OCDE - Artificial Intelligence and tourism in APEC economies de 2026

Please cite this paper as: OECD (2026-09-09), “Artificial Intelligence and tourism in APEC economies: Boosting innovation and enhancing

sustainability”, OECD Tourism Papers, 2026/02, OECD Publishing, Paris. http://dx.doi.org/10.1787/4549486a-en OECD Tourism Papers 2026/02 Artificial Intelligence and tourism in APEC economies

BOOSTING INNOVATION AND ENHANCING

SUSTAINABILITY

OECD2025 D4SME Survey OECD SME and Entrepreneurship Papers Artificial Intelligence and tourism in APEC economies OECD Tourism Papers 2025 D4SME Survey OECD SME and Entrepreneurship Papers Artificial Intelligence and tourism in APEC economies OECD Tourism PapersOECD Tourism Papers

Artificial Intelligence and tourism in APEC economies Boosting innovation and enhancing sustainability

Artificial intelligence is transforming tourism, creating new opportunities to enhance visitor experiences, improve business performance, and support sustainable development, while also raising policy challenges. This paper explores the opportunities, risks and policy implications of AI adoption in tourism across APEC economies. It identifies six priority areas for policy action to support AI adoption in tourism, with particular attention to the sector's SME-dominated structure. Drawing on emerging practices across APEC economies, the paper highlights policy approaches to harness the benefits of AI while fostering a more innovative, resilient, and sustainable tourism economy.

JEL codes: Z3, Z38

Keywords: apec economies, artificial intelligence, digital transformation, innovation, sustainable tourism, tourism

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ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

ABOUT THE OECD The OECD is a multi-disciplinary inter-governmental organisation with member countries which engages

tourism

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ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

ABOUT THE OECD The OECD is a multi-disciplinary inter-governmental organisation with member countries which engages in its work an increasing number of non-members from all regions of the world. The Organisation’s core mission today is to help governments work together towards a stronger, cleaner, fairer global economy. Through its network of specialised committees and working groups, the OECD provides a setting where governments compare policy experiences, seek answers to common problems, identify goo d practice, and co-ordinate domestic and international policies. More information available: www.oecd.org.

ABOUT OECD TOURISM PAPERS This series is designed to make available to a wider readership selected studies drawing on the work of the OECD Tourism Committee (www.oecd.org/cfe/tourism). OECD Tourism papers address issues such as trends and policies, innovation, sustainability, skills and statistics . The series complements OECD tourism publications, and aims to share knowledge, stimulate discussion and analysis on specific topics and obtain feedback from wider interested audiences on specific topics. The paper was approved and declassified by the OECD Tourism Committee on 17 April 2 026 [CFE/TOU(2025)11/FINAL] and prepared for publication by the Secretariat. This paper was authorised for publication by Lamia Kamal-Chaoui, Director, Centre for Entrepreneurship, SMEs, Regions and Cities, OECD. This document, as well as any statistical data and map included herein, are wi thout prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and bou ndaries and to the name of any territory, city or area.

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© OECD 2026

Attribution 4.0 International (CC BY 4.0) This work is made available under the Creative Common s Attribution 4.0 International licence. By using t his work, you

Cover Image: Atstock Productions / iStock / Getty Images Plus

© OECD 2026

Attribution 4.0 International (CC BY 4.0) This work is made available under the Creative Common s Attribution 4.0 International licence. By using t his work, you accept to be bound by the terms of this licence (https://creativecommons.org/licenses/by/4.0/). Attribution – you must cite the work. Translations – you must cite the original work, identify changes to the original and add the following text: In the event of any discrepancy between the original work and the translation, only the text of original work should be considered valid. Adaptations – you must cite the original work and add the following text: This is an adaptation of an original work by the OECD. The opinions expressed and arguments employed in this adaptation should not be reported as repres enting the official views of the OECD or of its Member countries. Third-party material – the licence does not apply to third-party material in the work. If using such material, you are responsible for obtaining permission from the third party and for any claims of infringement. You must not use the OECD logo, visual identity or cover image without express permission or suggest the OECD endorses your use of the work. Any dispute arising under this licence shall be settled by arbitration in accordance with the Permanent Court of Arbitration (PCA) Arbitration Rules 2012. The seat of arbitration shall be Paris (France). The number of arbitrators shall be one. 3

