Why AI is critical to meeting rising ESG requirements

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

Certainly, in recent years, ESG issues have become increasingly important to business stakeholders, with increasing demands from investors, employees and customers. According to S&P GlobalIn 2022, boards of directors and heads of government will face “increasing pressure to demonstrate that they are sufficiently equipped to understand and oversee ESG issues – from climate change to human rights to social unrest.”

ESG investments in particular have 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 beyond checking regulatory boxes. It is used as a tool to attract investors and financing, as well as to meet the expectations of today’s consumers and employees.

But according to a recent Oracle’s Global ESG Research, 91% of business leaders currently face 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.

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

ESG data challenges driving the use of AI

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

“We need to make sure that we collect the massive amounts of data when they’re in completely different silos, that we use that data to improve operations within the company, that we report that data to different stakeholders and against a very confusing landscape of ESG frameworks,” she said.

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

Making progress is a must, experts say. These ESG and durability commitments are no longer just fun to have,” says Shim. “It’s really starting to become a kind of foundation that organizations need to focus on and there are increasing standards that need to be integrated into the operations of all companies,” she explains.

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

The connection between humans and AI ESG

In addition to the operational challenges surrounding ESG, the Oracle survey found that 96% of business leaders admit that human biases and emotions often distract from the ESG end goals. In fact, 93% of business leaders say they would trust a bot rather than a human to make sustainable and social decisions.

“We have people standing up now who are hardwired for ESG,” Pamela Rucker, CIO Advisor, Harvard Professional Development instructor, who helped set up the Oracle study. “The idea that they would trust a computer is no different for them. They already rely on a computer to guide them to work, to give them directions, to tell them where the best prices are.”

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

“If we have a machine that can sort through some of that data, the people can 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,” he said. Rucker: “AI gives you a chance to see more of that data, and you can spend more time coming 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 now start using AI to leverage ESG data. “Don’t wait for additional regulations,” he said.

Getting to grips with data is essential as companies begin their journey to bring 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’ll never figure out how to get there.” where you are. must come,” he said.

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

“It’s still a bit 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 viewed as 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 customers connect their ESG data and data monitoring to the company’s actual operations.

“If we think of business facilities and assets, infrastructure and supply chain as something that is relevant to all sectors, all the data that is acquired needs to be rolled up and integrated with data and process flows within the ESG reporting and management,” he said. “You get the data from the company.”

Deloitte works with Signal AI on ESG efforts

Deloitte recently partnered with Signal AI, which provides AI-powered media intelligence, to help the consultancy’s clients identify and address supplier risks related to ESG issues.

“With the emergence of ESG and as companies navigate a more complex environment than ever before, the world is awash with unstructured data,” said David Benigson, CEO of Signal AI. “Companies may constantly be lagging behind and responding to these issues rather than having the kind of data and insights at their fingertips to lead the way.”

The rise of machine learning and AI, he said, could fundamentally address those challenges. “We can turn data into structured insights that help business leaders and organizations better understand their environment and identify those risks, those threats faster, but also those opportunities more efficiently – giving us a more outside-in perspective on issues like ESG .”

He pointed to recent reactions to ‘greenwashing’, including by Elon Musk (who called ESG a “scam” because Tesla has been removed from the S&P 500 ESG). “There are allegations that organizations are essentially marking their own homework when it comes to sorting their performance and aligning with these kinds of ESG obligations,” he said. “At Signal, we counter 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 doing in the wild. †

Deloitte’s de Spa said the company 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 of all kinds of waste has asked us to help them better understand their own value chain,” he says. “They have a small number of often small suppliers that they depend on and it’s not easy to keep track of what they’re doing.” With Signal AI, he explained, Deloitte can track what is happening to those companies to determine if there are any risks — if they are no longer able to deliver, for example if there is a scandal that causes them to go bankrupt, or if it company is causing sustainability issues.”

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

ESG will need AI and people in the future

As sustainability and other ESG-related regulations begin to spread around the world, AI and smart technology will continue to play a critical role, Deloitte’s de Spa said. “It’s not just about carbon, or even just a responsible value chain with a net zero footprint,” he said. “But it’s also about modern slavery and farmers and other social issues that companies will have to report on in the coming years.”

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

Whatever happens, Rucker said, there will certainly be more for AI-driven tools to measure when it comes to ESG. “One of the reasons I’m getting excited about this is because it’s not just about an environmental footprint anymore, and those massive amounts of data mean you have to put some hard work done by a machine,” she said. “I see an ESG future in which humans need machines and machines need humans. I don’t think they can exist without each other.”