Why AI is critical to meet rising ESG demands

Could artificial intelligence (AI) help companies meet growing expectations for environmental, social and governance (ESG) reporting? 

Certainly, over the past couple of years, ESG issues have soared in importance for corporate stakeholders, with increasing demands from investors, employees and customers. According to S&P Global, in 2022 corporate boards and government leaders “will face rising pressure to demonstrate that they are adequately equipped to understand and oversee ESG issues — from climate change to human rights to social unrest.”

ESG investing, in particular, has been a big part of this boom: Bloomberg Intelligence found that ESG assets are on track to exceed $50 trillion by 2025, representing more than a third of the projected $140.5 trillion in total global assets under management. Meanwhile, ESG reporting has become a top priority that goes beyond ticking off regulatory boxes. It’s used as a tool to attract investors and financing, as well as to meet expectations of today’s consumers and employees.  

But according to a recent Oracle ESG global study, 91% of business leaders are currently facing major challenges in making progress on sustainability and ESG initiatives. These include finding the right data to track progress, and time-consuming manual processes to report on ESG metrics.

“A lot of the data that needs to be collected either doesn’t exist yet or needs to come from many systems,” said Sem J. de Spa, senior manager of digital risk solutions at Deloitte. “It’s also way more complex than just your company, because it’s your suppliers, but also the suppliers of your suppliers.” 

ESG data challenges driving use of AI

That is where AI has increasingly become part of the ESG equation. AI can help manage data, glean data insights, operationalize data and report against it, said Christina Shim, VP of strategy and sustainability, AI applications software at IBM. 

“We need to make sure that we’re gathering the mass amounts of data when they’re in completely different silos, that we’re leveraging that data to improve operations within the business, that we’re reporting that data to a variety of stakeholders and against a very confusing landscape of ESG frameworks,” she said. 

According to Deloitte, although a BlackRock survey found that 92% of S&P companies were reporting ESG metrics by the end of 2020, 53% of global respondents cited “poor quality or availability of ESG data and analytics” and another 33% cited “poor quality of sustainability investment reporting” as the two biggest barriers to adopting sustainable investing. 

Making progress is a must, experts say. Increasingly, these ESG and sustainability commitments are no longer simply nice to have,” said Shim. “It’s really becoming kind of like a basis of what organizations need to be focused on and there are increasingly higher standards that have to be integrated into the operations of all businesses,” she explained. 

“The challenge is huge, especially as new regulations and standards emerge and ESG requirements are under more scrutiny,” said De Spa. This has led to hundreds of technology vendors flooding the market that use AI to help tackle these issues. “We need all of them, at least a lot of them, to solve these challenges,” he said.

The human-AI ESG connection

On top of the operational challenges around ESG, the Oracle study found 96% of business leaders admit human bias and emotion often distract from the end ESG goals. In fact, 93% of business leaders say they would trust a bot over a human to make sustainability and social decisions. 

“We have people who are coming up now who are hardwired for ESG,” Pamela Rucker, CIO advisor, instructor for Harvard Professional Development, who helped put together the Oracle study. “The idea that they would trust a computer isn’t different for them. They already trust a computer to guide them to work, to give them directions, to tell them where the best prices are.” 

But, she added, humans can work with technology to create more meaningful change and the survey also found that business leaders believe there is still a place for humans in ESG efforts, including managing making changes (48%), educating others (46%), and making strategic decisions (42%). 

“Having a machine that might be able to sift through some of that data will allow the humans to come in and look at places where they can add some context around places where we might have some ambiguity, or we might have places where there’s an opportunity,” said Rucker. “AI gives you a chance to see more of that data, and you can spend more time trying to come up with the insights.” 

How companies can get started with AI and ESG

Seth Dobrin, chief AI officer at IBM, told VentureBeat that companies should get started now on using AI to harness ESG data. “Don’t wait for additional regulations to come,” he said. 

