When you think of AI, sustainability may not be the first thing that comes to mind. But with rapid advances in technology, AI is poised to play a major role in the future of our economy, health, and environment.
From enhancing financial inclusion to optimizing energy use and improving healthcare outcomes, AI's capabilities are vast and varied. And for the past decade, AI has intersected with some of the most important objectives we have as a planet—the United Nations Sustainable Development Goals.
Throughout the 2010s, members of the United Nations gathered to discuss major issues plaguing society, such as poverty, inequality, and climate change. The outcome of these meetings was a set of 17 Sustainability Development Goals (or SDGs) for ending poverty, protecting the planet, and ensuring a more peaceful and just world by 2030.
All United Nations Member States adopted these goals in 2015:
While these goals act as a useful framework, they also present enormous challenges.
For one, the 17 goals are highly interconnected. Ending poverty, for example, must go hand-in-hand with strategies to improve health and education, reduce inequality, and spur economic growth. And the United Nations is on a tight timeline—in the grand scheme, 15 years is not a long time for goals of this size and scope.
To foster alignment and achieve success in that short timeframe, national governments must rely heavily on enterprise businesses that have the resources, global reach, and influence across societies and economies that governments need to enact meaningful change.
Thankfully, advances in data analytics, automation, and machine learning have enabled many companies to drive progress toward each of the 17 SDGs, making the world a better place while earning consumer trust and driving revenue.
AI is playing a pivotal role in advancing Sustainable Development Goals through the following sectors:
Through machine learning algorithms and data analytics, financial institutions are better able to find and extend credit to previously unreachable populations, making significant contributions to Goal 1: No Poverty. For example, fintech startups like Tala use AI to analyze mobile phone usage patterns to provide microloans in countries like Kenya, Tanzania, and India.
AI has also facilitated significant advancements in Goal 9: Industry, Innovation, and Infrastructure through:
And some financial institutions are even using AI to find and develop sustainable investing strategies and analyze environmental risk in portfolios, advancing Goal 13: Climate Action.
Healthcare has a natural tie to Goal 3: Good Health and Well-being, and AI is leading the way, particularly in terms of diagnostics. Today, AI algorithms are interpreting medical images, such as X-rays and MRIs, more quickly and accurately than human radiologists, and many leading healthcare companies are implementing AI in their diagnostics workflow:
AI is also crucial in managing patient care, especially for chronic diseases. AI systems are monitoring patient stats in real-time through wearable devices, alerting healthcare providers when intervention is needed, thereby improving overall patient outcomes.
AI's big data analysis capabilities aid in data-driven policymaking for urban development, aligning with Goal 11: Sustainable Cities and Communities. For instance, Singapore uses AI to manage traffic flow and reduce congestion through its Intelligent Transport Systems, which utilize sensors and data analytics to optimize road network efficiency and improve urban mobility.
AI is balancing energy supply and demand, making significant strides in Goal 7: Affordable and Clean Energy. NextEra Energy, a Fortune 200 company, leverages predictive analytics and machine learning to manage renewable energy outputs from wind and solar farms based on weather patterns, improving efficiency and eliminating energy waste. They own several subsidiaries, including America's largest electric utility, Florida Power & Light Company, allowing them to provide clean, affordable, reliable electricity to nearly 6 million customer accounts.
AI also helps in smart grid management. Utilities use AI to analyze data from smart meters and sensors to detect faults in the network and predict equipment failures before they occur. This proactive maintenance helps reduce downtime and improve the reliability of energy supply. In May 2024, Siemens launched a series of new AI-based apps for more efficient operation of water infrastructure on their Xcelerator marketplace.
Retail and CPG giants are using AI to make headway on Goal 12: Responsible Consumption and Production. Since 2020, Amazon has used natural language processing and generative AI to make even more accurate predictions of what customers will love and buy across Amazon’s vast catalog of products—forecasting demand for over 400 million products per day. Their highly accurate models reduce overstock and understock situations, which, in turn, minimizes waste and supports more sustainable consumption patterns.
Procter & Gamble has followed suit, partnering with Microsoft to implement AI, machine learning, and edge computing services across its manufacturing supply chain to:
AI technologies also help personalize shopping experiences, learning customers’ shopping preferences and suggesting products they are more likely to purchase, decreasing return rates and associated waste.
AI technology isn’t just a futuristic ideal. It’s a practical tool already making significant strides toward the UN Sustainable Development Goals, analyzing vast datasets, predicting trends, and optimizing processes faster and better than ever.
As we look to the future, the continued integration of AI into SDG efforts will be paramount to achieving them by 2030. And AI's applications are as diverse as the goals themselves. The key is to harness the potential of AI responsibly and creatively.
