The recent tragedy of the LA fires once again highlighted the importance of effective climate risk management on many levels. Two heads might be better than one in designing such global and critical solutions, and perhaps human capabilities in CRM might be significantly enhanced by artificial intelligence (AI).
Climate Risk Management (CRM) In a Nutshell
Climate Risk Management (CRM) refers to the processes and strategies to assess vulnerabilities, mitigate exposure, adapt to and cope with risks arising from climate-related events, such as wildfires, hurricanes, floods, and droughts.
Companies from different sectors (energy, technology, agriculture, etc.) may have enhanced climate-related risks, as well as certain communities or whole countries. Therefore, there are numerous programs and policies developed on both corporate and government levels to reduce the risks, prevent connected disasters and effectively handle the outcomes of climatic hazards.
What Can Be Done to Mitigate Large-Scale Climate Risks?
Climate-related events such as hurricanes, floods or wildfires are major disasters affecting populations across the globe. Due to their wide-scale impact, climate risks are always a government concern. What can be done about them on a national or regional level?
To begin with, government agencies develop or adopt technology tools to assess wildfire, hurricane or flood risks across communities. They also back scientific teams who do proper climate research and fund local wildfire prevention and recovery efforts.
How Governments Tackle Wildfire Dangers
To reduce flammable vegetation like dry grass, shrubs, and dead trees in high-priority and high-risk forest areas, agencies can conduct controlled burns with the participation of firefighters and land managers. They also leverage predictive analytics to allocate firefighting resources more efficiently and detect high-risk zones taking into account changing circumstances.
Upon assessment of high-risk areas, government institutions can plan land use responsibly to limit construction in such locations and implement enhanced fire-safe building policies for critical regions. National and regional agencies partner with local utility companies to improve wildfire prevention and response strategies. For instance, jointly they can ensure brushing clearance and defensible space around homes in fire-prone areas.
Helping Affected Communities
Another important measure to improve climate risk resilience in local communities is public education. Such campaigns can better prepare residents for fire evacuations and preventive measures. Besides, governments are responsible for addressing food, water, sanitation, hygiene, health, housing and education concerns of people displaced due to climate shocks, especially when it comes to vulnerable communities and population segments.
Businesses’ Responsibility for Climate Risk Prevention
Governmental efforts alone are not enough to eliminate or significantly reduce climate risks. Therefore, all responsible business entities are also adopting climate risk management (CRM) policies and solutions.
Preventive CRM Measures
Businesses invest in preventive measures like infrastructure upgrades and early warning systems, integrate technologies using data, AI, and satellite imagery for better risk prediction, and partner with researchers and governments to develop climate risk-resistant products.
Depending on the industry, enterprises employ different CRM tools. These can be power line upgrades, public safety power shut offs and burying cables underground for energy companies; advanced weather forecasting, water-efficient irrigation systems, and heat- or drought-resistant crop varieties for the agricultural sector; adopting fire-resistant building materials and improving fire defences for builders; creating tech solutions to monitor land changes and predict wildfire-prone regions for technology providers, etc.
Where Corporate Responsibility Starts
Businesses are responsible not only for their own employees and premises, but also for the local communities they affect. Activities of many corporations can increase climate risks, so their duty is to avoid negative impacts and dangerous outcomes for the people and territories involved. This responsibility is often demanded by law, but even if it’s not, CRM must be part of the business agenda for any entity.
What Does AI Have to Do With CRM?
As a transformative technology, artificial intelligence (AI) is an essential part of most modern CRM assessment systems. AI-driven data analysis lays the foundation for climate-related decisions at corporate and state levels. For starters, this technology facilitates complex CRM analytical processes. Moreover, AI enhances climate-related predictions and resource allocation, revealing previously unknown factors or possibilities due to real-time interactions with vast datasets including satellite images, weather patterns, historical climate data, and more. Now, let’s be more specific.
AI in Real Estate and Insurance Climate Risk Assessment
Extreme weather and climate hazards can cause substantial damage to real estate located in vulnerable areas. Insurance companies are highly vulnerable to wildfire risks due to payouts for fire damage claims. Other types of climate risks might contribute to deteriorating health conditions in affected populations. This is an important factor to consider for health insurance providers.
To assess risks, real estate and insurance companies might employ machine learning models to analyse historical data, weather patterns, satellite imagery, and vegetation density to identify wildfire-prone areas, discover drought or flooding risk predictions, etc.
Furthermore, AI can create not generic but hyper-localised risk maps, helping insurers and real estate managers assess the risk for individual properties rather than broad regions. This allows for more accurate premium pricing, better property management plans, as well as implementation of adaptation measures and mitigation strategies at site level.
Additionally, AI systems provide real-time updates on risks as environmental conditions change, empowering firms with more strategic flexibility and faster reactive measures.