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

This paper on artificial intelligence and tourism was produced by the OECD Centr e for Entrepreneurship, SMEs, Regions and Cities (CFE), led by Director Lamia Kamal-Chaoui, as part of the Programme of Work of the OECD Tourism Committee . The work was undertaken with the financial support of the Korean Ministry of Culture, Sports and Tourism, to support Korea’s 2025 APEC host year. This paper contributes to a better understanding of the policy implications of AI adoption in tourism by

of the OECD Tourism Committee . The work was undertaken with the financial support of the Korean Ministry of Culture, Sports and Tourism, to support Korea’s 2025 APEC host year. This paper contributes to a better understanding of the policy implications of AI adoption in tourism by identifying key opportunities and risks, highlighting emerging practices across APEC economies, and outlining priority actions to strengthen innovation, resilience, and sustainabili ty in the sector. It builds on the G7/OECD Policy Paper on Artificial Intelligence which was prepared and endorsed by G7 Tourism Ministers under Italy’s 2024 G7 Presidency. It benefitted from contributions, feedback and guidance from policymakers in APEC and OECD economies. It also benefitted from consultations and feedback from intergovernmental organisations, including UN Tourism, as well as representatives of tou rism and technology businesses, experts, academics and industry associations which parti cipated in the OECDKorea Forum on Artificial Intelligence and Tourism: Promoting innovation - enhancing sustainability held in Gyeongju, Korea on 6 February 2025 and the APEC Self-Funded Workshop on A rtificial Intelligence and Tourism on 28 July 2025 in Incheon, Korea, including: Agoda, Booking.com, D ataAppeal, Destination Vancouver, ETF Tourism Frontiers, Expedia, Globaleur, Ground K Concierge Services, GroupNAO , Gyeongju Smart Media Center, Jalan Research Centre Japan, Japan Travel Agency, Korean Culture and Tourism Institute, Korean Tourism Organization, Microsoft, NUUA Travel Tech Startup, Pacific Asia Travel Association, Sejong University, Singapore Tourist Board, Tripbtoz, Tourism Pr oductivity Nexus Malaysia, Tourism Tribe Australia, Turismo de Portugal and the University of Surrey. The paper was co-ordinated by Doyeon Kwon, Senior Policy Analyst (CFE), under the supervision of Jane

Stacey, Head of the Tourism Policy and Analysis Unit (CFE). Hannes Thees (Catholic Universität EichstättIngolstadt) drafted the paper and prepared the forum and workshop. Joshua Ryan-Saha (TravelTec h Scotland at the Edinburgh Futures Institute) provided valuable inputs and facilitat ed the workshop. Marco Bianchini, Head of the Digitalisation and AI for SMEs Unit (CFE) provided valuable feedback and inputs. Monserrat Fonbonnat, Assistant (CFE) provided administrative support and Bridgette Joyce, Publications Co-ordinator (CFE) prepared the paper for publication. Acknowledgements4 

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

Table of contents Acknowledgements 3 Executive summary 5 Artificial Intelligence and tourism in APEC economies 7

Setting the scene: Potential and challenges of AI 7

Understanding the wider AI policy environment and its implications for tourism 12 Policies to boost AI-driven innovation and enhance sustainable tourism 14 References 25 Note 26

TABLES Table 1. AI agenda and strategies in APEC economies 13 Table 2. Raising awareness of AI opportunities and risks: selected APEC examples 16 Table 3. Improving tourism data governance and business intelligence: selected APEC examples 18 Table 4. Supporting AI uptake by small and medium tourism enterprises: selected APEC examples 20 Table 5. Supporting human capital development in tourism: selected APEC examples 21 Table 6. Enhancing trust, transparency and ethical AI implementation in tourism: selected APEC examples 23 Table 7. Empowering destinations and DMOs as AI agents for co-operation: selected APEC examples 24

