The AI Revolution in Sustainability

Artificial Intelligence is a rapidly evolving technology that is poised to impact every major industry in one way or another. AI is unique in its ability to perform tasks that usually require human intelligence by measuring and analyzing vast amounts of complex datasets, improving itself over time, and producing predictions and recommendations that humans can use in decision-making. AI does this all at faster speeds and more efficiently than its human counterparts. These fundamental components of AI explain how this nascent technology could revolutionize the way we mitigate and adapt to climate change.

Measuring and analyzing

Sustainability is a complicated puzzle involving environmental, biological, geographic, logistical, and political variables and therefore needs a technology like AI that can manage those complex, interconnected datasets1. For example, AI can be used to measure the carbon footprint of a product2 throughout its lifecycle while connecting that data to policies and scientific understandings. Without such measurement and analysis, decision-makers are neither incentivized nor equipped to implement more sustainable policies.


Using AI as a monitoring tool can make climate adaptation more efficient, cost-effective and safe. AI is already being used to monitor environmentally destructive actions like illegal logging3 or other climate-related threats to human health like air quality2. Limited resources can therefore be deployed more strategically to investigate environmental threats or to proactively prepare for and respond to natural disasters more quickly.


Low-hanging fruit in the effort to achieve sustainability goals is to reduce inefficiencies. One company4 has developed an AI-enabled platform that juggles complex information such as safety, cost, and emissions to make shipping more sustainable by optimizing fuel use, routes, speed, and other factors. They already prevented more than 440,000 tons of CO2 from being emitted by their customers’ ships last year. AI can also be used to optimize the process for new technological innovation3 that might help address certain sustainability concerns, such as creating more efficient energy systems and batteries or developing new methods of carbon capture. AI can be used to optimize any industry to save time, energy, and money.


AI is a powerful tool for modeling future scenarios. By feeding complex datasets into an AI system with specific outcomes in mind, humans can leverage the technology to better predict climate impact like floods3, wildfires, sea level rise, pest infestations3, and hurricanes. These predictive models act as powerful decision-making tools as we adapt to increasingly frequent and severe climate events.


Perhaps the greatest strength of AI in implementing changes toward sustainability is its ability to make recommendations. So far this year, more than 50% of CEOs5 have compensation associated with meeting specific sustainability measures, which is triple the amount over 2022. AI can be used to recommend where and how to make changes for the biggest impact at the lowest cost.

AI is a key investment category for the modern investor, especially those interested in sustainability. In fact, investors poured $70.1 billion6 into climate tech in 2022, which was an 89% increase over 2021. TrueShares Technology, AI, and Deep Learning ETF (LRNZ) offers exposure to the foundational technologies needed for AI to function, regardless of industry or use-case. The concentrated fund is actively managed to give investors the confidence of knowing that a qualified manager is constantly monitoring industry trends and company fundamentals as these technologies and their uses change and evolve over time.


Active management does not guarantee investment success. There is no guarantee that the fund will meet its investment objective. 

Artificial Intelligence, Machine Learning and Deep Learning Investment Risk – the extent of such technologies’ versatility has not yet been fully explored. There is no guarantee that these products or services will be successful and the securities of such companies, especially smaller, start-up companies, are typically more volatile than those of companies that do not rely heavily on technology.