When you think of AI, sustainability may not be the first thing that comes to mind. But with rapid advances in technology, AI is poised to play a major role in the future of our economy, health, and environment.
From enhancing financial inclusion to optimizing energy use and improving healthcare outcomes, AI's capabilities are vast and varied. And for the past decade, AI has intersected with some of the most important objectives we have as a planet—the United Nations Sustainable Development Goals.
Throughout the 2010s, members of the United Nations gathered to discuss major issues plaguing society, such as poverty, inequality, and climate change. The outcome of these meetings was a set of 17 Sustainability Development Goals (or SDGs) for ending poverty, protecting the planet, and ensuring a more peaceful and just world by 2030.
All United Nations Member States adopted these goals in 2015:
While these goals act as a useful framework, they also present enormous challenges.
For one, the 17 goals are highly interconnected. Ending poverty, for example, must go hand-in-hand with strategies to improve health and education, reduce inequality, and spur economic growth. And the United Nations is on a tight timeline—in the grand scheme, 15 years is not a long time for goals of this size and scope.
To foster alignment and achieve success in that short timeframe, national governments must rely heavily on enterprise businesses that have the resources, global reach, and influence across societies and economies that governments need to enact meaningful change.
Thankfully, advances in data analytics, automation, and machine learning have enabled many companies to drive progress toward each of the 17 SDGs, making the world a better place while earning consumer trust and driving revenue.
AI is playing a pivotal role in advancing Sustainable Development Goals through the following sectors:
Through machine learning algorithms and data analytics, financial institutions are better able to find and extend credit to previously unreachable populations, making significant contributions to Goal 1: No Poverty. For example, fintech startups like Tala use AI to analyze mobile phone usage patterns to provide microloans in countries like Kenya, Tanzania, and India.
AI has also facilitated significant advancements in Goal 9: Industry, Innovation, and Infrastructure through:
And some financial institutions are even using AI to find and develop sustainable investing strategies and analyze environmental risk in portfolios, advancing Goal 13: Climate Action.
Healthcare has a natural tie to Goal 3: Good Health and Well-being, and AI is leading the way, particularly in terms of diagnostics. Today, AI algorithms are interpreting medical images, such as X-rays and MRIs, more quickly and accurately than human radiologists, and many leading healthcare companies are implementing AI in their diagnostics workflow:
AI is also crucial in managing patient care, especially for chronic diseases. AI systems are monitoring patient stats in real-time through wearable devices, alerting healthcare providers when intervention is needed, thereby improving overall patient outcomes.
AI's big data analysis capabilities aid in data-driven policymaking for urban development, aligning with Goal 11: Sustainable Cities and Communities. For instance, Singapore uses AI to manage traffic flow and reduce congestion through its Intelligent Transport Systems, which utilize sensors and data analytics to optimize road network efficiency and improve urban mobility.
AI is balancing energy supply and demand, making significant strides in Goal 7: Affordable and Clean Energy. NextEra Energy, a Fortune 200 company, leverages predictive analytics and machine learning to manage renewable energy outputs from wind and solar farms based on weather patterns, improving efficiency and eliminating energy waste. They own several subsidiaries, including America's largest electric utility, Florida Power & Light Company, allowing them to provide clean, affordable, reliable electricity to nearly 6 million customer accounts.
AI also helps in smart grid management. Utilities use AI to analyze data from smart meters and sensors to detect faults in the network and predict equipment failures before they occur. This proactive maintenance helps reduce downtime and improve the reliability of energy supply. In May 2024, Siemens launched a series of new AI-based apps for more efficient operation of water infrastructure on their Xcelerator marketplace.
Retail and CPG giants are using AI to make headway on Goal 12: Responsible Consumption and Production. Since 2020, Amazon has used natural language processing and generative AI to make even more accurate predictions of what customers will love and buy across Amazon’s vast catalog of products—forecasting demand for over 400 million products per day. Their highly accurate models reduce overstock and understock situations, which, in turn, minimizes waste and supports more sustainable consumption patterns.
Procter & Gamble has followed suit, partnering with Microsoft to implement AI, machine learning, and edge computing services across its manufacturing supply chain to:
AI technologies also help personalize shopping experiences, learning customers’ shopping preferences and suggesting products they are more likely to purchase, decreasing return rates and associated waste.
AI technology isn’t just a futuristic ideal. It’s a practical tool already making significant strides toward the UN Sustainable Development Goals, analyzing vast datasets, predicting trends, and optimizing processes faster and better than ever.
As we look to the future, the continued integration of AI into SDG efforts will be paramount to achieving them by 2030. And AI's applications are as diverse as the goals themselves. The key is to harness the potential of AI responsibly and creatively.