AI can help tourism meet global development targets

The study shows that AI adoption in tourism has entered a new phase. Early applications focused largely on automation, demand forecasting, and customer service optimization. While these tools delivered efficiency gains, they often reinforced volume-driven growth models that intensified environmental and social pressures. Recent research, however, reflects a shift toward sustainability-oriented deployment.

Can artificial intelligence help tourism grow without undermining environmental limits and social equity? A new study published in the journal Tourism and Hospitality Research reveals that the technology holds genuine potential to transform tourism in line with global sustainability objectives.

Titled AI-Powered Sustainable Tourism: Aligning Innovations with the Sustainable Development Goals, the paper reviews how AI technologies are being applied across tourism systems and evaluates whether these innovations genuinely support the United Nations Sustainable Development Goals (SDGs) rather than merely optimizing short-term performance.

AI moves from operational efficiency to sustainability strategy

The study shows that AI adoption in tourism has entered a new phase. Early applications focused largely on automation, demand forecasting, and customer service optimization. While these tools delivered efficiency gains, they often reinforced volume-driven growth models that intensified environmental and social pressures. Recent research, however, reflects a shift toward sustainability-oriented deployment.

AI is increasingly embedded in tourism supply chains to improve resource efficiency, reduce waste, and optimize energy and water use. Predictive analytics enable hotels, transport providers, and destinations to align capacity with demand more precisely, lowering emissions and reducing strain on local infrastructure. Intelligent systems are also being used to coordinate logistics, manage inventories, and reduce food waste across hospitality operations.

The study highlights that these changes are not isolated technological upgrades but part of broader sustainability strategies. AI tools support real-time monitoring of environmental indicators, enabling destinations to respond dynamically to stress points such as overcrowding, pollution, or ecosystem degradation. In this way, AI shifts from a back-office efficiency tool to a system-level management instrument.

Economic sustainability also features prominently. AI-driven optimization helps tourism businesses reduce costs while maintaining service quality, supporting long-term financial resilience. For destinations heavily dependent on tourism revenues, this balance is critical. The study emphasizes that sustainable tourism is not anti-growth but growth-aware, seeking to decouple economic benefits from environmental harm.

Importantly, the research notes that sustainability outcomes depend on how AI systems are designed and governed. When AI is deployed solely to maximize throughput or spending, sustainability gains are limited. When embedded within policy frameworks that prioritize long-term value creation, AI becomes a lever for structural change.

Influencing tourist behavior and managing demand responsibly

Recommendation systems, conversational interfaces, and intelligent travel planning tools increasingly shape where people go, how they travel, and what choices they make at destinations. These systems can either exacerbate sustainability challenges or help mitigate them.

The review shows growing evidence that AI can steer tourists toward less crowded locations, off-peak travel periods, and lower-impact activities. By dynamically adjusting recommendations based on real-time data, AI systems can distribute demand more evenly across space and time, easing pressure on fragile destinations. This approach directly addresses overtourism, one of the most persistent sustainability challenges facing popular destinations worldwide.

AI-driven personalization also has the potential to encourage more responsible consumption. Intelligent systems can highlight eco-certified accommodations, low-carbon transport options, and locally sourced experiences. When integrated thoughtfully, these nudges influence behavior without restricting choice, aligning individual preferences with sustainability goals.

The study notes that behavioral impacts extend beyond individual trips. Exposure to sustainable options and messaging can generate spillover effects, shaping future travel decisions and everyday consumption habits. This suggests that AI-enabled tourism platforms may contribute to broader cultural shifts toward sustainability.

However, the research also flags risks. Algorithmic bias, lack of transparency, and profit-driven optimization can undermine these benefits. If recommendation systems prioritize commercial partnerships over sustainability criteria, they may reinforce unsustainable practices. The study stresses the need for accountability and clear governance to ensure that AI-driven influence aligns with public interest objectives.

Demand management emerges as a critical governance challenge. AI provides powerful tools to predict and shape tourist flows, but decisions about how these tools are used carry ethical and political implications. The study argues that destinations must retain oversight, ensuring that AI supports inclusive access and community well-being rather than privileging certain groups or interests.

Governance, ethics, and alignment with global development goals

The study analyses governance and alignment with the Sustainable Development Goals. Across the reviewed literature, AI-powered tourism initiatives show strong connections to multiple SDGs, particularly those related to economic growth, innovation, sustainable cities, responsible consumption, and climate action.

AI contributes to SDG 8 by supporting decent work and economic resilience through efficiency gains and new skill requirements. It aligns with SDG 9 by fostering innovation in infrastructure and services. Smart destination planning and mobility optimization advance SDG 11, while waste reduction and energy management support SDG 12. Climate-focused applications, including emissions monitoring and low-carbon transport optimization, contribute directly to SDG 13.

The study also identifies indirect contributions to goals related to gender equality, reduced inequalities, biodiversity protection, and partnerships. For example, AI-supported conservation initiatives help protect natural assets critical to nature-based tourism, while data-driven planning can improve accessibility and inclusivity.

Yet the research is clear that alignment with SDGs is not automatic. Governance frameworks determine whether AI amplifies sustainability or entrenches existing inequalities. Poorly regulated AI risks excluding marginalized communities, displacing workers, and prioritizing efficiency over equity. The study emphasizes transparency, stakeholder participation, and ethical oversight as essential conditions for sustainable AI deployment.

Workforce readiness is another recurring concern. As AI transforms tourism operations, demand grows for digital, analytical, and sustainability-related skills. Without targeted training and reskilling, AI adoption may widen labor inequalities. The study calls for education and workforce development to be integrated into tourism innovation strategies.

The review also highlights gaps in empirical evidence. While conceptual and case-based studies dominate the literature, longitudinal research measuring real-world sustainability outcomes remains limited. This gap makes it difficult to assess whether AI-driven interventions deliver lasting benefits or merely short-term improvements. The authors argue that future research must move beyond pilot projects to evaluate system-wide impacts over time.

Implications for destinations, policymakers, and industry

Sustainable tourism outcomes depend less on the sophistication of algorithms and more on the frameworks guiding their use. Destinations that treat AI as a strategic public good rather than a purely commercial asset are better positioned to align innovation with long-term development goals.

For policymakers, the findings underscore the importance of embedding AI within sustainability policy from the outset. Regulatory clarity, ethical standards, and cross-sector coordination are essential to prevent fragmented or contradictory initiatives. The study suggests that public authorities play a crucial role in setting sustainability criteria that guide AI deployment across tourism systems.

For industry actors, the research highlights opportunities as well as responsibilities. AI can support competitiveness while reducing environmental footprints, but only when sustainability metrics are integrated into performance evaluation. Companies that adopt AI without considering social and environmental impacts risk reputational and regulatory backlash.

For researchers and development agencies, the study identifies priority areas for future work including measuring long-term behavioral change, assessing equity impacts, and developing governance models that balance innovation with accountability. Expanding research beyond high-income destinations is also critical to ensure that AI-powered sustainable tourism benefits diverse regions and communities.