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5. Conclusion and policy implications
5.1. Conclusion
This study was conducted to explore the causal mechanisms by which micro-level AI
Readiness impacts macro-level Destination Resilience and Regenerative Tourism practices,
mediated by organizational adaptive capacity. The PLS-SEM analysis of 250 tourism small
and medium-sized enterprises (SMEs) in Ho Chi Minh City provided robust empirical
evidence supporting all proposed hypotheses.
First, the research affirms that AI is not merely a cost-cutting tool but a strategic
resource that profoundly generates organizational adaptive capacity (H1). Second, the
core finding validates the perfect mediating role of adaptive capacity (H4, H5); implying
that AI technology itself does not rescue a destination. Instead, it equips SMEs with the
agility to proactively overcome crises and contribute to ecological regeneration (Ben
Youssef & Zeqiri, 2022; Huang et al., 2022). Finally, governance and policy support exert a
positive moderating effect (H6a, H6b), demonstrating that a favorable public governance
environment is a mandatory catalyst for translating technological advantages into
comprehensive resilience (C.Hall et al, 2021).
5.2. Managerial implications for tourism SMEs
Based on the empirical results, SME managers in Ho Chi Minh City must shift their
mindset from being "technology consumers" to "technology masters." Businesses should
prioritize investments in AI-oriented human capital through continuous reskilling and
upskilling programs (Buhalis et al., 2023). Rather than fearing job displacement, SMEs
should utilize AI to automate repetitive tasks, thereby freeing up employees to focus on
services requiring emotional intelligence and the "human touch"—the core value of the
hospitality sector (Tussyadiah, 2020). Furthermore, SMEs should leverage predictive
analytics to optimize energy management and minimize waste, transforming their
operations into active agents in the regenerative tourism movement (Dredge, 2022).
5.3. Policy implications for destination authorities in HCMC
The significant moderating role of GPS highlights the responsibilities of local
authorities in the digital transformation journey. First, the department of tourism and
destination management organizations (DMOs) in HCMC should provide targeted
financial incentives (e.g., subsidies for SaaS adoption) to help SMEs overcome initial
investment barriers. Second, the government should develop a shared tourism data
platform, granting grassroots enterprises access to real-time market insights to enhance
their forecasting and adaptive capabilities (Gretzel et al., 2015). Ultimately, it is
imperative to establish clear ethical and legal frameworks regarding customer data
privacy (similar to GDPR standards) to prevent algorithmic bias risks and protect privacy,
thereby fostering a safe and inclusive smart tourism ecosystem (De Almeida et al., 2021).
5.4. Limitations and future research directions
Despite its valuable theoretical contributions, this study has certain limitations. The
data was collected using a cross-sectional design in a single destination (HCMC), which
may limit generalizability. Future studies should employ longitudinal approaches to assess
the impact of AI across different phases of a crisis cycle. Additionally, extending the model
to deeply investigate "AI Ethics" or the impact of immersive technologies (VR/AR) on
tourist behavior would present promising avenues for future research.

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