The fashion industry is under pressure these days to foster synchronicity between its sustainability teams and finance teams.
With looming climate disclosure rules on the horizon, the heat is on for the industry’s different departments to operate in greater lockstep—driven by the mounting risks around compliance and the uncertainty of pending regulations as well as investor scrutiny and supply chain exposure.
It’s one of the reasons why Worldly developed Axion: a tool to “help sustainability teams create deeper business cases for the value of their work with their sourcing partners,” chief growth officer Adele Stafford said during Sourcing Journal’s Fall Summit: Countering Chaos.
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“Worldly operates in this ecosystem of brands, retailers and suppliers,” she prefaced. “But also a lot of other partners came together and made a deep commitment around a shared way to measure and manage data.”
Earlier this month, the sustainability supply chain data and intelligence platform for consumer goods—spun out of the Sustainable Apparel Coalition (SAC)—beta launched Axion, a solution for climate and social risk. The tool was developed with Earthena AI, a London-based climate insights provider, in less than a year, per Stafford.
“They’re a group of climate scientists who are also AI experts and bring a deep sort of expertise in climate science,” Stafford said of Earthena AI. “We started the project in May and we launched last week—quite a hustle, recognizing that there’s just a growing demand from our customers for, again, this kind of layered perspective and a sort of shared world view of that data.”
Using “deep primary data and external sources,” Axion offers a holistic risk analysis focused on environmental and social risks. More specifically, Axion offers detailed supplier insights and recommendations in pursuit of integrating sustainability with compliance and sourcing teams, as well as enhancing business cases and cross-functional collaboration.
“Let’s take decarbonization, because that’s top of mind for most of us in this room,” Stafford said before using the hypothetical to quasi-demo how Axion can identify regional hot spots and supplier-specific interventions.
“Then you’re able to layer in some of this risk data, which looks at what are grid decarbonization rates going to do over the next five years,” she continued. “For example, ‘is this an appropriate intervention within this particular supplier?’ So really, again, getting much more acute in terms of the type of actions.”
The tool also has a recommendations engine. As to “leverage the best practices already established in the industry,” Worldly partnered with the Apparel Impact Institute.
“They have a whole series of playbooks and best practices from their work deep in the field, implementing all kinds of strategies around decarbonization,” Stafford said. “We leverage those types of those types of recommendations as well.”
It’s worth noting that Stafford said Axion uses agentic artificial intelligence for its “clear guardrails,” though Worldly has previously referred to the tool as generative AI. They’re pretty different, as the agentic version is focused exclusively on a specific set of content and can only make recommendations based on said content.
“They’re not out there scouring the web and coming up with generative ideas; it’s really heavily protected,” Stafford said. “AI is a tool meant to empower you to do better work, faster, more insightful work. But certainly, in our industry, human verification and validation is not going away anytime soon around data; we see it as a as an enabler.”
In this context, AI’s environmental footprint is considered minimal compared to that of hyperscalers—which is what (or where) Stafford said the focus should be: on the actual ramifications.
“Not every question or query needs to be met with AI,” she said. “We have to be thoughtful about how we use it.”
