As the world grapples with the urgent need to mitigate climate change, protect the environment, and ensure the well-being of future generations, could the intersection of AI and sustainability open the gateway to a sustainable future?
Artificial intelligence (AI) has taken the world by storm. The release of tools such as OpenAI’s ChatGPT has demonstrated the potential of AI to revolutionise many aspects of our lives. The World Economic Forum even lists AI as one of the top emerging technologies expected to make a significant impact over the next three to five years.
While AI has the potential to address some of the most pressing issues of our time, some hold the belief that it poses a significant threat to the future of our society by generating a world full of unemployment and misinformation.
Ultimately, the impact of AI will depend on how it is developed and used. If AI is used responsibly, it has the potential to improve our lives in many ways. However, if AI is used irresponsibly, it could pose a serious threat to our society.
One use case for AI’s use comes in the fight against climate change and the creation of a more sustainable future, arguably one of the greatest challenges of the century.
Reporting for sustainable success
Within the business landscape, sustainability has become a crucial factor for value-driven investors and consumers who now expect more from companies. This trend has prompted organisations to find new ways to assess and showcase their sustainable contributions to remain relevant in today’s world.
A significant challenge companies face is the subjectivity of sustainability measures, with varying interpretations of what truly counts. Between the myriad of governmental regulations, reporting frameworks, and standards which are all designed to help companies measure and disclose their sustainability efforts, companies are struggling to keep up.
While the challenge is likely to be alleviated slightly due to the recent release of the International Sustainability Standards Boards (ISSB) S1 General Requirements for Disclosure of Sustainability-related Financial Information, and S2 Climate-related Disclosures, companies are still facing difficulties in terms of sustainability.
These frameworks aim to measure and scale a company’s sustainability index, quantifying its efforts. In today’s hyper-competitive landscape, an organisation’s growth and success increasingly depend on socioeconomic and environmental considerations. Corporate Social Responsibility (CSR), traditionally focused on avoiding harm, has evolved into a mandate to actively “do good,” encompassed by the strategic priorities of ESG or SDG.
Sustainability reports play a vital role in this context. Notably, popular rating agencies like S&P Global produce sustainability indices for individual companies, capturing investors’ attention and benchmarking long-term impacts and returns. Organisations leverage cloud-based strategies to make sustainability data readily available as part of open data initiatives supported by cloud service providers such as AWS, GCP, and Azure.
Standard-setting bodies like the Sustainability Accounting Standards Board (SASB), the Global Reporting Initiative (GRI), the Carbon Disclosure Project (CDP), and the Task Force on Climate-Related Financial Disclosures (TCFD) are ensuring that 90% of S&P 500 indexed companies publish sustainability reports and make them easily accessible. The percentage of S&P 500 companies publishing sustainability reports increased from 20% in 2011 to 95% in 2022.
AI and sustainability use cases
AI plays a crucial role in facilitating sustainable practices and reporting their impact. For instance, AI can potentially enable the development of smart cities and circular economies that optimise resource utilisation. AI-powered smart city systems can collect and analyse data from a wide variety of municipal services. Smart meters, which use Internet of Things (IoT) sensors to track and monitor energy usage, are a prime example of AI making cities smarter.
By enabling constant monitoring and analysis of energy usage, smart meters provide city administrators with real-time data to optimise energy consumption and save costs. The result is cities that are smart and sustainable. And this is just one use case in the smart meter’s arsenal.
All sorts of problems, from traffic to criminality, can be solved in “smart cities” thanks to the combination of AI and analytics based on data collected by sensors throughout the urban environment.
Barcelona is a prime example of a smart city that has successfully implemented smart meters to improve energy efficiency and reduce costs. In 2012, the city deployed nearly 20,000 smart meters to remotely sense and control irrigation and water levels within the city’s parks, resulting in a 25% increase in water conservation, saving approximately $555,000 per year.
It can also contribute to renewable electricity generation through smart networks that align energy consumption with periods of abundant sunlight and wind. By analysing vast interconnected databases, AI can drive environmental outcomes by coordinating actions aimed at preservation.
Previous research indicates that AI breakthroughs will enhance our understanding of climate change and help model its potential consequences. Furthermore, AI can contribute to the development of low-carbon energy systems that heavily incorporate renewable energy and energy efficiency, both essential for combating climate change and enhancing ecological well-being.