Getting a handle on data is essential as companies begin their journey towards bringing AI technologies into the mix. “You need a baseline to understand where you are, because you can make all the goals and imperatives, you can commit to whatever you want, but until you know where you are, you’re never gonna figure out how to get to where you need to get to,” he said. 

Dobrin said he also sees organizations moving from a defensive, risk management posture around ESG to a proactive approach that is open to AI and other technologies to help. 

“It’s still somewhat of a compliance exercise, but it’s shifting,” he said. “Companies know they need to get on board and think proactively so that they are considered a thought leader in the space and not just a laggard doing the bare minimum.” 

One of the key areas IBM is focusing on, he added, is helping clients connect their ESG data and the data monitoring with the actual operations of the business. 

“If we’re thinking about business facilities and assets, infrastructure and supply chain as something that’s relevant across industries, all the data that’s being sourced needs to be rolled up and integrated with data and process flows within the ESG reporting and management piece,” he said. “You’re sourcing the data from the business.” 

Deloitte works with Signal AI on ESG efforts

Deloitte recently partnered with Signal AI, which offers AI-powered media intelligence, to help the consulting firm’s clients spot and address supplier risks related to ESG issues. 

“With the rise of ESG and as businesses are navigating a more complex environment than ever before, the world has become awash in unstructured data,” said David Benigson, CEO of Signal AI. “Businesses may find themselves constantly on the back foot, responding to these issues reactively rather than having the sort of data and insights at their fingertips to be at the forefront.” 

The emergence of machine learning and AI, he said, can fundamentally address those challenges. “We can transform data into structured insights that help business leaders and organizations better understand their environment and get ahead of those risks, those threats faster, but also spot those opportunities more efficiently too – providing more of an outside-in perspective on issues such as ESG.” 

He pointed to recent backlash around “greenwashing,” including by Elon Musk (who called ESG a “scam” because Tesla was removed from S&P 500’s ESG Index). “There are accusations that organizations are essentially marking their own homework when it comes to sorting their performance and alignment against these sorts of ESG commitments,” he said. “At Signal, we provide the counter to that – we don’t necessarily analyze what the company says they’re going to do, but what the world thinks about what that company is doing and what that company is actually doing in the wild.” 

Deloitte’s de Spa said the firm uses Signal AI for what it calls a “responsible value chain” – basically, supplier risk management. 

“For example, a sustainable organization that cleans oceans and rivers from all kinds of waste asked us to help them get more insight into their own value chain,” he said. “They have a small number of often small suppliers they are dependent on and you cannot easily keep track of what they’re doing.” With Signal AI, he explained, Deloitte can follow what is happening with those companies to identify if there are any risks – if they are no longer able to deliver, for example, if there is a scandal that puts them out of business, or if the company is causing issues related to sustainability.” 

In one case, Deloitte discovered a company that was not treating their workers fairly. “You can definitely fight greenwashing because you can see what is going on,” he said. “You can leverage millions of sources to identify what is really happening.” 

ESG will need AI and humans going forward

As sustainability and other ESG-related regulations begin to proliferate around the world, AI and smart technology will continue to play a crucial role, said Deloitte’s de Spa. “It’s not just about carbon, or even having a responsible value chain that has a net zero footprint,” he said. “But it’s also about modern slavery and farmers and other social types of things that companies will need to report on in the next few years.” 

Going forward, a key factor will be how to connect and integrate data together using AI, said IBM’s Dobrin. “Many offer a carbon piece or sell AI just for energy efficiency or supply chain transparency,” he said. “But you need to connect all of it together in a one-stop-shop, that will be a total game-changer in this space.” 

No matter what, said Rucker, there is certainly going to be more for AI-driven tools to measure when it comes to ESG. “One of the reasons I get excited about this is because it’s not just about a carbon footprint anymore, and those massive amounts of data mean you’re going to have to have heavy lifting done by a machine,” she said. “I see an ESG future where the human needs the machine and the machine needs the human. I don’t think that they can exist without each other.”