A Better World with ESG and AI

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“It used to be the case that investors had to compromise between ethics and returns. The whole point about ESG is that ethical businesses should be well-run businesses and should have the best returns.” David Doughty, Chief Executive, Excellencia

 

When the topic of environmental, social, and governance (ESG) initiatives comes up-–whether in corporate boardrooms or online forums—what’s really being discussed are, for the most part, issues of environmental sustainability. While that is certainly an important subset of the ESG universe, it is by no means the complete story.

 

It’s only in the past couple of decades that business schools have begun including the full array of ESG topics into their curricula alongside the usual finance, accounting, and marketing courses. In a fortuitous confluence of timelines, 20 years is also about the length of time that artificial intelligence (AI) has truly been making its presence felt in corporations around the globe, which may have made it inevitable that a corporate focus area as new as ESG should now be getting explicitly linked to AI.

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Photo by jcomp

 

At first blush, AI and ESG might seem nonobvious bedfellows. It’s only when you dig beneath the surface and explore challenges like employee motivation and retention, regulatory compliance, and corporate reputation, that you discover meaningful overlaps between these two seemingly disparate disciplines. 

 

The ESG movement officially began about 20 years ago with the 2005 release of a United Nations-sponsored report titled “Who Cares Wins,” in which the UN invited numerous financial and investment institutions to take part in creating a framework for a new area of focus. Today, the ESG movement is estimated to encompass $30T in assets under management, a figure almost certainly low given that the initiative as defined by the UN focused primarily on the environment, with little emphasis on the other two elements of the ESG abbreviation. The broader debate about the role ESG factors should play in corporate strategy and investment decisions dates back considerably further—as far back as the 1950s—when trade union pension funds realized that investing in social causes could be good for business.

 

But what does any of this have to do with AI? It’s a question best illustrated by looking at areas where SparkCognition has been a leading player since its founding nearly a decade ago.

 

The role of AI in environmental sustainability

 

Many people and organizations associate ESG issues with the environment, and rightly so since issues of environmental sustainability were the initial impetus for what eventually became the ESG model. Since then, AI has become an integral component of sustainability management for many firms, particularly those in the energy sector, including oil and gas, as well as electric power generation. 

 

Predictive maintenance capabilities enabled by AI can proactively identify and address impending equipment failures—failures that could otherwise lead to unscheduled emissions, inefficient equipment operation, wasted resources, and even physical risk to workers near such equipment. In addition to the predictive and proactive maintenance capabilities enabled by AI, the rapidly-emerging field of visual AI can identify unsafe conditions, incipient emergencies like fires or chemical releases, and the presence of workers in unauthorized areas.

 

Finally, through the use of AI-powered natural language processing (NLP) technology, conditions that threaten health, safety, or the environment can be proactively identified by analyzing accident and condition reports in an automated manner. This capability greatly expedites the process of extracting value from this frequently voluminous and unstructured information. 

 

Social responsibility

 

One of the more difficult-to-quantify elements of ESG is social responsibility. Nevertheless, it is an increasingly important factor in investment decisions made by institutional funds and other investors, as well as individual investors. And, potentially more critical for day-to-day company operations, a reputation for social responsibility increasingly plays a role in a firm’s ability to attract and retain skilled workers, managers, and executives. 

 

In an era of skill gaps, high turnover, and increased worker mobility, taking every feasible step to not only improve worker safety and health, but also to take a leading position in diversity, equity, and inclusion (DEI) policies and practices are of paramount importance. 

 

Beyond the more well-known areas of AI implementation in fields like energy and manufacturing, additional ESG/DEI opportunities exist in, for example, the finance and banking arena, where AI applications are now increasingly used to vet new accounts, loan applications, and financial compliance, searching for instances of corruption, fraud, or discrimination.  

 

Governance

 

In response to the widely publicized views of economists like Milton Friedman, who in the 1970s argued that companies who focused on social responsibility were foregoing opportunities to maximize shareholder returns, authors Levering and Moskowitz popularized in a 1998 issue of Fortune magazine an article containing the first listing of “The Best Companies to Work For.” In that piece, the authors highlighted explicit connections between corporate governance and the maximizing of productivity and efficiency, as well as an improved ability to secure the services of the most talented executives and managers, which in turn led to improved financial performance. 

 

Governance touches every aspect of corporate and organizational operations, but in particular, it involves practices around diversity, equity, and inclusion. Through AI’s ability to analyze financial performance, interpret unstructured written documentation, and generally better manage operational risk, it has emerged as an important contributor to a firm’s ability to deliver improved corporate governance, which in turn drives better long-term financial performance and an enhanced company reputation. 

 

ESG as competitive advantage

 

Numerous institutions, universities, and nonprofits have, in recent years, developed indices and analytical frameworks for evaluating corporate ESG performance. Although such performance can be difficult to quantify, its value is nonetheless increasingly important to investors, employees, and even customers—whose buying decisions are driven by a perception of company reputation. More than ever, ESG and DEI practices play an important role in this. 

 

“Improved financial performance due to ESG becomes more marked over longer time horizons.” NYU Stern School Study: ESG and Financial Performance 

 

While usually associated with the more operational aspects of company operations, AI’s ability to contribute meaningfully to a company’s ESG goals has become more widespread and apparent with each passing year, not only in the area of environmental sustainability, but also in social responsibility and corporate governance. AI can play important roles in contributing to the creation of safer, healthier workplaces, and in achieving environmental best practices employees increasingly expect from a prospective employer. 

 

Moving beyond the traditional corporate goals of maximizing profit and shareholder returns requires new and unorthodox approaches to assessing the role of intangible assets in measuring corporate value. Artificial intelligence provides an increasingly rich array of tools to support such approaches.  

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