AI-powered tools are a basis for smart and customer-centric underwriting processes as they can not only automate risk assessment but also identify policyholders who have taken risk-reduction steps, such as installing fire-resistant roofing or maintaining defensible space, for discount offers or other encouraging incentives.
Use Cases
One real-life example of AI implementation in these segments is the Singaporean startup Climate Alpha which uses AI to enable real estate owners and investors analyse the impact of climate change on their portfolios. The platform leverages public and private data about industry-standard climate models, census and economic indicators, along with proprietary machine learning algorithms to forecast climate change’s financial impact.
Major insurance companies also use the power of AI to improve climate risk assessment. Thus, AXA Climate – a specialised entity within the AXA Group – analyses climate and environmental risks for various entities, including industrial sites and agricultural areas, to develop tailored adaptation strategies. The subsidiary assesses climate-related risks using satellite imagery, historical fire data, and climate projections leveraging AI to model wildfire risks and provide parametric insurance products.
AI for Urban Planning and Infrastructure Resilience
AI tools can create detailed maps of climate risks, including fire-prone zones or potential flood plains to guide urban planners in creating building codes and zoning laws. The innovative technology gives city officials the possibility to predict the impact of different climate hazards on a specific location. There’s, for instance, the Virtual Singapore project – an AI-powered 3D digital platform intended for use by the public, private, people and research sectors to test and explore different scenarios. One of the potential use cases for this digital twin is to simulate the impacts of climate risks like rising sea levels, heatwaves, and urban flooding. Additionally, urban planners can use Virtual Singapore to optimise building designs, improve energy efficiency, and plan green spaces to mitigate urban heat islands.
Besides, AI can help make cities more resilient and ‘smart’. For instance, AI-powered IoT sensors may monitor environmental conditions in real time, assisting cities in proactively adapting to risks. Smart sensors installed in high-risk zones detect early signs of fires, such as smoke or temperature spikes. As AI identifies wildfire-prone areas, urban planners better understand the need to create defensible spaces and fire-resistant infrastructure.
Dutch Climate-Resilient Infrastructure
The city of Rotterdam, Netherlands, is almost fully located below sea level. However, smart technologies help it survive and mitigate flooding risks. First, the city has a highly sensitive weather radar on the roof of its tallest building equipped with weather forecasting technology that predicts the coming rain 12 hours ahead. Secondly, there are several water squares in the city to host rainwater in a nice public place instead of the sewers. Finally, many local buildings have “green-blue” rooftops with plants and reservoirs for collecting excess water. The main point is that Rotterdam is piloting a smart automated system to manage all that.
The city’s goal is to create a system that synchronises water levels across rooftop tanks to better manage sewer capacity and develop a climate-proof city by the year 2030. By connecting valve control devices to a network of blue roofs, they start acting as a distributed system of stormwater reservoirs. Before a rainstorm, the reservoirs can be automatically and remotely emptied via the dedicated app, to prepare for collecting rainwater during heavy downpours. This helps to alleviate pressure on the sewer system and minimise flooding. The city authorities also collaborate with tech startup Sobolt, which can analyse the surface area of green rooftops more accurately, using aerial photography, satellite images and AI-based techniques.
AI in Building Climate-Resilient Agriculture
Agricultural enterprises and individual farms are largely reliant on weather conditions. Therefore, efficient weather forecasting is key to the right assessment and mitigation of climate risks for crops, fruit gardens, farm animals, etc.
As the second-largest producer of rice, wheat and sugar, and a country with large rural areas, India has been lately making efforts to improve its weather forecasting systems with AI. Such tech-driven tools are particularly helpful for predicting severe weather changes like floods and droughts.
AI can also create detailed risk maps for drought-prone or flood-vulnerable areas, guiding agricultural land-use decisions. The technology analyses soil data to recommend crop rotations and cover crops that preserve soil fertility and reduce erosion. It is crucial for regenerative practices that reduce the environmental impact of farming and make agriculture more resilient to climate shocks.
Besides, many agritech startups use AI to make different agriculture processes more climate-resilient. There’s SatSure in India which uses satellite imagery and AI to provide insights into crop health, yield predictions, and disaster management. In Vietnam, we have Enfarm, which uses vital agricultural data to optimise crop nutrition, boost yields and minimise environmental impact. The company leverages AI and the Internet of Things to empower farmers with knowledge about the state of soil, weather, potential crop yields, market updates, and more. Another example is Benson Hill that uses AI to take the plant breeding process to a new level and develop climate-resilient crops with higher yields.
On a Final Note
Nature is full not only of beauty and vital energy but also of destructive powers. It is a human obligation to adapt to those climate and weather impacts in order to maintain our basic subsistence. Governments and businesses around the world have sufficient resources to mitigate the climate risks at hand. The efficacy of their CRM strategies can be significantly enhanced with smart AI technology. It is already showing revolutionary results in segments from urban planning to sustainable agriculture, though the AI tools are still in their infancy.
