though every business owner is trying to squeeze through the door simultaneously.
Within the world of hospitality – more specifically, hospitality technology – we are now seeing an influx of platforms that promise to wield the power of AI to unlock new levels of efficiency, profitability, and guest connection. The subsequent platform landscape is exciting for any hospitality brand in the market for a technology upgrade or overhaul – but it’s also overwhelming. What distinguishes one AI platform from the next? Beyond the buzzword, what does it mean to be “AI-powered”? What does it mean to be “AI-native,” also known as AI-first? Are all AI-powered platforms created equal?
The development process
AI-native platforms are built from the start, with AI as a critical component. This ensures that all platform features make the most out of AI, from its foundation to how it interacts with users. This complete integration of AI makes the platform more productive and easy to use.
In comparison, traditional systems are first developed without AI. If AI is added later, it generally requires significant changes, which can cause compatibility problems and service interruptions. Also, since the system wasn’t initially designed for AI, it might not utilize AI’s full potential.
AI-native platforms also focus on data. Since AI significantly depends on data for learning and functioning, these platforms are made to handle a lot of data efficiently. This stands out from traditional systems, which often have a hard time managing the data load that AI needs.
Also, the development of AI-native platforms is a continuous process. AI constantly learns and gets better with time, so the platform never stops evolving. In contrast, traditional systems are typically built all at once, with upgrades released as separate versions.
Lastly, building AI-native platforms usually involves a team of varied experts, such as data scientists, AI specialists, and software engineers. This team effort ensures the platform is fine-tuned for AI in every direction. In traditional systems, the development team usually lacks such a wide range of expertise.
What differentiates AI-first platforms from traditional system upgrades?
An AI-native platform is designed with artificial intelligence at its core, making it inherently more capable than traditional systems that incorporate AI as an afterthought. This increased capability stems from leveraging machine learning algorithms from the get-go, enabling them to continually learn, adapt, and improve. While AI can be effectively leveraged in many different ways, an undeniable advantage exists in a system specifically designed to fully exploit AI’s potential. AI is seamlessly integrated into every aspect of these platforms, from architecture to user interface, to enhance efficiency and effectiveness.
In simpler terms, an AI-first platform is similar to a custom-built house, with all the precise finishes, functionality, and add-ons you wanted—right from the start, rather than renovating an existing structure after the fact. After all, extensive renovations can be challenging, especially when the original structure was never built with those features in mind. Similarly, traditional systems are typically developed without AI in mind, and, as a result, when AI is later added, significant modifications to the existing system are often required.
Here are the top 5 advantages of an AI-first platform:
1. An enhanced user experience
We know that the cornerstone of any great app is a great user experience. Fortunately, an AI-native platform has AI functionality baked into its DNA and, as a result, offers a more cohesive and intuitive user interface that learns from user behavior and preferences to unlock new levels of personalization.
Moreover, users benefit from smoother workflows, enhanced predictive analytics, intelligent automation, and adaptive features that cater to an individual’s needs and preferences to meaningfully enhance productivity and user satisfaction, which, in turn, helps eliminate barriers to adoption.
2. Advanced data insights and decision intelligence
When extracting meaningful, actionable insights from vast amounts of data, AI-native platforms are in a league of their own. By leveraging sophisticated algorithms, they can provide accurate decision intelligence rather than just recommendations, empowering hoteliers with actionable insights that drive revenue growth and competitive advantages.
3. Faster integration and ecosystem connectivity:
AI-native platforms also help to eliminate any concerns regarding data integration challenges. Unlike traditional platforms, which are often weighed down by data silos and may struggle to handle large amounts of data, these systems are designed to seamlessly and efficiently collect, process, and analyze large volumes of data. And in the world of hospitality, data is a precious currency.
These platforms are designed to seamlessly integrate with other software systems and third-party applications, creating a connected ecosystem that enhances interoperability and data exchange. Whether integrating with property management systems, channel managers, or guest feedback platforms, the interoperability ensures that hotels can leverage the full potential of their technology stack and unlock new opportunities for innovation and growth.
4. Continuous improvement through machine learning:
To stay ahead of ever-changing guest preferences and industry trends, hospitality brands must invest in technology that makes their property more agile and adaptable. One of the critical advantages of AI-first technology is its ability to continuously learn and adapt to changing conditions while providing the flexibility and agility that traditional systems lack. Through machine learning algorithms, these platforms analyze feedback, performance data, and market trends to refine their recommendations and predictions over time. This iterative process of improvement ensures that AI-native platforms remain relevant and effective in a constantly changing and hyper-competitive landscape.
5. A cost-effective, future-proof solution
Platforms built from the ground up using AI are more robust, intuitive, and scalable and tend to be more cost-effective in the long run. While the initial development costs may be higher, the efficiencies and robust capabilities they offer can result in significant cost savings over time. On the other hand, traditional systems often incur additional costs for upgrades and maintenance, particularly when attempting to integrate AI after the system has already been built.
Everyone is talking about it for a reason – the next frontier of exceptional hospitality service is undeniably powered by AI, and the time to adopt AI-native technology is now. With the right investments into the right technology, hospitality and travel brands can gain the agility to scale and the foresight to adapt to whatever the market demands – and come out on top.
