Three Real-World Examples of How AI Can Streamline Hospitality Workflows

This article is part of HN Thematics

Over the last few years, the two things the hospitality industry has learned to count on are uncertainty and change. As a result, organizations need adaptability and resilience to navigate this highly dynamic world, and their people are the foundation for both. As environments change, so do business priorities, and effective organizations will position their people to adapt on the fly. This requires employees and business leaders to have the relevant insights and tools to develop the critical skills they need. Hospitality companies are turning to AI to streamline workflows, helping to minimize complex or time-consuming efforts and empower employees to allocate more time to value-driven tasks.

In our last post Four Ways AI Can Transform the Hospitality Consumer Experience, we touched on how AI can simplify operational tasks and refine staffing efficiency. Here are three real-world and in-production examples of the application of AI in operations, and how it can drive value for the hospitality organization.

1. Complete performance reviews more quickly

In this time of employee churn in the hospitality industry, keeping valued employees becomes imperative, but managers can’t always take the time to create meaningful feedback for those employees. The assisted authoring function of generative AI can help create a performance review summary by analyzing multiple data sources to help uplift performance conversations

2. Provide better service

Consumers are becoming accustomed to more targeted services, but delivering those services isn’t always easy. Disparate data sources can be hard to search, and they can make it difficult for employees to provide the kind of service consumers expect. With generative AI, service agents can quickly and easily create content, which can help improve productivity while providing appropriate service responses.

3. Understand candidate credentials more easily

In addition to keeping employees, hotels need to hire qualified employees, but it’s not always easy to sort through candidate data. The summary function of generative AI can produce a concise summary that describes a candidate’s capabilities and attributes for a position.

What genAI capabilities are at work here?

The first example used assisted authoring: with just a short prompt, generative AI capabilities can quickly create content, such as job or new product descriptions, for review, revision, and approval.

The second example used suggestions: using natural language processing and best practices to quickly guide users to better results. Generative AI can also offer recommendations for survey questions or professional development tips for managers to provide to employees. For example, a customer service application can suggest a how-to article based on the customer’s inquiry.

The third example used summarization: Increasing efficiency by identifying key insights from one or more data sources. New generative AI capabilities can explain the key elements of content for simple and impactful consumption. For example, a customer service agent can ask for a summary of a knowledge base article to resolve a customer service inquiry or deliver a concise text summary from a table or chart.

The AI use cases here represent just the tip of the iceberg, as there are myriad applications for these technologies that can be applied throughout specific industries such as hospitality, and across common areas such as human resources and customer services.

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