BOXES Box 1. Statistical insights on AI adoption in tourism in APEC economies 8 Box 2. OECD definition of AI systems 9 5

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

BOXES Box 1. Statistical insights on AI adoption in tourism in APEC economies 8 Box 2. OECD definition of AI systems 9 5

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

Artificial Intelligence (AI) is emerging as a transformative force for tourism across APEC economies. Tourism plays an important economic role in the region, supporting employment, l ocal development and international connectivity, and stands to benefit significantly from AI . However, the sector is highly fragmented, with many micro, small and medium-sized enterprises (SMEs) operati ng at varying levels of digital readiness. These characteristics shape both the opportunities and chal lenges associated with AI adoption. This paper explores how AI can drive innovation and sustainability in tourism, whil e identifying policy priorities to support effective and responsible AI adoption in the sector. Drawing on discussions from the OECD–Korea Forum on Artificial Intelligence and Tourism and APEC Self-Funded Work shop on Artificial Intelligence and Tourism in 2025, as well as inputs from APEC and OECD economies , the paper aims to help policymakers understand emerging AI applications in tourism, assess assoc iated opportunities and risks, and identify policy responses that can maximise benefits for the sector and help harness AI as an enabler of more innovative, resilient and sustainable tourism development. The paper a lso aims to foster dialogue within and across APEC economies and support AI implementation in ways that are aligned with broader economy-wide standards and priorities, building on earlier OECD work on AI and tourism, including the G7/OECD Policy Paper on AI and Tourism. AI applications are expanding rapidly across the tourism value chain. AI-powered tools are increasingly being used to personalise visitor experiences, enhance customer service, optimise operations and revenue management, strengthen forecasting, and manage visitor flows. AI-enhanced data analytics and business intelligence are improving decision-making, while generative and agentic AI are lowering barriers to marketing, content creation and service delivery, creating significant opportunities for tourism businesses,

being used to personalise visitor experiences, enhance customer service, optimise operations and revenue management, strengthen forecasting, and manage visitor flows. AI-enhanced data analytics and business intelligence are improving decision-making, while generative and agentic AI are lowering barriers to marketing, content creation and service delivery, creating significant opportunities for tourism businesses, particularly SMEs. AI can also support broader policy objectives, including to reduce seasonality, improve accessibility, strengthen crisis preparedness, support cultural heritage preservation and enhance environmental sustainability through more efficient resource use , demonstrating its potential to advance longstanding tourism policy goals through more informed and data-driven decision-ma king. Early debates around AI in tourism highlighted its promise, but as implementation progr esses, practical challenges and risks are moving to the forefront. Alongside its potential bene fits, AI adoption remains uneven, particularly among SMEs, and is accompanied by range of emerging ris ks. Algorithmic bias and poor-quality data may reinforce market imbalances and distort demand. Generative AI c an contribute to misinformation, fake reviews, and fabricated tourism offerings, undermining consumer tr ust. Agentic AI may reshape tourism distribution models by bypassing destination platforms and in dividual businesses, with implications for market visibility, competition and access to data, particu larly for SMEs. Additional concerns relate to data protection, intellectual property rights, workforce impacts and the environmental footprint of AI technologies. Without appropriate safeguards, these risks could li mit the benefits of AI adoption across the tourism ecosystem, undermine user trust, exacerbate existing digital divides between SMEs and larger firms, and leave economic potential untapped. Across the APEC region, policy frameworks vary in maturity and scope, but most sha re an emphasis on fostering innovation while promoting responsible, reliable and human-centred developme nt. Economywide AI strategies are increasingly common, and typically balance innovation an d competitiveness with responsible, regulatory and capacity-building considerations, often through publi c–private collaboration. Executive summary6 

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

wide AI strategies are increasingly common, and typically balance innovation an d competitiveness with responsible, regulatory and capacity-building considerations, often through publi c–private collaboration. Executive summary6 

