Harnessing Artificial Intelligence to accelerate sustainable development

Despite global efforts to combat climate change, the world is still not on track to meet the Paris Agreement's goal of limiting global warming to 1.5°C – a critical threshold to prevent catastrophic and irreversible harm to our planet. Major challenges such as geopolitical tensions and conflicts, the ongoing climate crisis, a prolonged period of high inflation in recent years and the lingering effects of the COVID-19 pandemic have significantly hindered progress towards a more sustainable future.

Recognising the need for comprehensive action, the United Nations introduced 17 Sustainable Development Goals (SDGs) in 2015 as a universal call to action. These goals aim to end poverty, protect the planet and ensure peace and prosperity for all by 2030. They cover a wide range of interconnected issues, from quality education and gender equality to clean energy and climate action. Achieving these ambitious targets requires unprecedented collaboration across governments, businesses and communities around the globe.

With only six years left until the 2030 deadline, the world is on course to achieve only around 17% of these goals.² As global leaders attempt to deal with multiple crises, the gap between our actions and our objectives continues to widen. This critical situation calls for innovative and cost-effective solutions that can amplify positive impact and accelerate progress toward a more sustainable and equitable world.

Artificial intelligence: a potential game-changer for sustainable development
Given the growing political commitment to take climate action, new tools and innovative solutions are urgently needed to tackle these complex challenges. This is evident from the 194 parties that are developing Nationally Determined Contributions under the Paris Agreement, outlining how each country intends to reduce its greenhouse gas emissions and combat climate change.³ While these commitments are crucial, avoiding catastrophic global warming requires more than just goodwill; it demands a deep analytical understanding of complex systems with numerous variables and feedback loops. Modelling these intricate interconnections is a significant challenge, especially with massive and often incomplete data sets on climate patterns and human activities.

This is where Artificial Intelligence (AI) comes in: It excels at processing vast amounts of diverse data and uncovering patterns that traditional analysis might miss. It can facilitate scenario development, accelerate strategy evaluation, optimise operations and monitor progress toward predefined goals. Through AI, we can gain deeper insights into complex systems like supply chains, energy grids, agricultural ecosystems and even the climate itself. AI technologies are advancing rapidly, and nearly 75% of large companies have already integrated them into their business strategies.²

The possibilities of AI in driving climate action 
Building on its transformative potential, AI is already making significant contributions to all the SDGs. For instance, in healthcare, AI has major benefits in transforming and accelerating different processes − from modelling proteins and screening drugs to designing vaccines. It can also support the targeted delivery of aid and public services, help to solve supply chain issues like the last-mile distribution of food in remote areas, optimise forecasting of the long-term impacts of climate change, provide early warnings for natural disasters and deliver expert knowledge directly to frontline aid workers. 

Among the different contributions that AI can make, one of its most essential roles lies in tackling climate change, in alignment with SDG 13 (Climate Action). AI has the potential to drive climate progress across key areas including:³

• Mitigation: AI can help to reduce and remove greenhouse gas emissions by optimising energy consumption, enhancing efficiency in transportation and industrial processes, and facilitating the development of renewable energy sources. It can also provide accurate measurements of emissions, enabling progress to be tracked more effectively.
• Adaptation and resilience: AI can aid organisations and communities in preparing for and responding to the impacts of climate change. This includes developing early-warning systems for extreme weather events, optimising resource allocation during disasters, and modelling climate scenarios to inform policy and planning.
• Foundational capabilities: AI can improve climate modelling, advance climate economics, enhance education and foster innovation. By processing vast amounts of climate data, AI can also enable more accurate predictions and support the development of new technologies and strategies to combat climate change.

Real-world impacts
To illustrate the immense capabilities of AI, we need only consider the role it can play in disaster preparedness. AI-powered tools now provide actionable flood forecasts by combining models that predict river levels with those identifying areas impacted by them, resulting in projections up to seven days in advance of an extreme weather event.⁴ For example, during recent flooding in Somalia, AI platforms delivered risk maps and daily forecasts, enabling targeted actions like risk communications and the floodproofing of critical infrastructure. This demonstrates how AI can significantly enhance disaster response efforts and community resilience. 

