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By Dr Mahua Biswas, Course Coordinator in Business and Management and Business Lecturer, FSB Luton and Hassan Tariq, Business Lecturer, FSB Luton

Abstract

In recent years, Artificial intelligence (AI) has evolved as a powerful tool that can help create new solutions to climate change and solve this problem effectively. AI helps identify climate change risk regions, create adaptation plans for businesses and communities, predict floods and wildfires and pinpoint the location of earthquakes (Rutenberg et al., 2021: Jain. et al. 2023). Furthermore, AI-powered technologies lead to optimal energy utilisation and increase the efficiency of renewable energies with predictive analysis on tremendous data sets for matching demand and supply patterns (Masterson, 2024).  In this article, we focus on the two important impacts of climate change on businesses and how AI can be used to mitigate these climate risks.

Introduction
Business is impacted by climate change throughout the world:  Global warming impacted water-dependent industries, including agriculture and hydropower which are suffering from reduced efficiency and risk of energy shortages due to declining water levels in rivers. Floods, hurricanes, and droughts can hinder transportation, damage infrastructure, decrease in labour productivity and delay raw material availability which results in affecting the production and distribution process (World Economic Forum, 2020).  Climate change directly affects other businesses such as the travel and tourism, hotel and restaurant, and aviation industries.  The tourism industry that relies on the natural beauty and animals of the region is facing adverse consequences due to the damaging environment and reducing biodiversity. Industries such as insurance, real estate, and health care are all susceptible to climate risks. Insurance companies are required to make substantial payouts to policyholders. The healthcare industry is equally vulnerable to climate risks. With the exacerbation of water scarcity, remote populations who are already vulnerable to economic and social conflict, experience the greatest impact of restricted availability of clean water and sanitation facilities (Cruz et. al.2007). The UK’s National Health Service (NHS) predicts that unless immediate action is taken, extreme temperatures, frequent storms and floods, could lead to outbreaks of infectious diseases such as encephalitis and vibriosis (NHS, n.d.). In addition, damage to infrastructure from extreme weather events puts a strain on public resources and hinders economic growth. In general, every economic sector is vulnerable to the risks of climate change.

Supply chain Disruption

Climate disruption to global supply chains could cost $25 trillion by mid-century as Sun et al. (2024) of King’s College revealed. As the global economy has become increasingly integrated, disruptions in one area would have ripple effects on others, often in unexpected ways. Crop failures, layoffs or work stoppages due to heat waves in one region can cause disruptions in production and business in other distant areas. In February 2021, a historic winter engulfed the entire state of Texas, broke numerous records for the lowest temperature and became the first billion-dollar weather disaster of the year. Scientists believed that the severe freeze was the result of climate change (Busby et al., 2021). The February 2021 Texas Freeze led to the most severe unplanned electricity blackout in the history of the United States (The Great Texas Freeze: February 11-20, 2021, 2024). As a result, three important semiconductor factories were forced to close, worsening the worldwide scarcity of semiconductors caused by the COVID-19 pandemic and impeding the production of automobiles that depend on microchips. The power failure resulted in the shutdown of the railroads, severely disrupting critical communications between Texas and the Pacific Northwest for three days (see Yale Environment 360, 2022).

According to the World Meteorological Organization (WWA), heavy rains in Dubai (UAE) and Oman in April 2024 were caused by climate change. The incidents brought Dubai to a standstill for weeks. These disruptions have a critical impact on local businesses and also have severe effects on international trade that can compromise reliability and efficiency and thus weaken the global supply chain (Herold and Łukasz Marzantowicz, 2023).

Labour Supply and Labour Productivity

Climate change is expected to reduce labour supply and productivity, especially in tropical regions. According to the International Labour Organisation (ILO), climate change causes a global loss of up to 3.8% of total working hours worldwide over seven years. The figure represents a total of 136 million full-time jobs and $2.4 trillion in economic losses, as reported by the (World Economic Forum, 2023). Research has indicated that if the temperature exceeds a certain level, workers are required to increase the number of breaks during the workday, from 10 to 40 minutes more per hour of active work. The study conducted by Dasgupta et al. (2021) suggests that current climatic conditions have a detrimental impact on labour productivity, especially in tropical countries. Under 3.0°C warming, future climate change is expected to decrease world total labour in low-exposure sectors by 18 percentage points in low-income industries, and by 24.8 percentage points in high-income industries. The data from 2017 indicates that 153 billion working hours were lost due to heat exposure worldwide, a significant increase of 62 billion hours compared to the year 2000 (Watts, N. et al., 2018)  Every year, for every trillion tonne of carbon emissions, the economy losses labour productivity equivalent to 2% of the total GDP.  According to Chavaillaz et al. (2019), this leads to an extra annual economic loss of 4,400 Giga $ approximately. In addition to this, it is difficult to measure the number of disruptions in everyday life caused by climate change including loss of work and school days, as well as the negative impact on business, transportation, agriculture, energy production, and tourism. It has the potential to impede agricultural activities, disrupt air traffic, and prevent people from carrying out day-to-day activities. However, these disruptions have a significant impact on the overall decline in labour productivity.