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

However, dedicated AI strategies for tourism remain limited, even in economies where the sector is a major contributor to growth. This highlights the value of a more targeted policy discussion to consider the specific characteristics and needs of the tourism sector and ensure that broader AI frameworks translate into practical guidance and support for tourism stakeholders. It also reflects the need to bett er align tourismspecific actions with broader national and economy-wide AI strategies. While AI has significant potential to drive innovation, competitiveness and s ustainability in tourism , its benefits are not automatic. A coordinated and evidence ‑based policy approach is required to ensure that AI adoption in tourism delivers shared value for businesses, workers, destinations and travellers across APEC economies. T he paper identifies six priority policy areas to support AI-driven innovation and sustainable tourism development: • Raise awareness of AI opportunities and risks in tourism. Promote broad-based engagement so that tourists, businesses and destinations better understand the potential, limitati ons and implications of AI. • Improve tourism data governance and business intelligence . Strengthen data quality, interoperability and safeguards against misuse, while embedding AI into existi ng digital and data infrastructures to support informed decision-making. • Support AI uptake by tourism SMEs. Reduce structural, financial and capacity barriers through targeted support where appropriate, enabling micro, small and medium-sized businesses become key actors in tourism innovation ecosystems. • Develop tourism workforce capacity . Prepare workers for AI-driven transformation through education, training and skills development, combining AI literacy with broader ski lls that support adaptation and resilience. • Enhance trust and transparency in AI deployment. Promote responsible AI through clear governance mechanisms, while fostering innovation through cross-sectoral co-operation. • Empower destinations and DMOs as AI enablers . Enable destination management

adaptation and resilience. • Enhance trust and transparency in AI deployment. Promote responsible AI through clear governance mechanisms, while fostering innovation through cross-sectoral co-operation. • Empower destinations and DMOs as AI enablers . Enable destination management organisations to coordinate stakeholders, support AI diffusion, drive local inn ovation and adapt AI solutions to place-specific needs and priorities. 7

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

Setting the scene: Potential and challenges of AI Tourism is a vital economic sector for many APEC economies. It is also a sector facing increasing pressure to innovate, enhance competitiveness, and contribute to wider policy goals a mid global trends and challenges, including environmental, social and demographic shifts, global a nd regional tensions and digitalisation.

At the same time, Artificial Intelligence (AI) is emerging as a transformative for ce in tourism, offering unprecedented opportunities for innovation, operational efficiency, personalised servi ces, and sustainability. As the current and potential impacts of AI become increasingly ta ngible, there has been growing attention on understanding the applications and potential of AI for tourism and the opportunities and challenges it brings for the sector (UN Tourism & Saxion University of Appli ed Sciences, 2025 [1]), (WTTC, 2024[2]) (McKinsey & Company, 2024[3]) (OECD, 2024[4]). AI adoption remains uneven across the tourism sector in APEC economies (Box 1), often reflecting challenges in digital readiness, regulatory environments, and investment c apacity. Policy makers need to navigate the opportunities and risks AI presents for tourism stakeholders, and are increasingly seeking guidance on how to ensure that the broader tourism sector can access and benefit from these technologies, including small and medium-sized enterprises (SMEs). The G7/OECD Policy Paper on Artificial Intelligence and Tourism (OECD, 2024 [4]) brought a sectoral perspective to global AI policy discussions for the first time, addressing A I-specific opportunities and

including small and medium-sized enterprises (SMEs). The G7/OECD Policy Paper on Artificial Intelligence and Tourism (OECD, 2024 [4]) brought a sectoral perspective to global AI policy discussions for the first time, addressing A I-specific opportunities and challenges in tourism and the implications for tourists, workers, businesses, destinations and policymakers. Since its endorsement by G7 Tourism Ministers in November 2024, the global conversation has evolved. While early discussions centred on AI’s promise, growing experience with im plementation is bringing practical challenges and risks to the forefront. These include questions around how to tak e initial implementation steps, as well as concerns about the reliability and accuracy of AI -generated content. These trends are also recognised by the G20 tourism agenda, which, under South Afri ca’s 2025 G20 Presidency, has put people-centred AI and innovation as a priority (G20 South Africa, 2 025[5]). AI is also high on the APEC agenda and a key priority for Korea under its 2025 hos t year, following the 2024 APEC Leader’s Machu Picchu Declaration, which recognises the potential for AI to drive innovation, promote sustainable economic growth, and transform daily life across economies. APE C work on AI includes: the Recommendations Report on Supporting AI at Scale (2024), which outlines the role of international standards in scaling AI responsibly across sectors; the Artificial Intelligence Landscape in APEC (2025), which examines how economies can balance AI development with appropriate oversi ght; and the Closing the Digital Skills Gap Report (2020), which highlights the need for coordinated action to build a future-ready, digitally skilled workforce across the region. Artificial Intelligence and tourism in APEC economies8 

