Following tourism and hospitality developments means keeping track of several connected sectors. Changes in airline connectivity, hotel investment, visitor demand, government policy, and destination management can all affect how the industry operates. Relevant information is spread across specialist publications, research firms, and international organisations, making regular monitoring a time consuming task.

The AI Learning Centre (AILC) has developed an automated tourism intelligence workflow that brings these updates into a single briefing. The system collects articles from multiple sources, evaluates their significance, groups related coverage, and prepares concise summaries for university staff and students. The completed briefing is delivered by email and published to a dedicated webpage.

The Use Case: Keeping Up with a Connected Industry

Tourism reporting covers everything from major policy decisions and hotel performance data to promotional announcements and travel inspiration. For teaching and research, the challenge is selecting developments with enough substance to support a useful discussion.

An announced hotel project, for example, has different implications from a completed opening. A forecast of visitor growth also needs to be distinguished from recorded arrivals. The workflow is designed to preserve these distinctions while helping readers identify developments relevant to tourism management, hospitality operations, aviation, investment, sustainability, and regional development.

The Power of an Agentic Platform

The workflow uses an Agentic Platform to coordinate collection, article extraction, AI analysis, and publication.

Two specialised AI stages handle the editorial work. The first scores articles using a tourism intelligence framework. The second summarises the selected stories and explains their significance. Between these stages, similarity analysis reduces repeated coverage of the same event.

The process is configured to run daily, creating a repeatable monitoring routine.

Workflow Process Overview

1. Collecting Articles from Specialist Sources

The platform brings together reporting from Skift, PhocusWire, Hospitality Net, HOTELS Magazine, Travel Weekly, STR through CoStar, HVS, the World Travel & Tourism Council, and UN Tourism.

Together, these sources provide coverage of travel technology, accommodation, hotel performance, investment, tourism policy, and destination development.

The workflow combines RSS collection with website extraction, using processing steps adapted to each publication’s structure. Article text and available metadata are then brought into a common format before analysis.

A date filter excludes articles older than seven days, while some source collection steps apply narrower windows.

2. Evaluating Tourism Significance

The first AI agent assesses each article across five criteria. Each receives a score from 0 to 5, producing a total out of 25:

1. Tourism Significance: How important is the development for tourism, hospitality, aviation, accommodation, or destination management?
2. Signal Strength: Does the reporting describe a concrete development supported by facts, figures, dates, or named organisations?
3. Source Credibility: How reliable and traceable are the publication and its underlying information?
4. Practical Relevance: How useful is the development for industry awareness, research, planning, or teaching?
5. Novelty: Does the article introduce meaningful new information?

The scoring instructions give greater weight to documented developments and supported reporting. Promotional material, generic travel inspiration, and repetitive commentary are intended to receive lower scores when they lack substantial industry information.

Only articles scoring at least 17 out of 25 proceed.

3. Grouping Similar Stories

Several publications may cover the same investment, policy announcement, or market development. Including every version would make the briefing repetitive.

The platform uses AI embeddings to compare article titles and group similar stories. It retains the highest scoring article from each group and records the associated coverage.

The remaining stories are ranked by score, with mention count used to break ties. Up to ten stories then advance to summarisation.

The mention count indicates how much related coverage was collected during that run. It gives readers context about a story’s visibility across the monitored sources.

4. Producing an Educational Summary

The second AI agent writes a summary of three to four sentences for each selected story, followed by a single sentence explaining why the development matters.

The instructions focus the analysis on the article’s main event and exclude unrelated promotional material, side stories, and website navigation.

Particular attention is given to the status of reported developments. Proposed investments, planned routes, announced projects, and completed developments should be described according to their actual stage. Forecasts and stakeholder claims should remain clearly attributed.

Each story also receives a Positive, Negative, or Neutral sentiment label based on the reported event and its likely implications. Mixed or uncertain developments can be classified as neutral.

5. Delivering the Briefing

The selected stories are assembled into a formatted Tourism Intelligence Briefing, ordered by impact score.

Each entry includes the source, linked headline, summary, key takeaway, sentiment, score, and mention count where applicable. A scoring guide explains how the articles are evaluated.

The completed briefing is sent through Microsoft Outlook. The same HTML output is also used to update a dedicated report webpage, providing another way to access the selected stories.

The End Result

The workflow brings a broad collection of tourism reporting into a focused briefing for academic reading and discussion. Students and staff can review the selected developments, understand their industry relevance, and follow the original links when a story warrants closer examination.

By automating collection and initial analysis, the system reduces the manual work involved in maintaining a regular view of tourism and hospitality developments.

Click here to view the output