AI agents are reshaping travel planning, challenging DMOs to adapt as AI-driven search, marketing and booking redefine the visitor experience.
As AI agents evolve from simple assistants to autonomous decision-makers, they're reshaping how travellers research, plan and book holidays. This fundamental shift, accelerated by developments like AI Overviews and more recently OpenAI's Operator, challenges destinations to rethink their strategies as AI intermediaries increasingly shape the visitor cycle. Here at the Digital Tourism Think Tank, we believe AI systems will be the new gatekeepers of destination marketing. Not only is AI search increasingly driving traffic to websites, but Google is also powering AI-assisted advertising to maximise campaign performance. 97% of travellers want a travel superapp and the majority of our panel of destination experts agree that delegated discovery will be a lasting trend that will disrupt the tourism industry. With ChatGPT integrations powering many DMOs' conversational marketing assistants, it may not be too long before agentic AI developments migrate across into interactions on destination websites.
While social media will always remain key for inspiring travellers, generative AI is showing signs of replacing search engine traffic in the research phase. Growing at 35% annually, the AI market for the tourism industry is predicted to reach $10 billion by 2033. Reducing the amount of time needed to decide on a holiday, it is highly likely that microvacations and weekend breaks will become more popular as booking spontaneous trips becomes much simpler with agentic AI doing the majority of the trip planning legwork. With AI agents rising in prominence, DMOs must remain vigilant about how interaction on their website changes and be ready to quickly adjust their digital content strategies. There may soon be fewer "visits" and more "agents" visiting sites, which will have implications for how websites and content are designed and optimised. Technologies for streamlining agent-to-agent communication are resulting in more efficient communication between different agentic AI tools, with the recent launch of GibberLink for AI voice agents speeding up data transmission by 80%.
As agentic AI is not a like-for-like replacement for search engines, it remains to be seen to what extent AI will dominate travel decision-making on a large scale. Anecdotal evidence suggests that the uptake of conversational marketing tools can be relatively low when chatbots have been installed on DMO websites. Despite booking trips often being a stressful experience, travellers do enjoy researching where they'll spend their precious holiday time with family and friends. With the widespread knowledge that AI can make mistakes, we foresee that travellers will, for the moment, continue to undergo extensive research for longer holidays. This will be particularly true for important decisions like destination and hotel choices, while the activities and experiences sector may be more susceptible to AI's influence.
Demographic and cultural differences are major considerations in the extent of preparedness for agentic AI. Skyscanner's Horizons Spring Travel Outlook 2025 outlines that despite 92% of those aged 25-34 feeling confident about using AI for planning and booking a trip, this falls to 23% of over 65s. Given this broad spectrum, only 47% of travellers currently feel prepared for AI's emerging role in enabling delegated discovery. While there are competing accounts of the readiness of different segments to use AI for booking a holiday, a hybrid approach is likely to be required for the next couple of years as travellers become accustomed to the benefits of using agentic AI.
While AI agents are able to conduct tasks autonomously, it remains to be seen the extent to which they can reflect a visitor's emotions. Transforming an algorithm into a meaningful and personalised interaction is something that will take time to perfect. This will most likely bring additional implications in terms of data privacy, requiring travellers to give access to their search history and past holiday preferences to give the most accurate results. In doing so, the role of generative AI now needs to move away from being used for attracting PR value to prioritising functional applications. With this in mind, focusing on the user experience and designing an intuitive web interface must become a stronger priority before launching a new AI-enabled solution. A couple of bad experiences will be all it takes for trust to be lost in the potential of AI's expanding capabilities and travellers to be dissuaded from using these new personalised recommendation engines.
Complementing the importance of user-centric design, psychographic research will be a vital asset in fully understanding user behaviour when interacting with AI agents. Good prompting skills are necessary to avoid homogenous recommendations and algorithms need to adapt to real-life scenarios. Careful prompting architecture is required to fully understand the subtleties of a traveller's enquiry to avoid any potential misinterpretation. While many conversational marketing tools already have suggestions, these tend to be quite generic and lack individual personalisation. However, as travellers gradually adapt to the influence of generative AI across many aspects of their lives, they will learn to balance integrating the efficiency of AI with real-life human interaction, connection and authenticity. Even now, 90% of travellers want instant responses, with 61% placing more value on receiving an AI response than waiting to interact with a human agent.
Much like how the iPhone redefined travellers' digital interactions, the use of AI agents will gradually become standard practice. In taking a longer-term outlook and understanding how travellers actually use agentic AI, this technology will likely evolve further, potentially with tailored modes for different industries. For travel enquiries, this might mean receiving suggestions based on an in-depth understanding of a traveller's personality and interests based on previous interactions or introducing the ability for collaborative searches where groups can use an AI agent to design an itinerary that reflects their mutual desires, offering split payment options to streamline the travel purchasing journey.
