Why AI is essential to meet growing ESG requirements


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

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

ESG investing, in particular, has played a significant role in this boom: Bloomberg Intelligence has found that ESG assets are on track to exceed $50 trillion by 2025, representing more than a third of the 140 Projected $500 billion in global assets under management. In the meantime, ESG reporting has become a top priority that goes beyond ticking 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 global Oracle ESG study, 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 for reporting on ESG metrics.

“Much of the data that needs to be collected doesn’t yet exist or needs 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 your business, because they are your suppliers, but also your suppliers’ suppliers.”

ESG data challenges are driving the use of AI

This is where AI is increasingly part of the ESG equation. AI can help manage data, glean insights from data, operationalize data, and report on it, said Christina Shim, vice president of strategy and sustainability, applications software. AI at IBM.

“We need to make sure that we’re collecting massive amounts of data when it’s in completely different silos, that we’re leveraging that data to improve operations within the business, that we’re communicating that data to a variety of stakeholders and in a very confusing landscape of ESG frameworks,” she said.

According to Deloitte, although a BlackRock survey found that 92% of S&P companies were publishing ESG metrics at the end of 2020, 53% of global respondents cited “poor quality or availability of ESG data and analysis” and 33% cited “poor quality”. of sustainable investing 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 just nice to have,” Shim said. “It’s really becoming kind of a base that organizations need to focus on and there are higher and higher standards that need to be built into the operations of all businesses,” she explained.

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

The human-AI ESG connection

In addition to ESG-related operational challenges, Oracle’s research found that 96% of business leaders admit that human biases and emotions 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 coming in now who are hardwired for ESG,” Pamela Rucker, CIO advisor, instructor for Harvard Professional Development, who helped set up the Oracle study. “The idea that they would trust a computer is no 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 efforts. ESG, including change management (48%), educating others (46%). , and making strategic decisions (42%).

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

How companies can get started with AI and ESG

Seth Dobrin, director of AI at IBM, told VentureBeat that companies should start using AI now to mine ESG data. “Don’t wait for more regulations to come in,” he said.

Mastering data is critical as companies begin their journey to integrating AI technologies into the mix. “You need a baseline to understand where you are, because you can achieve all the goals and imperatives, you can commit to whatever you want, but until you know where you are, you can’t. you’ll never know how to get to where you need to get to,” he said.

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

“It’s still a bit of a compliance exercise, but that’s changing,” he said. “Companies know they need to get involved and think proactively in order to be seen as a thought leader in the field and not just a laggard doing the bare minimum.”

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

“If we consider facilities and business assets, infrastructure and supply chain as something relevant across industries, all data from sources needs to be aggregated and integrated with data and process flows in the framework of ESG reporting and management,” he said. “You get the company data.”

Deloitte works with Signal AI on ESG efforts

Deloitte recently partnered with Signal AI, which offers AI-powered media intelligence, to help the advisory firm’s clients identify and manage supplier risk related to ESG issues.

“With the rise of ESG and as businesses navigate a more complex environment than ever before, the world is awash with unstructured data,” said David Benigson, CEO of Signal AI. “Companies can find themselves constantly on the back foot, responding to these issues reactively rather than having the kind of data and information at their fingertips to be ahead of the game.”

The emergence of machine learning and AI, he said, can fundamentally address these challenges. “We can transform data into structured information that helps business leaders and organizations better understand their environment and anticipate these risks, threats more quickly, but also spot these opportunities more effectively – providing a more external 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 the S&P 500 ESG index). “There are accusations that organizations are essentially marking their own homework when it comes to sorting out their performance and aligning with these types of ESG commitments,” he said. “At Signal, we provide the opposite of that – we don’t necessarily analyze what the company says it’s going to do, but what the world thinks of what this company is doing and what it’s doing. actually in nature.”

Deloitte’s of Spa said the company uses Signal AI for what it calls a “responsible value chain” — essentially, supplier risk management.

“For example, a sustainable organization that cleans oceans and rivers of all kinds of waste asked us to help them better understand their own value chain,” he said. “They depend on a small number of often small vendors and you can’t easily track what they’re doing.” With Signal AI, he explained, Deloitte can track what is happening with these 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 causes sustainability issues.

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

ESG will need AI and humans in the future

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

Going forward, a key driver will be how to connect and integrate data together using AI, IBM’s Dobrin said. “Many offer a carbon coin or sell AI just for energy efficiency or supply chain transparency,” he said. “But you have to connect everything together in a one-stop shop, it will be a total change in this space.”

Either way, Rucker said, there will definitely be more to measure for AI-powered tools when it comes to ESG. “One of the reasons I’m excited about this is because it’s not just a carbon footprint anymore, and these massive amounts of data mean you’re going to have to have some 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 they can exist without each other.

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