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From Messy Data to Miracles: How Hotels Are Making AI Work for Them
Hotels must prioritize clean, centralized data and clear goals for effective AI use. Staff training and experimentation boost engagement and unlock AI’s real potential in hospitality.
From Dirty Data to Performing Miracles: Hotel Approaches to AI
Travel companies across all segments face challenges with artificial intelligence (AI) advancements. Key questions include which AI use cases make sense, whether data is centralized and clean enough for insights, the reliability of AI outputs, and the choice of large language models. The consensus among experts is clear: embrace AI thoughtfully, set boundaries, and encourage staff experimentation.
Balancing Enthusiasm and Caution
Some in the hotel industry believe AI could replace human roles, while others prefer a cautious approach. Matthijs Welle, CEO of Mews, shared that AI can work wonders if hotels engage fully with it. Initially, adoption was low, but after focused training, usage and engagement rose significantly.
Mews offers hotels AI-generated, concise insights on guest history and preferences to boost upselling and personalized experiences. However, Welle emphasizes that data alone isn’t enough. Teams must actively discuss how to act on these insights to see real change—a conversation many hotels have yet to start.
The Foundation: Clean, Centralized Data
Data quality remains a hurdle. Bryson Koehler, CEO of Revinate, highlights that incoming hotel data often requires extensive cleansing, which is crucial before AI can be effective. AI can assist in cleaning data and augment marketing and front-desk operations, but success depends on starting with reliable data.
Internal Adoption and Experimentation
Adopting AI tools internally is still early stage. Welle noted that even with powerful tools like Glean, about 20% of employees hadn’t logged in after a month. Experimentation includes internal policy bots and training aids, while consumer-facing applications, such as chatbots for booking and payments, are being tested selectively by brands like 25hours.
Valerie Parkes from Choice Hotels stresses the need for training to increase comfort and engagement with AI. Large organizations face additional challenges around security and legal concerns. Choice Hotels carefully evaluates the timing and value of AI investments, ensuring initiatives align with clear outcomes rather than chasing trends.
Continuous Experimentation in the Industry
Carlo del Mistro of Ennismore confirms most hospitality companies remain in pilot phases. Internal tools for staff support and training are common, while customer-facing AI is tested on smaller scales to avoid disruptions. This approach allows quick rollback if needed, reducing risk while exploring AI's potential.
Creating a Culture That Embraces Innovation
Technology adoption depends on clarity around goals and processes. Parkes points out that technology won’t solve problems if outcomes and workflows aren’t defined first. Passionate employees should be empowered as AI champions, demonstrating benefits and encouraging wider adoption. Mews often pilots with forward-thinking general managers who then share success stories.
Koehler emphasizes ease of use as critical for adoption, especially as staff face increased workloads. He also notes that labor and operational costs are unlikely to decrease, making AI adoption a practical response to ongoing industry pressures.
Where Hotels Should Start with AI
Hotels should shift focus from technology itself to defining clear outcomes and processes. Understanding what they want to achieve allows them to select and apply AI tools effectively. Without this foundation, AI won’t deliver value.
For hospitality professionals interested in learning more about practical AI applications, resources like Complete AI Training offer courses that break down AI tools and techniques relevant to the industry.