Debunking The Myths About AI-driven Hotel Revenue Management Systems — Source: FLYR (formerly Pace Revenue)

Practically every day, AI is integrated into a new product or service. And we're not just talking about virtual assistants and search engines. AI is being embraced by businesses worldwide to optimize their processes and grow revenue, among other things.

AI has been making inroads into the hospitality industry in more ways than one. According to a report by Grand View Research, the global market for AI in hospitality is projected to reach $9.2 billion by 2025. The report attributes this growth to the increasing adoption of AI technology by hotels and resorts to improve their operations and provide better customer service. However, one central area of focus has been AI-driven revenue management systems (RMS). Organizations that use these systems have experienced their benefits first-hand: revenue growth, better customer experiences, simplified processes, etc.

Pricing strategies are a complex affair and have wide-reaching consequences. But those complexities may not be immediately apparent. Revenue management is a set of heuristics to simplify all of the issues that can arise in a very complex world because we don't have enough computational power to solve them optimally. This represents the traditional revenue management model where segment forecasting and yield management are viewed as linear processes. But that ignores the fact that once you've priced or repriced, you will have to re-forecast. And while your segments may be static, they will change based on your forecasting. So, we're actually looking at a circular motion of continuously segmenting, continuously forecasting, and continuously pricing.

AI is everywhere. And the tech is as powerful as it is polarizing. And whenever something is polarizing, you tend to hear opposing views about it, making it difficult to separate the wheat from the chaff. So that's what we're going to do in this post.

Let's start.

Myth #1:  All revenue management systems are created equal

Revenue management systems are all designed to help businesses make data-driven pricing decisions. However, their effectiveness depends on various factors, such as the quality of the data fed into the system - garbage in, garbage out, as they say.

And, it should be said that you can’t simply “tag” or retrofit AI onto an existing RMS that focuses on decision support and recommendations and call it a day. Though it may seem like a quick and easy solution for some, unfortunately, effective revenue optimization is just not that simple. One of the main reasons for this is that today’s revenue management platforms simply aren’t built to handle the quantity or complexity of the data required. Instead, they rely on static rules that are supported by algorithms.

Because FLYRs Revenue Optimization solution was built from the ground up using cutting-edge AI technology, to generate decision intelligence for better, faster insights-driven business decisions. Unlike other RMS platforms, our system is continually evaluating decision outcomes and optimizing them through a feedback system, getting smarter and better from day one! (We will have a follow up article to dive deeper into our Decision Intelligence capabilities soon).

Another critical factor will be the system's algorithmic sophistication. Revenue management systems that leverage advanced machine learning techniques will not only be able to analyze massive amounts of data but will also provide businesses with far more accurate results than systems that rely on simple rule-based approaches.

And finally, there’s customization. You know your business better than anyone (or anything) else. A proper RMS should allow organizations to tailor their pricing strategies to their own use cases and business objectives. A "one-size-fits-all" approach simply won't work for everyone.

Myth #2: Revenue management systems are only suitable for large chain hotels

Many independent lodging providers use the above as a justification for not getting on board with AI-driven RMS. But it's a misconception, to be sure. Advanced revenue management systems are just as crucial for independent hoteliers as they are for larger organizations. One could make the case that it is even more critical for smaller operators.

The latter tend to have fewer resources, highlighting the need to make every penny count. AI-driven revenue management systems can provide lodging operators of any size and type, whether large chains, luxury resorts, or limited service properties, with insight and intelligence to make optimal commercial decisions in real-time.

Myth #3: AI-driven revenue management systems will replace human revenue managers

You'll likely have heard this one since ChatGPT hit the scene late last year: AI will replace humans in the workplace. Let's be clear: AI has already replaced some jobs - mainly in customer service (where online FAQs can also "replace" human assistance). But there are still plenty of humans in call centers.

While there's no doubt AI can benefit hotel businesses, we're still far from a point where AI can be let loose unattended. Regardless of how many tricks it learned, a puppy still needs supervision. Perhaps that day will come, but it won't be tomorrow (and it may never come).

And that's particularly true in the case of AI-driven revenue management. While these systems have an astounding ability to analyze massive data sets to provide insights, human oversight, and decision-making remain critical to their effectiveness. However, automation can indeed deliver massive efficiency savings - and in some cases, properties may not need to hire a dedicated revenue manager as a result. And with the labour shortages the industry is struggling with, it’s critical to automate as many repetitive administrative functions as possible. This optimizes productivity and frees staff to focus on getting new business in the door.

Revenue management is a complex process that is about more than just data analysis. Revenue management is also about developing and implementing pricing strategies for various segments, including groups. That, in turn, requires a deep understanding of customer behavior, market trends, and business goals - all of which are rather human-centric. AI-driven systems can certainly help with the data analysis portion of revenue management, but they cannot fully replace the human expertise needed to make critical strategic decisions based on that analysis.

Wapping Up

That was an overview of some of the more prominent (and stubborn) myths surrounding AI and revenue management systems. Hopefully, we've provided a more balanced and nuanced view of what they do and how they're used.

AI-driven revenue management systems benefit all types of properties, regardless of size or niche. They're sophisticated systems that enable businesses to forecast demand and optimize their pricing strategies. And they achieve this while keeping your revenue managers in the loop.

AI-driven revenue management systems have an uncanny ability to identify patterns and trends within swaths of data to inform pricing. And you’d be hard-pressed to find an industry that wouldn’t benefit from that. AI-driven revenue management systems are THE next-generation tools that will provide hotel revenue teams with interconnected, real-time BI to enhance their decision-making process.

But, as we stated above, not all revenue management systems are created equal. They each will have their own set of strengths and weaknesses. But to get the most out of your RMS, you'll want to make sure of a few things:

  • It is built upon robust algorithms, which means an AI-driven system designed from the ground up using AI and machine learning.
  • It is easy to use for all departments and allows for fine-tuning to ensure it aligns with your property’s unique needs and business goals.
  • It delivers automation and efficiencies, enabling your staff to do more in less time.

Overall, AI is an extremely powerful tool that can be used to transform the hospitality industry. By automating tasks, personalizing experiences, and improving efficiency, AI can help hotels deliver better service, increase profits, and stay ahead of the competition.

Are you using an AI-driven revenue management system? You can learn more here.

About FLYR

FLYR is a technology company that is purpose-built for the travel industry. Leveraging deep learning, an advanced form of AI, FLYR is helping airlines, cargo, and hospitality businesses around the globe elevate their results. With FLYR, businesses are able to improve revenue performance and modernize the e-commerce experience through accurate forecasting, automation, and analytics. Learn more at For more information visit

Stephanie Normand
VP Marketing
FLYR (formerly Pace Revenue)