Agriculture is another key area where the deployment of AI has already provided benefits, as it can assist farmers in forecasting weather and crop yields, developing sustainable pest control methods and predicting soil erosion, as well as suggesting mitigation measures. These capabilities aim to optimise agricultural practices, promote sustainable crop growing and enhance food security.

Additionally, AI has started reshaping materials engineering by rapidly screening billions of potential low-carbon compounds to replace high-emission materials like steel, cement and plastics. AI-driven labs test selected compounds, with AI interpreting results and designing further experiments, which can drastically shorten research and development timelines.

Transforming businesses with AI
Beyond these sector-specific applications, AI has transformative potential at the company level, unlocking business value and helping to advance sustainable development in multiple ways:²

• Advanced data analysis: Generative AI can extract valuable insights from unstructured data such as text, images and audio and reveal patterns that traditional analytics might miss. This can empower companies to make informed decisions based on comprehensive data.
• Intelligent decision support: Generative AI interprets complex information to support decision-making by providing recommendations, aiming to predict outcomes and offer explanations. In this way, it can help businesses to navigate challenges and develop effective, sustainable strategies.
• Workforce empowerment and efficiency: Generative AI can enhance productivity by acting as a virtual assistant, automating routine tasks like content creation and data analysis. If successfully implemented, this allows teams to focus on strategic initiatives while ensuring consistency and quality in automated outputs, driving innovation and fostering a culture of sustainability.

By applying these AI capabilities in the right way, companies can accelerate sustainable development across several key areas:²

• Enhancing operational efficiency and reducing environmental impacts: AI can optimise the use of resources and improves worker effectiveness, leading to cost savings. It also offers possibilities to lower the environmental footprint of businesses by minimising waste and energy consumption.
• Strengthening sustainable value chains and driving innovation: By analysing supply chain data, AI can help companies to address environmental and social impacts more efficiently, promoting responsible sourcing and comprehensive lifecycle assessments. It can also accelerate innovation in areas like green finance and sustainable product design, fostering breakthrough technologies for sustainable development.
• Risk management and resilience: AI can enable companies to anticipate, assess and mitigate risks related to climate and environmental changes as well as social factors. By analysing trends and predictive data, AI can help to build resilience within operations and supply chains, and to ensure that businesses can adapt to evolving sustainability demands.

Navigating the challenges of AI implementation
While AI holds great promise, it also entails certain risks that require careful management. Without responsible oversight, AI could cause environmental and social harm, while unequal access to technology could widen the digital divide, hindering progress toward the SDGs.

Generative AI introduces new opportunities but also risks like biased outputs, factual errors, misuse and increased resource consumption, as well as societal impacts, such as job displacement and the spread of misinformation. Additionally, the underrepresentation of marginalised groups in AI training data can perpetuate bias and discrimination, especially in critical areas like healthcare, housing and social services.

Bridging the gap: Responsible AI for a sustainable future
AI has significant potential to accelerate progress towards the achievement of the SDGs by 2030. With many of the 17 SDGs not currently on track, AI can contribute to practical solutions in critical areas like climate action, sustainable agriculture and disaster preparedness. Real-world applications − such as AI-driven farming techniques that optimise agricultural practices and AI-enhanced disaster readiness tools − demonstrate how AI can make a tangible difference. By effectively integrating AI into our global strategies and fostering collaboration among governments, businesses and communities, we can address complex challenges more efficiently. Embracing and harnessing AI's capabilities today can help us to bridge the gap between our current efforts and the ambitious targets we have set ourselves in order to secure a sustainable and equitable future.

^* Sustainable Development Solutions Network, Sustainable Development Report 2024
² United Nations Global Compact and Accenture, Gen AI for the Global Goals, 2024
³ BCG and Google, Accelerating Climate Action with AI, Nov 2023
⁴ McKinsey, AI for social good: Improving lives and protecting the planet, May 2024