DMOs must remain alert to travellers' changing search patterns and find new ways to share high-quality, verifiable and up-to-date information. DMOs, ultimately, remain responsible for ensuring that their unbiased content can be accessed by external AI agents. With most DMOs focusing on highlighting hidden gems and visitor dispersion, prioritising the feeding of such content to the major AI platforms will provide an innovative solution to the challenge of overcrowding, enabling a greater degree of personalisation and opening new narratives. At face value, this approach may be detrimental to website traffic, but it will enable greater visibility of trustworthy destination information and support the dissemination of destination storytelling to a wider audience. Potentially, as the rapid advancement of generative AI continues, there could even be opportunities for focused retargeting campaigns, whereby DMOs can run data-driven marketing campaigns for travellers who have been exposed to a destination within their AI search results. As an area of considerable focus, it's clear that with iterative agentic AI developments continuing to be released, destination marketing metrics will need to evolve to fully account for generative AI's growing role in influencing travel decisions.
Understanding the changing patterns of web traffic and the extent to which this traffic comes from autonomous AI agents will be crucial for decision-making. Since the launch of AI-driven search, some websites have seen their organic traffic decline by up to 30%. Such a statistic may make some question the future of the destination website. However, the relevancy of DMO websites may even be strengthened by becoming the focal point for a destination's digital presence and a much-needed platform to enable AI recommendations for prospective travellers. With changing search patterns, SEO is only likely to become more important as AI agents will prioritise scraping content from the top-ranked sites. DMOs will therefore need to find ways to understand which searches are driving visitors to their websites, particularly given that this traffic is less transient and will now predominantly be in the middle of the purchasing funnel. On the other hand, smaller destinations may need to establish partnerships with their neighbours in order to avoid being overlooked and work together to highlight their joint assets and overarching touristic appeal.
Despite the potential of agentic AI, DMOs should avoid getting stuck in the AI hype and rushing to incorporate this technology at the centre of their strategies. This is necessary for creating value for both visitors and the wider destination ecosystem. From a visitor perspective, the implications of agentic AI must be fully evaluated, from how localised content for different segments can appear in searches to the impact of server capacity constraints from AI scraping and how it affects website load times. The adoption of agentic AI also requires DMOs to rethink how they report on the value of their work for tourism businesses and local stakeholders and identify how to communicate the impact of AI recommendations. With AI agents leading to the research and booking phases blending together, the development of this technology presents a strong opportunity for DMOs to build upon their role in sharing factual and inspiring information and shift their priorities towards driving conversion.
As AI agents evolve from simple assistants to autonomous decision-makers, they're reshaping how travellers research, plan and book holidays. This fundamental shift, accelerated by developments like AI Overviews and more recently OpenAI's Operator, challenges destinations to rethink their strategies as AI intermediaries increasingly shape the visitor cycle. Here at the Digital Tourism Think Tank, we believe AI systems will be the new gatekeepers of destination marketing. Not only is AI search increasingly driving traffic to websites, but Google is also powering AI-assisted advertising to maximise campaign performance. 97% of travellers want a travel superapp and the majority of our panel of destination experts agree that delegated discovery will be a lasting trend that will disrupt the tourism industry. With ChatGPT integrations powering many DMOs' conversational marketing assistants, it may not be too long before agentic AI developments migrate across into interactions on destination websites.
While social media will always remain key for inspiring travellers, generative AI is showing signs of replacing search engine traffic in the research phase. Growing at 35% annually, the AI market for the tourism industry is predicted to reach $10 billion by 2033. Reducing the amount of time needed to decide on a holiday, it is highly likely that microvacations and weekend breaks will become more popular as booking spontaneous trips becomes much simpler with agentic AI doing the majority of the trip planning legwork. With AI agents rising in prominence, DMOs must remain vigilant about how interaction on their website changes and be ready to quickly adjust their digital content strategies. There may soon be fewer "visits" and more "agents" visiting sites, which will have implications for how websites and content are designed and optimised. Technologies for streamlining agent-to-agent communication are resulting in more efficient communication between different agentic AI tools, with the recent launch of GibberLink for AI voice agents speeding up data transmission by 80%.
As agentic AI is not a like-for-like replacement for search engines, it remains to be seen to what extent AI will dominate travel decision-making on a large scale. Anecdotal evidence suggests that the uptake of conversational marketing tools can be relatively low when chatbots have been installed on DMO websites. Despite booking trips often being a stressful experience, travellers do enjoy researching where they'll spend their precious holiday time with family and friends. With the widespread knowledge that AI can make mistakes, we foresee that travellers will, for the moment, continue to undergo extensive research for longer holidays. This will be particularly true for important decisions like destination and hotel choices, while the activities and experiences sector may be more susceptible to AI's influence.
