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How generative AI can help individuals invest in ESG-forward companies
The cofounder of Daizy says we need to untangle the E, the S, and the G in ESG; report, track, and measure each category separately; and make that data available to everyone.
BlackRock CEO Larry Fink’s assertion at the Aspen Ideas Festival in June that “ESG has been weaponized” is not only accurate, but it has opened the door to a larger public conversation that involves institutions as well as individual investors.
Specifically, the 1.8 billion millennials, who were a key factor in the rise of ESG investing, and their younger demographic siblings, Gen Z—who had a disposable income of $360 billion in 2022, even though most of them have not even entered the workforce.
ESG assets under management, predicted to reach $ 33.9 trillion by 2026, according to PwC, rely on a data set that, until recently, is only accessible to institutional investors. Further, that data is bucketed as one ESG measure and characterized by a vast range of frameworks and reporting requirements. This puts individual investors at a significant disadvantage.
The solution is simple: We need to untangle the Environmental, Social, and Governance in ESG by reporting, tracking, and measuring each category separately, and making that data available to everyone.
Fortunately, the conversational power of generative AI has reached a maturity where every investor can now access this data for free, personalize their environmental, social, and governance criteria, and make informed bets with their capital through companies like the one I cofounded, Daizy.
COMPARING COMPELLING STOCKS
For individual investors, being able to access an untangled set of environmental, social, and governance metrics unmasks a stock that might appear to be an ESG leader by scoring exponentially well in one category but is performing well below the S&P average in another.
It would also highlight a company that may not score well on environmental today but ranks exceptionally high in social and governance, and has put in place the right commitments, strategic plans, and actions to emerge as a leader who successfully made the transition to net zero within the timeline they have publicly reported.
Let’s say, for example, you are considering investing in Tesla, as a company that is leading the EV transition, but you care equally about board diversity in your investment portfolio.
Tesla scores off the charts on the environmental, with an almost zero carbon footprint in its vehicles, but untangling the ESG data also shows the company has serious problems when it comes to diversity (a key social component) and governance.
In the current framework, Tesla is an ESG leader because of its environmental score, but whether the stock is a good long-term bet requires many other considerations—including whether it can improve its social and governance scores.
In contrast, General Motors, under Mary Barra, has said it plans to make its global products and operations carbon neutral by 2040 and only sell vehicles with zero tailpipe emissions by 2035. It’s a public, transparent plan, with measurable milestones, aimed at ensuring the company captures the EV opportunity while also mitigating the downside risk of ignoring this market. Further, Mary Barra’s GM is an indisputable leader in social and governance metrics, with GM boasting 6 women on its 13-member board of directors.
As the energy transition accelerates—one of the most important investment opportunities in the decade ahead—identifying environmental, social, and governance may be the best way to ensure we are rewarding the companies that are getting the transition right and will not be left holding billions in capital assets that are irrelevant 10 years from now.
DEMOCRATIZING NEXT GENERATION INVESTING WITH AI
Next generation investors have already driven some $50 billion into ESG funds. As elected officials continue to politicize and block access to ESG data for institutions—as evidenced by Florida Governor Ron DeSantis’ anti-ESG rule, which bars the state’s $186 billion pension fund from considering ESG data—individual investors have a significant opportunity to access this data and make informed investments on their own terms.
For example, generative AI allows investors to “converse” with this important data in a manner that is as simple as entering a query like, “Does Coca Cola have lower carbon emissions and higher board diversity than the S&P 500?” or, “Is Microsoft using renewable energy sources and what is their net zero target?”
The most important step for individual investors right now, is to take advantage of free sources of institutional-grade environmental, social, and governance data, personalize your investing criteria based on your own values and performance requirements, and then follow the data to where values-based investments and extraordinary returns intersect.
At scale, the impact of investors who are voting with their capital may be the fastest path to progress across all three elements of environmental, social, and governance and one of the surest ways to de-weaponize ESG in a way that delivers economic, environmental, and social returns for all investors.