ClimateAi has been nominated for the World AI Awards in the AI in Sustainable Tourism category, recognising its use of artificial intelligence and machine learning to help organisations understand weather disruption and longer-term climate risk.
For tourism, that problem is becoming increasingly practical. Hotels, resorts, destinations, attractions and travel infrastructure depend heavily on local conditions. Extreme heat, flooding, storms, water stress and changing seasonal patterns can affect everything from visitor demand to asset planning.
ClimateAi approaches that uncertainty through ClimateLens, its enterprise climate-resilience platform. Instead of simply reporting historical climate data, the technology combines AI, machine learning and multiple data sources to produce forecasts and longer-term risk information intended to support operational and strategic decisions.
Looking beyond tomorrow’s weather forecast
ClimateLens works across very different time horizons.
Its Monitor product focuses on operational forecasting, covering conditions from day-to-day decisions through the months ahead. ClimateAi’s current forecasting system combines short-term forecasts of roughly 15 days, subseasonal forecasts extending to six weeks and seasonal forecasts reaching approximately six months.
The platform also tackles the other end of the timeline. ClimateLens Adapt is designed to examine risks and opportunities under future climate scenarios extending 10 years and beyond.
That distinction matters for tourism.
A destination operator may need to understand the probability of disruptive weather during an upcoming season. A hotel developer considering a long-lived asset faces another question entirely: how might heat, rainfall, flooding or other climate hazards change over the lifetime of that investment?
ClimateAi’s technology is designed to put both types of questions into a decision-making framework.
AI pushes climate forecasts closer to local conditions
Global climate models are powerful, but their geographical resolution can become a limitation when organisations need to understand what may happen at a particular asset or location.
ClimateAi has been developing machine-learning methods to narrow that gap.
The company was granted a U.S. patent in 2024 for technology using deep generative models to increase the accuracy and resolution of weather forecasts. Its approach uses generative adversarial networks to correct and downscale broader weather and climate forecasts, producing more localised information.
ClimateAi has subsequently demonstrated forecasting at approximately one-kilometre resolution in work conducted for the U.S. Department of Defense.
For sustainable tourism, greater geographical detail could be particularly relevant in places where conditions change sharply across relatively short distances. Coastal destinations, islands and mountainous tourism regions are obvious examples.
The technology does not eliminate climate uncertainty. What it can do is give organisations another layer of information for assessing that uncertainty before making operational or investment decisions.
From climate risk to tourism decisions
ClimateAi does not position ClimateLens solely as a travel product. Its platform serves climate-sensitive industries and organisations more broadly, with applications including supply chains, agriculture, manufacturing, finance and government.
That makes the AI in Sustainable Tourism nomination an interesting one.
The potential tourism application lies in translating climate intelligence into decisions around destinations and physical assets. ClimateLens can evaluate hazards at specific locations, compare climate scenarios and help organisations investigate alternative locations when conditions change.
Its forecasting API also provides historical information, climatological baselines and probabilistic forecasts using latitude and longitude. ClimateAi says its current forecast endpoints can create a continuous outlook extending from the present to approximately six months.
For tourism businesses, similar capabilities could inform seasonal planning, climate-risk assessments, infrastructure decisions and resilience strategies. They could also help destination stakeholders examine how the environmental conditions supporting tourism today may shift over longer periods.
The important distinction is between capability and deployment: ClimateAi has established climate-risk technology and documented enterprise applications, but tourism-specific outcomes should not be assumed without evidence from individual deployments.
Sustainable tourism has a climate intelligence problem
Sustainable tourism is often discussed through carbon emissions, conservation and responsible visitor behaviour. Climate adaptation belongs in that conversation too.
Tourism infrastructure is frequently built for decades. Decisions made now about resorts, transport links, recreational facilities and destination development may therefore encounter environmental conditions different from those captured in historical averages.
ClimateAi’s approach is to use artificial intelligence not simply to describe that risk but to make climate information more usable for decisions.
Its technology combines short-range operational forecasting with seasonal outlooks and longer-term climate scenarios. That creates a bridge between questions about what could happen during the next tourism season and what a destination might face years from now.
Graham Cooke, President of the World AI Awards, said:
“ClimateAi’s nomination in AI in Sustainable Tourism highlights an increasingly important part of the sustainability conversation: understanding how destinations and tourism businesses can prepare for changing climate conditions.
“Artificial intelligence can help turn enormous volumes of weather and climate data into information that organisations can use when considering operations, infrastructure and long-term resilience. ClimateAi’s work demonstrates the opportunity for better climate intelligence to support more informed planning across tourism and other climate-sensitive industries. We congratulate the team on its World AI Awards nomination and look forward to following the development of its technology.”
ClimateAi joins organisations, entrepreneurs, researchers and technology developers being recognised through the World AI Awards.
The programme recognises organisations, individuals, products and technologies contributing to the development and practical application of artificial intelligence across industries.
ClimateAi’s nomination also reflects a broader shift in the sustainable tourism conversation. AI does not have to interact directly with travellers to influence how tourism develops. Some of its most consequential applications may happen behind the scenes — analysing climate conditions, identifying vulnerabilities and helping organisations make better-informed decisions about where and how they operate.
For destinations facing increasingly unpredictable environmental conditions, knowing more about what may be coming is not the entire solution. But it can be a useful place to start.
Learn more about ClimateAi and its climate intelligence technology at https://www.climate.ai/.
Discover the World AI Awards, explore the nominees and learn more about the awards at https://www.worldawards.ai/.
