Artificial intelligence (AI) is revolutionary in its ability to mitigate further climate change, but it's not capable of addressing the root cause of the problem or significantly changing the magnitude of the current climate crisis, Alexis Normand, co-founder of carbon accounting software vendor Greenly, told SDxCentral.

AI plays an "immense role" in managing energy efficiency and reducing carbon emissions from industries like transportation, agriculture, and manufacturing. It's also instrumental in predicting extreme weather events exacerbated by climate change, "which can further serve as information on how our daily activities are impacting habitual weather patterns, while also preparing us for the impact of natural disasters in advance," Normand said.

Despite its ability to "help us respond more rapidly and take the precautionary measures necessary to prevent further climate change," AI carries its own set of flaws.

On a technological level, it can be difficult for AI programs to determine the correct data set, and they often struggle with data security, data storage, and "eliminating bias factors that can overall impact the end data," Normand explained.

And AI presents financial barriers, too. It's expensive to install and requires highly technical specialists, meaning a company with a smaller budget can't take advantage of AI for climate mitigation.

From a social perspective, "AI can be hard for the rest of the world to get on board with," despite how commonly it is used in everyday life. Normand credits this hesitancy to humanity's tendency to not accept data gathered without human assistance.

He noted that "transparency is difficult to build enough, and AI could present further challenges in establishing trust within a sector and relative business partners." This would be detrimental to the global fight against climate change, he added, because transparency is a crucial component of fostering environmentally sustainable business practices and norms.

Another AI flaw often cited is the carbon intensity of running powerful AI workloads in the cloud. Normand acknowledged while AI does contribute to carbon intensity because of the electricity needed for AI compute, companies should see AI as a long-term tool for mitigating climate change.

"It is important to note that AI is also contributing to providing preventative measures to global warming predicaments that would otherwise go unnoticed," Normand said.

He likens this concept to carbon capture and storage systems, which are expensive to install and require a lot of energy to operate, but "they are ultimately benefiting the environment in the long run by reducing the amount of carbon dioxide emissions directly from the source of industrial activity," he explained.

One of AI's most promising use cases is in data analytics and climate reporting as it can lead to implementing preventative mitigation strategies that wouldn't be suggested otherwise, Normand said.

"In other words, recovering from the environmental or urban damage from natural disasters caused by climate change used to be something that could only be handled after the natural disaster itself occurred, but with AI – it’s possible to mitigate the effects of climate change before they happen, and allow for better decision-making in various environmental protection strategies," he explained.

AI's proactive perspective is a unique capability and could "be a game changer" against climate change, but at the end of the day, AI can't tackle the excessive global carbon dioxide and greenhouse gas emissions at the crux of the issue.

"AI can help to predict the future impact of climate change, but AI doesn’t have the power to change the past and the current global warming crisis we are already facing today," he noted.

To that point, enterprises should focus primarily on strategies that reduce environmental impact. "It’s imperative that all companies and individuals around the world remain cognizant of the importance of the strategies to reduce carbon emissions in the first place," Normand said.