Brand Watch: Under the spotlight as never before, companies turn to AI to get their numbers right

May 11 – The notion that modern technologies can help resolve some of the largest sustainability challenges has a long track record, not least among tech-minded brands. Many solutions just require a tweak of existing applications, like Google’s decision to add methane analysers to cars that were already collecting data for its street view service, for example. Others are more targeted. Think, the super-successful Global Forest Watch app, a free deforestation tracking service.

Enthusiasm for so-called “tech-for-good” solutions shows no signs of abating, as shown by the continued flood of brand-led competitions, accelerators and hackathons. Typical is the XPRIZE, set up by Tesla chief executive Elon Musk’s charitable foundation, which recently named 15 finalists for an $80 million payout. The prize money, due to be dispersed in 2025, will go to the venture with the most compelling solution for removing carbon from the atmosphere.

Similar in ethos (if not in budget) is the new innovation connections initiative from Tesco, the UK’s biggest supermarket. Designed to accelerate the growth of eco-minded startups in the food sector, the scheme sees eight early-stage firms compete to have their solution rolled out in the UK supermarket’s supply chain.

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All the finalists have a strong tech profile, from the inventor of a bio-acoustics system for monitoring on-farm pest levels through to a fish-feed producer that manufacturers its product from waste-based microalgae.

The Global Cement and Concrete Association also picked out six promising startups this month for its Innovandi Open Challenge, all of which boast “ground-breaking technologies” geared towards achieving net zero.

An armyworm on a sugar cane crop – startups are using tech to tackle the problem of pests in agriculture. REUTERS/Aly Song

The tech-for-good lens is being increasingly turned to solving sustainability-related management challenges within brands’ own operations. As the scope of social and environmental issues grows, so does the complexity of managing them. A sharp growth in consumer and investor scrutiny also means brands are more under the spotlight than ever to get it right. Claiming to have a relevant sustainability policy is no longer enough; brands need to provide evidence of a marked improvement in practices and performance.

Step forward the bots. According to recent research by U.S. tech giant Oracle, more than 93% of business leaders would trust artificial intelligence more than a human to make a sustainability decision. Underlying the finding is an assumption that bots make fewer mistakes when collecting data (43%), show less bias (42%), and predict future outcomes with greater accuracy (41%).

Digital technologies, especially artificial intelligence and machine learning, remain a “fairly new space for many business practitioners”, says Elena Avesani, global sustainability director at Oracle. But the potential for their application in the field of sustainability management is considerable.

She cites UK electricity and gas utility National Grid, which now uses cloud-based machine-learning models to calculate the volume of renewable electricity in the grid at any one time. The solution, which analyses data at a speed and breadth that would be impossible for humans to achieve, has increased the accuracy of the company’s estimations by 40%, according to Avesani.

“The pressure is mounting to really change the way you run your businesses. You need to be able to make strategic decisions that look at ESG (environment, social, and governance) issues as part of the mix of variables that are part of running your business. (This) is bringing innovation on multiple levels,” she states.

The initial phase of management-focused tech applications centres around delivering efficiency and data-quality gains. Before brands consider providing evidence of improved performance externally, they need to obtain a clear and accurate picture of where they currently stand on multiple different issues, from employee diversity to greenhouse gas emissions. Smart software systems that can collate, organise, store and assess sustainability statistics from multiple data points make this task of internal stocktaking quicker and more reliable.

Britain’s National Grid uses machine-learning models to calculate the volume of renewable electricity in the grid. REUTERS/Andrew Boyers

Once a clear baseline is established, sustainability practitioners have a working platform to set priorities, determine a strategic direction and chart progress. Given the relatively small size of most corporate sustainability departments, much of this analytical legwork is habitually outsourced to the growing crop of sustainability service providers and consultants.

A pioneer in the emerging software-as-a-service (SaaS) field for sustainability is Manifest Climate. Co-founded by environmental lawyer Laura Zizzo, the Toronto-based tech startup uses a machine-learning model to inform companies the extent to which their climate policies and governance systems are aligned with the 11 recommendations of the Taskforce on Climate-related Financial Disclosures (TCFD).

With Canada expected to follow the UK in making TCFD-aligned financial reporting mandatory, clients include the Canadian financial services firm Scotiabank, insurance company Manulife and mining company Teck Resources.

Zizzo says the ultimate purpose of a SaaS model is to free up management time to make more informed strategic decisions. “We organise this information (about climate risk and disclosure) in a way that they can better understand … so that they can then prioritise climate in a way that makes more sense.” This central claim saw Manifest Climate recently win $30 million Canadian dollars ($23.98 million) in a successful funding round.

The next frontier for digital management solutions lies outside a brands’ own operations, a key challenge given the wider context in which macro-sustainability issues such as water management, carbon emissions and human rights play out. One example of how digital technology is being adapted for sustainable management is the application of blockchain in corporate supply chains. Startups such as Circulor (in mining, plastic, and construction), Retraced (in fashion), and Peer Ledger (food) are using the distributed database technology to track products from source to sale, thus answering a growing public demand for product-based chains of custody.

The challenge here is that many suppliers, especially smaller companies, are often privately owned and thus not subject to similar disclosure requirements as listed companies. In response, ESG data providers are building ever more sophisticated software systems to determine credible estimates from dispersed public data sets.

At the heart of all management tech is data. As Jon Sykes, chairman of Carbon Intelligence, a London-based climate information provider, puts it: “Data is at the root of impact. Data is at the root of change. Data is at the root of transition.” That’s not because numbers in and of themselves carry weight, but rather because if you get them right, they can provide a stable launchpad for impactful action.

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Opinions expressed are those of the author. They do not reflect the views of Reuters News, which, under the Trust Principles, is committed to integrity, independence, and freedom from bias. Sustainable Business Review, a part of Reuters Professional, is owned by Thomson Reuters and operates independently of Reuters News.