Demographic and cultural differences are major considerations in the extent of preparedness for agentic AI. Skyscanner's Horizons Spring Travel Outlook 2025 outlines that despite 92% of those aged 25-34 feeling confident about using AI for planning and booking a trip, this falls to 23% of over 65s. Given this broad spectrum, only 47% of travellers currently feel prepared for AI's emerging role in enabling delegated discovery. While there are competing accounts of the readiness of different segments to use AI for booking a holiday, a hybrid approach is likely to be required for the next couple of years as travellers become accustomed to the benefits of using agentic AI.
While AI agents are able to conduct tasks autonomously, it remains to be seen the extent to which they can reflect a visitor's emotions. Transforming an algorithm into a meaningful and personalised interaction is something that will take time to perfect. This will most likely bring additional implications in terms of data privacy, requiring travellers to give access to their search history and past holiday preferences to give the most accurate results. In doing so, the role of generative AI now needs to move away from being used for attracting PR value to prioritising functional applications. With this in mind, focusing on the user experience and designing an intuitive web interface must become a stronger priority before launching a new AI-enabled solution. A couple of bad experiences will be all it takes for trust to be lost in the potential of AI's expanding capabilities and travellers to be dissuaded from using these new personalised recommendation engines.
Complementing the importance of user-centric design, psychographic research will be a vital asset in fully understanding user behaviour when interacting with AI agents. Good prompting skills are necessary to avoid homogenous recommendations and algorithms need to adapt to real-life scenarios. Careful prompting architecture is required to fully understand the subtleties of a traveller's enquiry to avoid any potential misinterpretation. While many conversational marketing tools already have suggestions, these tend to be quite generic and lack individual personalisation. However, as travellers gradually adapt to the influence of generative AI across many aspects of their lives, they will learn to balance integrating the efficiency of AI with real-life human interaction, connection and authenticity. Even now, 90% of travellers want instant responses, with 61% placing more value on receiving an AI response than waiting to interact with a human agent.
Much like how the iPhone redefined travellers' digital interactions, the use of AI agents will gradually become standard practice. In taking a longer-term outlook and understanding how travellers actually use agentic AI, this technology will likely evolve further, potentially with tailored modes for different industries. For travel enquiries, this might mean receiving suggestions based on an in-depth understanding of a traveller's personality and interests based on previous interactions or introducing the ability for collaborative searches where groups can use an AI agent to design an itinerary that reflects their mutual desires, offering split payment options to streamline the travel purchasing journey.
DMOs must remain alert to travellers' changing search patterns and find new ways to share high-quality, verifiable and up-to-date information. DMOs, ultimately, remain responsible for ensuring that their unbiased content can be accessed by external AI agents. With most DMOs focusing on highlighting hidden gems and visitor dispersion, prioritising the feeding of such content to the major AI platforms will provide an innovative solution to the challenge of overcrowding, enabling a greater degree of personalisation and opening new narratives. At face value, this approach may be detrimental to website traffic, but it will enable greater visibility of trustworthy destination information and support the dissemination of destination storytelling to a wider audience. Potentially, as the rapid advancement of generative AI continues, there could even be opportunities for focused retargeting campaigns, whereby DMOs can run data-driven marketing campaigns for travellers who have been exposed to a destination within their AI search results. As an area of considerable focus, it's clear that with iterative agentic AI developments continuing to be released, destination marketing metrics will need to evolve to fully account for generative AI's growing role in influencing travel decisions.
Understanding the changing patterns of web traffic and the extent to which this traffic comes from autonomous AI agents will be crucial for decision-making. Since the launch of AI-driven search, some websites have seen their organic traffic decline by up to 30%. Such a statistic may make some question the future of the destination website. However, the relevancy of DMO websites may even be strengthened by becoming the focal point for a destination's digital presence and a much-needed platform to enable AI recommendations for prospective travellers. With changing search patterns, SEO is only likely to become more important as AI agents will prioritise scraping content from the top-ranked sites. DMOs will therefore need to find ways to understand which searches are driving visitors to their websites, particularly given that this traffic is less transient and will now predominantly be in the middle of the purchasing funnel. On the other hand, smaller destinations may need to establish partnerships with their neighbours in order to avoid being overlooked and work together to highlight their joint assets and overarching touristic appeal.
Despite the potential of agentic AI, DMOs should avoid getting stuck in the AI hype and rushing to incorporate this technology at the centre of their strategies. This is necessary for creating value for both visitors and the wider destination ecosystem. From a visitor perspective, the implications of agentic AI must be fully evaluated, from how localised content for different segments can appear in searches to the impact of server capacity constraints from AI scraping and how it affects website load times. The adoption of agentic AI also requires DMOs to rethink how they report on the value of their work for tourism businesses and local stakeholders and identify how to communicate the impact of AI recommendations. With AI agents leading to the research and booking phases blending together, the development of this technology presents a strong opportunity for DMOs to build upon their role in sharing factual and inspiring information and shift their priorities towards driving conversion.
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