Shree Priya Thakur | 12 July 2024

Summary

• The Anthroprocene era is marked with stresses on land, air, and water. Even if all the Paris Agreement commitments are met, by 2030 average global temperatures will rise to three degrees celsius above pre-industrial levels.

• AI integrated tools provide real time monitoring, risk analysis, impact measurement, and the ability to reshape the public narrative; all which are crucial to the climate modelling efforts of the 21st century. 

• Several companies have scaled pilot projects for coral monitoring and aquafarms but sophisticated efforts require the standardisation of regulations across jurisdictions.

The planet today faces unprecedented levels of environmental stress. Greenhouse gas (GHG) levels are the highest in three million years and are expected to be a chronic strain on economic progress, despite the Paris Agreement. Even if the pledges of the Paris Agreement were met in entirety, the global average temperatures in 2100 are projected to be three degree Celsius higher than the pre-industrial levels. Moreover,concerns are growing over the emergence of a “savannah state” as the Amazon basin is experiencing deforestation rates which could reduce regional rainfall by 8% by 2050. Coupled with this is the loss of biodiversity, specifically corals, and the stresses on ground water use; all of which indicate that a technological intervention is necessary. 

The overlap of the anthropocene era with the digital one comes at a time where AI applications in sustainability can generate lasting economic gains. According to  recent research by PwC, the use of AI in sustainability efforts  could contribute USD 5.2 trillion to the global economy by 2030, translating into a 4.4% increase in GDP when compared to a scenario without AI. The World Economic Forum, too, projects that regions such as North America, East Asia, and Europe could each see GDP gains exceeding USD 1 trillion. The power of AI to harness data, provide real time insights, and accurately measure progress could be transformative in the two sectors responsible for the highest levels of emissions: transport and energy. AI induced tools can reduce emission in transport and energy sectors by 1.7% and 2.2% respectively. 

Four Ways AI Can Help

Real Time Monitoring 

The World Economic Forum notes that 50% of the carbon reductions needed to achieve net zero emissions will come from technologies not yet invented, which explains  why innovation in AI powered tools has caught the eye of leading multinational corporations. AI’s ability to provide real time monitoring is crucial, particularly for the underfunded Sustainable Development Goals (SDGs). For instance, AI can aid SDG 14 (Life Below Water) by offering advanced ocean data, including biodiversity metrics, to support coral restoration. Companies like Pano AI are using AI to detect wildfires in real time, while NatureDot employs AI to monitor aquafarms. 

Financial Analysis and Risk Management 

The year 2023 was the hottest on record, highlighting the urgency for investors to factor in climate in their risk exposure analyses. AI powered tools can analyse complex datasets, including financial data, to dissect trends and risks associated with climate change. BlackRock, for instance, uses AI algorithms to track the carbon footprints resulting from various investments, helping investors and startups make informed decisions to align their portfolios with sustainability goals. 

Impact Measurement 

AI offers unparalleled precision and efficiency in measuring environmental impact. The European Commission, for example, uses AI to track the progress on SDG 6 (Clean Water and Improved Sanitation). By leveraging AI, global GHG emissions could be reduced by 4% by 2030, equivalent to the combined 2030 emissions of Australia, Japan, and Canada. AI powered impact measurement tools improve the elimination of bias and provide streamlining of data from multiple sources. 

Reshaping the Narrative

AI can revolutionise how society perceives sustainability, shifting the narrative from one of sacrifice to one of efficiency and innovation. In sectors like marketing, retail, and operations, AI applications can nudge consumer choices. Further, because AI facilitates economies of scale, it can usher in affordability through ramped up supply. While there are concerns of AI washing and utilising Freeware to train bots, it can aid ESG (Environmental, Social, and Governance) policies through elimination of human error, provide data visualisation, and use Natural Language Processing to democratise access to information. 

Despite its immense potential, there are challenges to using AI in sustainability efforts. Issues of inaccurate data and data silos where environment related information is fragmented across different jurisdictions pose a hurdle. Further, even training AI models require significant computational power consuming large amounts of energy, in turn increasing the carbon footprint. High initial investments and issues of privacy and prejudice are other complexities which must be addressed. Yet, AI can help make sustainability a more positive story and be the driving force powering the sustainability efforts of the 21st century. 

Forecast

• Short-term

  • It is highly likely that the current lack of standardisation surrounding AI guidelines will lead to inconsistencies and regulatory hurdles. Increased attention to develop regional frameworks would be necessary to scale AI powered pilot projects.

• Medium-term

  • By 2030, AI integrated smart grids are expected to be more widespread, reducing energy wastage. Particularly in the UK, this aligns with the new government’s decarbonisation targets set for 2030 . Further, the export of sophisticated AI tools to developing countries is likely (as is done with space equipment) to enable innovations such as predictive waste management and automated waste sorting.