Yet while the links between AI and sustainable goals are primarily positive, trade-offs must be acknowledged. Advanced AI technologies and their research and development may require substantial computational resources available only through large-scale data centres. These centres have significant energy demands and carbon footprints, but there are potentially less-intensive options the industry is exploring.
For example, Red Engineering has worked in conjunction with Engie to establish a new design for data centre energy infrastructure, which will update power and cooling generation systems to accept fuels like hydrogen as they come to market, transforming them into primary drivers for the zero-carbon transition.
Additionally, AI relies heavily on data analytics and resources that may not be equally accessible in low and middle-income countries, potentially exacerbating economic disparities and impeding progress towards economic growth, modernisation, and infrastructure development, as well as reducing inequalities.
Reflecting on the past 200 years, a series of industrial revolutions have significantly improved human living conditions. However, each previous revolution has come at the expense of our planet’s health, borrowing from the future to fuel present economic expansion. Today’s technological revolution must break this pattern and foster sustainable economic development. It is the collective responsibility of corporations, governments, and individuals to strategically harness the vast potential offered by AI to drive economic prosperity while securing a sustainable future.
The first crucial step in this endeavour is deploying tools to measure and report the environmental and social impact of contemporary corporate actions. AI can also assist in cross-checking and validating these reports, ensuring their accuracy, transparency, and accessibility. Measurement serves as the initial catalyst for action, and AI advancements have significantly simplified and expanded the availability of such measures.
Artificial intelligence and sustainable development
AI can be the invaluable partner that sustainable development requires to effectively design, implement, advise, and plan the long-term future of our planet.
According to a Nature study, AI has the potential to support the achievement of 79% of the Sustainable Development Goals (SDGs). The United Nations Sustainable Development Goals (SDGs) are a set of 17 global objectives that aim to address the world’s most pressing environmental, social, and economic challenges such as poverty, hunger, affordable and clean energy and responsible consumption and production.
According to the report, artificial intelligence (AI) has the potential to facilitate the achievement of 134 targets associated with the various goals. However, it should be noted that it can also hinder 59 targets and the current research priorities tend to neglect crucial factors. Many of these relate to how the technological improvements enabled by AI may be implemented in countries with different cultural values and wealth.
AI also holds the potential to enhance the efficiency of renewable energy sources. Companies are already leveraging this technology to determine the daily availability of energy-generating facilities such as wind turbines, hydraulic plants, and biomass plants. This information enables accurate prediction of required energy production in the upcoming days and facilitates proactive maintenance and troubleshooting.
Beyond the energy sector, numerous industries and businesses can benefit from AI while contributing to the welfare of the planet. In agriculture, for instance, AI optimises irrigation and fertilisation processes. By utilising humidity, temperature, and fertilisation sensors, AI can predict the specific needs of crops. Innovations in agricultural sustainability include the use of drones for surveillance and comprehensive pest control through hyperspectral image analysis.
Using AI to aid sustainability efforts
Even though the use of AI contributes to an expanding carbon footprint, AI itself has the potential to contribute to sustainability initiatives.
One significant area where AI is expected to play a pivotal role is in energy management. AI applications can effectively balance the supply and demand of electricity in real time, optimising energy utilisation and storage to reduce consumption. For example, a report by Accenture showed AI adoption in the energy sector is predicted to result in a 20% increase in energy efficiency by 2035. Additionally, the International Energy Agency (IEA) estimates that AI-driven energy management systems have the potential to reduce global greenhouse gas emissions by up to 4%.
In a future-focused on green energy, renewable sources such as microgrids, wind farms, and solar panels will contribute to the energy mix. However, the energy generated from these sources is subject to unpredictable fluctuations based on weather conditions, unlike the more predictable outputs of gas or coal plants.
In a decentralised global energy network of this nature, AI can play a vital role in handling the complexities associated with distributing power to industrial facilities, office buildings, homes, and other locations as needed. By transitioning our current energy system to a smart grid centred around AI, there is potential to enhance grid resilience and flexibility, particularly in the face of unforeseen meteorological events caused by our increasingly unstable climate. This flexibility and resilience will be crucial as the electricity demand grows in rapidly expanding digital economies within an ever more interconnected world.
Overall, if the environmental impact of AI can be reduced, and more organisations start to use AI in their sustainability initiatives, then the use of AI as a whole may be able to attain a level close to carbon neutrality. Yet AI should not be considered a cure-all. To pave the way to a truly green digital revolution, we need to start making conscious choices to promote research of more computationally efficient algorithms as well as hardware that requires less energy.
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