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AI Observatory · Italian tourism

Wave of September 1, 2026

Who tells Italy's story when AI answers.

2,804 questions · 5 engines · 70,095 answers

Italy

DMO
50%
of answers cite at least one DMO +0.3
Hotel
9%
of answers cite a hotel's own site −0.1
OTA
35%
of answers cite an OTA −1
Other sources
78%
of answers cite guides, media, blogs −1.3

out of 70,095 answers

Out of 100 cited sources

  • DMO13%
  • Hotel2%
  • OTA15%
  • Other sources71%

Other sources, 71%: of which

Item by item, out of all cited sources: together they add up to the other sources' share. Next to each, the most cited sites.

  • Newspapers and magazines15%Idealista · Corriere della Sera · Travel365
  • Maps and apps13%Google Maps · Komoot · Wanderlog
  • Travel blogs10%Lorenzo Taccioli · Villages Italy · Milazzo Life
  • Private tourism portals8%Visit Italy · Italia-Italy.org · Turismo Abruzzo (eJamo)
  • Transport and services5%Spiagge.it · Telepass - Moveo · Italo
  • Social and video5%YouTube · Facebook · Instagram
  • Attractions and activities4%
  • Guidebooks and encyclopedias3%Touring Club Italiano · Wikivoyage · Lonely Planet
  • Institutions and associations3%Ministero della Cultura · I Borghi più belli d'Italia
  • Unclassified2%
  • Real estate and holiday homes<1%
  • Hotel listings<1%

Category by category

1ª2ª3ª
SeaSardegna 68%Sardegna TurismoSicilia 65%Italia.itToscana 58%Visit Tuscany
MountainsTrentino-Alto Adige 84%Visit TrentinoVeneto 60%Italia.itValle d'Aosta 56%Love VdA
LakesLombardia 86%Italia.itPiemonte 58%Italia.itTrentino-Alto Adige 45%Visit Trentino
VillagesToscana 60%Visit TuscanySicilia 60%Italia.itLazio 53%Visit Lazio
CitiesToscana 99%Visit TuscanyVeneto 98%Italia.itLazio 96%Italia.it
SnowTrentino-Alto Adige 86%Visit TrentinoValle d'Aosta 74%Love VdALombardia 66%Italia.it
The region in generalToscana 85%Visit TuscanyVeneto 72%Italia.itCampania 69%Italia.it

Method in short

Every month we ask the same set of {questions} travel questions to AI engines with web search: ChatGPT, Perplexity, Copilot, Grok and Gemini.

Each question is asked several times on every engine: {answers} answers in this wave. The answers become a single value, so model randomness is not mistaken for change.

Every question comes from a real Google search: together, their keywords add up to {searches} searches a year.

For every answer we look at two things: who is named (destinations, hotels) and who is the source (the links cited), split into DMO, Hotel, OTA and Other.

Every month rankings are compared with the previous month's, on shared questions only: the ± next to each number is that change.

The full method