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

AI is also on the APEC tourism agenda, and has an important role to play in delivering on the ambition set out in the APEC Tourism Working Group Strategic Plan 2025-2029 , to champion innovation through

ARTIFICIAL INTELLIGENCE AND TOURISM IN APEC ECONOMIES © OECD 2026

AI is also on the APEC tourism agenda, and has an important role to play in delivering on the ambition set out in the APEC Tourism Working Group Strategic Plan 2025-2029 , to champion innovation through digitalisation and other new technologies and foster partnerships and promote sustai nable tourism to expand the benefits of travel and tourism to the wider APEC community and achieve econ omy growth in line with the APEC Putrajaya Vision 2024 , and its Aotearoa Plan of Action . The 2024 APEC Tourism Ministers Statement also underscores the importance of embracing technological advancements to enhance competitiveness and sustainability. This paper aims to support the APEC AI and tourism agenda, with a focus on boosting in novation and enhancing sustainability. More specifically, it seeks to deepen understandi ng of the potential and risks of AI-driven innovation and sustainability in the tourism sector and elaborate on key policy areas to support AI adoption in tourism. It contributes to a more informed policy landscape, identi fying opportunities for targeted interventions and collaborative approaches to harness the potential of AI for tourism. The paper builds on the still-limited but growing body of knowledge on AI-rel ated tourism policy, and in particular, the G7/OECD Policy Paper on AI and Tourism (OECD, 2024 [4]), as well as discussions at the OECD-Korea Forum on Artificial Intelligence and Tourism: promoting innovation - enhancing sustainability held in Gyeongju, Korea on 6 February 2025 and the APEC Self-Funded Workshop on Artificial Intelligence and Tourism: boosting innovation, enhancing sustainability in APEC economi es, which took place on 28 July 2025. It also builds on recent work of the OECD Tourism Committee and wider OECD work on artificial intelligence, as well as recent reports, including by UN Tourism (UN Tourism & Saxion University of Applied Sciences, 2025[1]) and WTTC (WTTC, 2024[2]). Box 1 . Statistical insights on AI adoption in tourism in APEC economies

intelligence, as well as recent reports, including by UN Tourism (UN Tourism & Saxion University of Applied Sciences, 2025[1]) and WTTC (WTTC, 2024[2]). Box 1 . Statistical insights on AI adoption in tourism in APEC economies AI is increasingly influencing how tourism services are delivered across the A PEC region. However, tourism-specific statistics are limited and often anecdotal. In many cases, AI use is embedded within larger digital processes, such as booking platforms, making it difficult to isolate or quantify. As such, there is a growing need for harmonised, sector-specific data collection to better unde rstand the scope and nature of AI use in tourism across the region. • Insights from Canada show that 5.9% of firms in the accommodation and food ser vices sector used AI in Q1 2024, with 4.9% having plans to use AI (Statistics Canada, 2024 [6]). • In Australia, a 2024 industry survey reported that 85% of hospitality operators were using some form of AI or automation, including 36% for inventory management and 26% for staff scheduling (SevenRooms, 2024[7]). An indicative study reveals technical expertise (40%), privacy concerns (33%), and budget limitations (31%) as main barriers for DMOs and SMEs (Tourism Tribe, 2025[8]). • In Malaysia, an impact study found that 12% of roles in hotels and accommodation are h ighly exposed to automation from AI and digitalisation, while around half face medium levels of impact and only a small share are low impact. Understanding and structuring AI systems AI refers to a broad field of computer science focused on developing systems capable of performing tasks that typically require human intelligence, such as reasoning, learning or decision making (Box 2). Applications, including chatbots, recommendation engines and predictive tools, are powered by underlying technologies such as machine learning, natural language processing and large language models. Artificial intelligence is also characterised by its capacity to process large volumes of data to i dentify patterns,

