Artificial intelligence (AI) is already reshaping day-to-day operations across Europe’s National Tourism Organisations (NTOs). A handful of member bodies have emerged as early adopters, reporting tangible productivity and quality gains. Crucially, employee sentiment is broadly positive: resistance to experimentation is low, signalling fertile ground for rapid diffusion.
Maturity, however, varies markedly between functions. Marketing departments are generally ahead of research departments in both adoption and confidence, and the performance gap within marketing teams is narrower than that observed across research teams. Practitioners in marketing report more immediate, visible value—from automated copywriting to data-driven campaign optimisation—whereas researchers consider the technology useful but still exploratory.
Across both functions, the most urgent enabler is skills development. Staff require structured, role-specific training to move beyond ad-hoc tool use and unlock AI’s full potential. After basic capability building, the priorities diverge. Research teams need clearer insight into what AI can achieve for their tasks; without this vision, experimentation risks stalling. Marketing teams, by contrast, call for stronger leadership and a cohesive strategy to scale successful pilots, but face budget constraints that threaten momentum.
Organisation-wide barriers likewise reflect these themes. The single greatest hurdle is a scarcity of in-house AI expertise. For research departments, the next obstacle is the absence of a well-defined AI roadmap. For marketing, constrained financial resources present the more pressing challenge.
Targeted investment in training, coupled with strategic guidance for research and budgetary support for marketing, will accelerate responsible AI adoption, close inter-departmental gaps and position NTOs to compete more effectively in the global tourism marketplace.
Artificial intelligence (AI) is already reshaping day-to-day operations across Europe’s National Tourism Organisations (NTOs). A handful of member bodies have emerged as early adopters, reporting tangible productivity and quality gains. Crucially, employee sentiment is broadly positive: resistance to experimentation is low, signalling fertile ground for rapid diffusion.
Maturity, however, varies markedly between functions. Marketing departments are generally ahead of research departments in both adoption and confidence, and the performance gap within marketing teams is narrower than that observed across research teams. Practitioners in marketing report more immediate, visible value—from automated copywriting to data-driven campaign optimisation—whereas researchers consider the technology useful but still exploratory.
Across both functions, the most urgent enabler is skills development. Staff require structured, role-specific training to move beyond ad-hoc tool use and unlock AI’s full potential. After basic capability building, the priorities diverge. Research teams need clearer insight into what AI can achieve for their tasks; without this vision, experimentation risks stalling. Marketing teams, by contrast, call for stronger leadership and a cohesive strategy to scale successful pilots, but face budget constraints that threaten momentum.
Organisation-wide barriers likewise reflect these themes. The single greatest hurdle is a scarcity of in-house AI expertise. For research departments, the next obstacle is the absence of a well-defined AI roadmap. For marketing, constrained financial resources present the more pressing challenge.
Targeted investment in training, coupled with strategic guidance for research and budgetary support for marketing, will accelerate responsible AI adoption, close inter-departmental gaps and position NTOs to compete more effectively in the global tourism marketplace.