Environmental, social and governance, better known as ESG, is increasingly important to investors. Companies are looking for better ways to report on ESG issues in an effort to capture the interest of investors who care about ESG and demonstrate their social commitments. Artificial intelligence can help companies dig into the gold mine of data surrounding ESG to strategize, plan and report. Learn how businesses are already leveraging AI externally to report ESG data and how it's impacting investing decisions.
ESG Data and Artificial Intelligence Use Cases
Investors want to see more ESG commitments from companies. They want to invest in companies whose ESG commitments align with theirs, and some are actively disinvesting in companies with differing views of what's important when it comes to environmental, social or governance issues. While using ESG data to play to the sympathies of potential investors sounds great, in reality it's a lot harder than it seems.
While all sides agree on the importance of ESG reporting, there are few standards to guide reporting. Likewise, there are no uniformly adopted reporting methodologies businesses can use to present the data they have gathered. This leaves businesses to make their own decisions when it comes to aggregating and reporting ESG data.
In the absence of robust quantitative data, many businesses are supplying qualitative data instead. Unfortunately, qualitative data based on anecdotes, stories and perceptions is no substitute for numbers that make the case. This is where AI and ESG can shine. AI is capable of ingesting and analyzing data with more efficiency than human employees without sacrificing accuracy. Deep learning and machine learning technologies make AI trainable so it can perform at a higher level, allowing companies to dig into the data on their end and use it to support strategic initiatives in line with demonstrated commitments.
AI can also solve current issues around transparency and accountability. Where a qualitative anecdote can appeal to the emotions, numbers don't lie. By using ESG data and artificial intelligence to tell a convincing story around performance, companies can win points.
Lastly, AI can help investors sort through the commitments made by companies to identify the best investment options given their preferences. It's the solution to large-scale investments when careful analysis is required, but far too time-consuming to be realistic.
Of course, ESG data isn't just something investors can use to find companies that align with their principles. It's good business practice, period. Thus, we should point out that using AI in ESG investing and reporting will benefit the company as well as potential investors.
What's Next for AI in ESG Investing?
We tend to think of AI as being adept at data mining tasks, yet ill-suited for tasks that require complex analysis. However, algorithms are increasingly becoming fluent in human tone. This means they can mine data for the sort of meaningful subtleties that matter when we're talking about ESG. Humans may still be better at this task than machines, but where AI has an edge is the speed with which it can ingest and process the breadth of information required.
To give an example of where things are headed with AI and ESG, AI can “read” the script of a CEO's speech and pick out keywords related to ESG, such as diversity. The AI can then use tone processing, or what programmers refer to as sentiment analysis, to gauge how the CEO really feels about diversity. It understands not just the words that are said but the intent behind them. The AI could then quantify the level of commitment based on word choice and sentiment. This will help companies understand where their intent and actions differ and can help investors make the wisest choices.
ESG investing is only going to become more important in the coming years. The time is now to identify ESG commitments, determine the type of data to measure to track performance, and implement ESG reporting software that leverages AI, so you can offer the robust sort of reporting that drives investment decisions.