Tourism organizations are not facing the imminent disappearance of their core business. A study published by ADN Tourisme and Afdas shows instead a shift in tasks towards verification, data management, and visitor interaction. This finding should be considered within the context of a qualitative survey conducted with a limited number of organizations.
Published in February 2026 and conducted by Matrice, the study focuses on the effects of generative artificial intelligence in destination management organizations (DMOs). This category includes tourist offices, departmental agencies, and regional organizations.
The work is based on a literature review, 22 semi-structured interviews conducted between August and October 2025, and three forward-looking workshops held in November. The professionals interviewed work in several organizations, including Serre-Ponçon Tourisme, Calvados Attractivité, the Beaune Tourist Office, Charentes Tourisme, ART Grand Est, and the Kaysersberg Valley Tourist Office.
Summary
A qualitative study, not a measurement of the entire sector
The methodology allows for the documentation of uses and perceptions from the field. However, it does not constitute a representative survey of all French tourism organizations.
It would therefore be excessive to conclude that all professions are protected or that all DMOs already use AI in the same way. On the contrary, the report observes fragmented, often experimental practices, more prevalent in communication, web development, marketing, and project engineering.
The study describes a shift in work towards verification, contextualization, and arbitration. The observed uses mainly concern certain tasks, such as writing, translation, or summarizing, without revealing a massive disappearance of professions in the sample studied.
AI replaces some tasks, but not the observed functions
In the structures studied, generative AI is mainly used to prepare first drafts of texts, reformulate content, translate, synthesize documents or search for information.
The authors do not observe a massive substitution of jobs. They describe a partial automation of isolated tasks, followed by human work of control, correction and contextualization.
This conclusion relates solely to the practices observed at the time of the survey. It does not allow for predictions regarding future staffing levels or the budgetary decisions of each organization.
Visitors are already asking tourist offices to verify the AI
Several professionals interviewed reported receiving visitors with AI-generated itineraries, recommendations, or images. Some of the content presented was said to be inaccurate, decontextualized, or not corresponding to the actual territory.
The study concludes that the role of the receptionist has evolved. The advisor no longer systematically produces the initial information, but intervenes more to confirm, correct, or adapt it to local conditions.
These situations are reported in the interviews. However, the document provides no measure of their frequency at the national level.
The main area of focus concerns tourism data
The report places data quality and governance at the heart of the transformation. The difficulties identified include duplicate data entry, unsynchronized databases, the lack of APIs, different repositories, and the sharing of responsibilities between data producers and managers.
The authors also distinguish AI from more traditional automation needs. Some difficulties attributed to artificial intelligence could actually be addressed through improved interoperability between tourism information systems.
For tourism organizations, the challenge is therefore as much about ensuring the reliability of schedules, prices, access conditions and service provider information as it is about choosing a new generative tool.
Three scenarios, but two different horizons
ADN Tourisme publicly presents three scenarios for 2030. Afdas and the detailed summary, however, place them at 2028. The official documents therefore use two different deadlines.
The first scenario relies on structured data and shared standards. The second describes a fragmentation of initiatives and increased dependence on private platforms. The third envisions selective adoption, based on ad hoc collaborations and unequal resources.
These scenarios are not forecasts. They are forward-looking tools intended to inform the decisions of tourism organizations.
Recommendations addressed to leaders
The study recommends starting with internal uses considered to be low risk, including summarizing, translating, formatting and preparing drafts.
For content intended for the public, it recommends human review, source identification, and stricter controls on sensitive information. It also suggests formalizing a usage charter, appointing an AI and data expert, and recognizing the time spent on validation.
The report therefore does not conclude that AI will have no impact on employment. Its findings are more precise: in the sample studied, it is currently transforming certain tasks without eliminating the observed jobs. The ability of tourism organizations to maintain their role will depend primarily on their organizational choices, training programs, and data governance.
Article published on July 23, 2026, based on official documents available at that date.
Sources
- https://www.adn-tourisme.fr/etude-ia-metiers/
- https://observatoires.afdas.com/actualites/organismes-de-tourisme-impact-de-lia-sur-les-metiers
- https://observatoires.afdas.com/sites/default/files/document-ressource/Impacts_IA_metiers_tourisme_OGD_ADN_Tourisme_Afdas_Rapport_2026.pdf
- https://observatoires.afdas.com/sites/default/files/document-ressource/Impacts_IA_metiers_tourisme_OGD_ADN_Tourisme_Afdas_Synthe%CC%80se_2026.pdf
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