AI and Climate Risk

There are many strategies that businesses have adopted to mitigate climate risk, viz., transition to renewable energies, promoting green products, reducing carbon emission, energy efficiency, disaster risk management, adopting policies aligned with national and international climate change agencies etc. However, businesses have the opportunity to surpass conventional ways and leverage AI address climate risks. Some of the methods are highlighted below:

Early warning signs:

One of the advantages of AI is its ability to analyse large amounts of data which allows for early warning or predictions of impending disasters. This allows for a quick and efficient response Satellites, meteorological stations, and other sources can be used to detect changes in weather or ocean conditions that may indicate the onset of storms or floods (Jain, H. et al., 2023). By analysing geographic and demographic data, the system can identify cities and infrastructure in areas that are at risk of damage from floods or hurricanes. AI-powered machine learning models can predict hurricanes, heatwaves and floods to avert massive impacts on our communities and infrastructure by monitoring real-time patterns or anomalies in data for rapid warnings (Zennaro et al., 2021). These AI-enable insights are critical to developing responsive strategies that help build resilience against climate-related disturbances (Leal Filho et al., 2022). This allows strategists to focus on planning and reaction measures, such as the organised evacuation or upgrading of important infrastructure. Implementing this measure can effectively limit the number of deaths and reduce the extent of damage caused by natural calamities.

Collaboration in the supply chain:

Artificial intelligence (AI) can improve the exchange of information between businesses, governments, and non-governmental organisations (NGOs) to effectively coordinate efforts to address climate disruptions (Kim, 2020). This can lead to the development of more effective collaborative approaches to risk management and maintaining uninterrupted supply chain operations. By incorporating AI into their operations, businesses can improve their ability to identify and address climate risks, building more resilient and greener supply chains in an increasingly volatile and uncertain world. In addition, it is crucial to promote collaboration between governmental agencies, civil society and NGOs to develop common climate change adaptation strategies which can better address the specific constraints the world faces. Additionally, adequate financial support, development of skills and knowledge, and engaging the public in the battle against climate change are pertinent in mobilising resources.

Risk Assessment Analysis:

The ability to determine important information quickly and accurately makes AI a valuable tool for identifying areas most affected by the effects of climate change, such as floods, earthquakes or drought areas (Nost and Colven, 2022). Artificial Intelligence allows governments, agencies, communities and businesses to use data to analyse weather patterns, satellite images and weather conditions. This allows them to develop strategic solutions that address the different situations in each region. AI can analyse historical disruptions, geographical hazards, and customer relationships to determine the most susceptible areas in a supply chain. This allows businesses to focus their risk mitigation efforts on the areas that need the most attention.
AI could be used to analyse satellite images and identify areas prone to flooding or erosion due to sea level rise. By applying machine learning algorithms to vast amounts of satellite images, AI models can discern patterns and trends that human analysts might miss (Jain et al., 2023) Therefore, these models can provide estimates of the potential impact of sea level rise on specific regions. By increasing the accuracy of predicting these results, businesses can adopt preventive measures to change their supply chains, redirect operations, or find alternate sources of raw materials. Businesses could also use AI-based demand forecasting mechanisms to manage inventory more effectively, reduce the need for surplus stock and guarantee the supply of critical products even in times of shortages. Artificial intelligence systems are capable of monitoring supply chain activities at all times and show effects as they occur. This leads to quick responses, such as engaging alternative suppliers or modifying the production schedule.

Labour productivity and AI

Artificial intelligence can effectively help businesses manage the risks related to climate change, such as tackling the issues of reduced labour productivity and labour availability (Vinuesa et al., 2020). AI can analyse vast weather data and forecast potential difficulties in the availability of labour in the future, considering anticipated climate patterns. Companies can use this information to propose solutions for possible labour scarcities, such as by allocating resources to automation or creating a more flexible and dynamic workforce. In businesses such as Agriculture or a water-bound industry where human labour is greatly impacted by high temperatures or cold weather, AI can help in automating monotonous or physically exhaustive work. However, it should be kept in mind, that when automation increases, employees may find it difficult to cope with it and they should be trained to effectively use and control such systems (Sjödin et al., 2021). This ensures that workers are comfortable and efficient when exposed to the elements. By using the power of AI, organisations can solve problems related to reducing production staff and equipment. Furthermore, they can turn these challenges into opportunities to drive innovation, increase sustainability and achieve growth.

AI may be employed in several other areas to address the risks associated with climate change, as provided in the table below:

Table 1: Application of AI in climate risk mitigation

However, despite these advantages, there are limitations to consider while using AI-powered models.  A key limitation is the need for high-quality data. For these systems to be effective, they require access to accurate and current data from a variety of sources. In addition, there are concerns about the possible biases in the data or algorithms that these systems utilise, which could result in inaccurate or unfair predictions (Zhang et al., 2023).

Another issue is the possibility of generating false alerts. AI systems are not perfect and can create false positive alarms leading to unnecessary notifications or disruptions (Chen et al., 2023). Another drawback of using AI models is that rare and critical minerals – like cobalt, lithium and tantalum – are needed for AI technologies which are obtained through dangerous extractive methods that can be very costly and can have a severe impact on the communities as well as the environment (Taddeo. Furthermore, developing effective adaptation strategies that can reduce the risks and impact of climate change is a difficult task. To create effective response plans, governments and communities must have accurate and relevant information regarding the specific risks each region faces.  Despite these challenges, the potential of artificial intelligence-powered early warning systems for natural disasters and mitigating climate risk is significant.

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