Applications, including chatbots, recommendation engines and predictive tools, are powered by underlying technologies such as machine learning, natural language processing and large language models. Artificial intelligence is also characterised by its capacity to process large volumes of data to i dentify patterns, generate insights and support autonomous or semi-autonomous decision making. 9

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Traditional AI typically relies on task-specific models trained on struc tured data and governed by predefined rules, requiring significant technical expertise and resources for dev elopment and implementation. In contrast, the rapid rise of generative AI introduces a more flexible, content-producing approach. It can generate novel text, images or code based on learned patterns, offering greater scalability and contextual adaptability. For the tourism sector, this shift presents both opport unities and challenges. Generative AI enables hyper-personalisation, faster content creation and l ower entry barriers — particularly relevant for micro and small tourism enterprises. At the same time, i t raises concerns around accuracy, intellectual property, and the emergence of new skill requirements, such as prompt engineering, to use these tools effectively and responsibly. More recently, Agentic AI systems allow direct booking and transactions by autonomously pursuing goals, making decisions, and taking actions. With these constantly improving AI developments, new challenges for the tourism sector and policies arise frequently and require flexibility in adjusting support mechanisms. Box 2 . OECD definition of AI systems Artificial intelligence is a machine-based system that mimics human intelligence to learn, adapt to changing environments, and perform tasks. It is defined as “a machine -based system that, for explicit or implicit objectives, infers, from the input it receives, how to generate outpu ts such as predictions, content, recommendations, or decisions that can influence physical or vir tual environments . Different AI systems vary in their levels of autonomy and adaptiveness after deployment. (OECD, 2024 [9]). Topics typically encompassed by the term “AI” and in the definition of an AI system include categories of techniques such as machine learning and knowledge-based approaches, and application areas such

AI systems vary in their levels of autonomy and adaptiveness after deployment. (OECD, 2024 [9]). Topics typically encompassed by the term “AI” and in the definition of an AI system include categories of techniques such as machine learning and knowledge-based approaches, and application areas such as computer vision, natural language processing, speech recognition, intelligent dec ision support systems, intelligent robotic systems, as well as the novel application of these tools to various domains. AI technologies are developing at a rapid pace and additional techniques and appli cations will likely emerge in the future. The OECD definition aims to be flexible by reflecting a broad understanding of AI, and actors using this definition are encouraged to exercise judgement on its relevant scope, depending on the context it is being used in. AI systems consist of five key dimensions: People & Planet (human and environmental impact), Economic Context (sectoral and organisational setting), Data & Input (nature and origin of data used), AI Model (technical design and functioning of the model), and Task & Output (what the system do es and produces). Each dimension captures essential characteristics and interactions of AI applications, enabling a structured assessment of their societal, technical, and economic implications. Clarifying these dimensions is crucial for effective policy development, as it helps identify who is affected, under what conditions.

Source: (OECD, 2022[10]) (OECD, 2024[9]).10 

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Conceptualisations of AI are manifold, trying to capture and simplify the complexity of AI. Frequently used differentiations include: • Large and Small Language Models: Large Language Models (LLMs) are powerful, generalpurpose AI systems trained on massive datasets across diverse domains. They can perform a wide range of tasks but often require significant computing resources and raise c oncerns about data privacy and control. In contrast, Small Language Models (SLMs) are lighter, more effic ient, and typically designed for specific, domain-focused applications. They can be securely deployed on

range of tasks but often require significant computing resources and raise c oncerns about data privacy and control. In contrast, Small Language Models (SLMs) are lighter, more effic ient, and typically designed for specific, domain-focused applications. They can be securely deployed on local or internal systems, offering greater customisability, privacy control, faster performanc e, and stronger alignment with sector-specific needs — making them particularly well-suited for