Otelier Chief Product Officer Niki Johnson was recently featured in a Hotels Magazine article discussing the crucial role of AI in hospitality and how to establish the right framework for innovation. The article highlights Otelier’s pioneering approaches to leveraging AI innovation in hospitality, ensuring hotels can adopt advanced technologies to enhance guest experiences and streamline operations. Learn how Otelier is at the forefront of integrating AI solutions in the hospitality industry.
Over the next couple years, advancements in artificial intelligence (AI) will transform nearly all areas of hospitality operations, helping us run more efficient hotels and providing prescriptive guidance to drive improved strategies across the board.
Early adopters are already turning to machine learning today for automation and hoteliers who aren’t taking steps to prepare for the next generation of AI-driven hospitality risk being left behind.
Over the past few years, we’ve seen early adoption of AI and machine learning, primarily in guest communication. Web chatbots, trip planners, automated call centers, for example, are already transforming the way hotels interact with guests.
Much of this technology is machine-learning based and will get exponentially better as more advanced AI features are adopted. As we look ahead, teams managing back-office tasks and revenue management strategies will see opportunities in automated rapid decision-making open, but only if steps are taken to centralize their data and focus on building the right framework for innovation.
At its foundation, AI relies on the centralization of data used to train a model to make predictions and responses. In hospitality, there is an abundance of data that we can use to train AI models, ingesting information from our property management system, accounting system, point-of-sale system, central reservations system, booking engine and more.
While we look toward a future where AI is informing all our business decisions, taking steps to centralize this data today is critical to ensure we are building the right framework for innovation.
AI in BI
The ability of today’s business-intelligence tools to centralize data from all areas of the business and serve it up in a user-friendly format to inform decisions is incredibly powerful. Moving our data and software to the cloud has paved the way for easier and increased data centralization through advancements in areas like Integration Platform as a Service (iPaaS) and central data warehouses, such as Snowflake.
Now, rapid adoption of generative AI models, such as Large Language Models (LLMs) and Generative Pre-trained Transformers (GPTs), and continued adoption of analytical AI models, are enhancing the business intelligence discipline by providing a next level of analysis. Instead of simply serving up descriptive analytics, next-generation tools will decipher and analyze the relevant information for you and either serve up a recommended action or automatically take the next steps.
What kind of actions could we see AI taking for us?
- Anomaly detection. Was your food cost or labor cost abnormally high this week? Did your booking engine experience a spike in conversions? AI systems can detect those anomalies, alert the hotelier, highlight the necessary information and then recommend a suggested course of action.
- Turning data to prescriptive insights. OK, you’ve got a pretty dashboard—what specifically should you be looking at? AI will analyze reports and dashboards and generate actual insights, pinpointing areas to adjust and improve strategy.
- Conversational data. Can you ask your data questions? AI assistants provide the opportunity to send messages with questions about the data in reports and automatically receive insights and next-step suggestions in text format.
The evolution of AI has driven a shift in the type of data we consume today, from descriptive analytics to predictive analytics to prescriptive analytics. Descriptive analysis primarily focuses on summarizing historical data to understand past trends and events. Predictive analysis takes this a step further by using AI models to make predictions based on patterns found in historical data. Finally, prescriptive analysis harnesses AI to not only predict future scenarios but also recommend the best actions to achieve desired outcomes.
Read the full article on Hotels Magazine to explore how AI innovation in hospitality can transform your business.
