The role of AI in sustainable investments

The intersection between AI and sustainable investing is potentially transformative for the sustainable finance industry. But there are concerns and risks potential users need to consider.

The data gap

The sustainable investing market is plagued by imperfect and inaccessible information due to much of the data collection being time consuming, manual and therefore prone to error. This, along with varying reporting frameworks across different jurisdictions, is a constant headache for investors.

Partly due to these problems, sustainable investing is facing resistance in some sectors. Greenwashing concerns are still putting some investors off from transactions advertised as "sustainable", particularly as we see an influx of anti-greenwashing regulations being introduced.

To what extent can AI offer a solution?

Arguably the best use case for AI in sustainable investing is data verification and analysis. The technology has the capacity to process more data and produce more accurate results than could be undertaken manually, increasing the underlying confidence in sustainability data. Predictive modelling can fill data gaps by providing more accurate substitutes for any missing data points. AI technologies can also to some extent guard against greenwashing through verification and sentiment analysis.

Whilst the more efficient sustainability processes provided by AI is a positive development, the technology has its limitations. The lack of standardized certifications and web of regulatory frameworks would continue to complicate comparisons between investments. Any confusion is compounded when, with the assistance of generative AI, different reporting obligations are fulfilled using the same data, just with different labels. Predictive modelling used to complete any "missing data" relies on a minimum level of real data to provide reliable results, and the manual element cannot be removed completely.

So whilst the use of AI has great potential to increase transparency and accessibility in sustainable investing, it is not perfect. Consequently it is essential to exercise caution to protect against potential governance issues that may arise during any AI process.

AI may be able to talk, but can it replace the human element?

In short, not yet. AI can't make decisions with the sentiment of human intelligence, and currently lacks the ability to spot mistakes when working with language, leaving users exposed to errors and compliance risks. The ethics of AI is not a new topic, but for sustainable investors this will be under intense scrutiny.

AI technology can be both environmentally and financially costly. It's clear less energy-intense AI training models are needed, and consolidating resources in AI development would be more cost-effective, fairer and introduce greater competition.

Data privacy when using the technology remains a major concern. Even with the EU's landmark AI Act, being introduced imminently – which will most likely be the gold standard referential – there will a lag in its effect as the majority of its provisions will likely not be enforceable until at least two years after the consolidated text is finalised.

A promising outlook

The full potential of AI has yet to be seen, but in its present form it can greatly streamline sustainable reporting, and in turn increase confidence in and scale sustainable investing. As with all new technologies, a cautious approach is advised on any AI deployment in sustainable investing to ensure safe and controlled growth in both areas.

While AI can help resolve data issues in sustainable investing, it can create problems such as information breaches and inherent bias in data

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