Since its release earlier this year, Chat
GPT-4
and other artificial intelligence (AI) tools from Google,
Microsoft and other tech companies have
led to a plethora of speculation about how entire industries could be
transformed.
But can AI also help companies manage their supply chains — and, more
specifically, eliminate the risk of forced labor and other human rights
violations among their suppliers? Justin
Dillon, founder of supply-chain
management software FRDM, certainly thinks so — he’s
seen massive potential since the company integrated AI earlier this year.
“AI is allowing FRDM to fill data gaps in supply chains and mining large data
sets for risk intelligence,” Dillon told Sustainable Brands®. “AI is
helping us quickly identify key attributes of these sub-suppliers needed to
provide accurate risk analysis.”
FRDM is, in fact, one of several supply-chain tracing tools — along with Altana
AI, (en)visible, Provenance and
Sourcemap
— that are incorporating AI to better provide brands with insights into their
supply chains. All were formed with the goal of using technology to increase
visibility into global supply chains, and empower brands to reduce or eliminate
social and environmental risks.
“One of the key advantages of AI is its ability to provide unparalleled
visibility into complex supply chains,” Jay
Risser, an AI educator and
expert, explained in a blog
post.
“AI-driven supply chain visibility enables businesses to make informed decisions
and build partnerships with suppliers committed to ethical practices.”
It’s a big challenge. Since globalization took off, supply chains have gotten
incredibly complex. A simple product such as a lamp or even a jacket can now
contain dozens of different components, sourced from different countries. While
this has made a plethora of consumer goods available at accessible costs to
millions around the world, it’s also led to many unintended problems; and labor
rights
and environmental
harms
have been discovered in the supply chains of many of the world’s biggest brands.
As companies began to face reputational risk due to civil society groups and
journalists uncovering human rights or labor
abuses
from suppliers that many did not even realize were supplying them, there’s been
a push to better manage and ensure supply-chain transparency, with
technology
playing a key role.
One of the most unique technology providers in this space is Altana
AI — which, unlike FRDM or
Provenance,
was founded specifically to take advantage of the unique capabilities of AI.
“We're the world's only dynamic, intelligent map of the global supply chain,”
Altana AI CEO Evan Smith told SB.
“We're using artificial intelligence both to build that map and then we use AI
to situate our customers inside of that map and show them what their supply
chain connections are beyond their direct relationships.”
This approach would, according to Smith, not have been possible even with the
most advanced machine learning technology from a few years ago. And it’s already
paid off, with one client using it to meet the strict requirements of the
Uyghur Forced Labor Prevention
Act
(UFLPA), which forbids companies from importing any
products
from the Xinjiang region of China.
“We connected our platform to the data of one of the biggest brands in the world
and found that roughly a third of their supply chain had exposure to Xinjiang,”
Smith said. “What they've been doing since then is work with their most
important garment manufacturers through our platform to engage the upstream
supplier network.” The impact? That brand has seen fewer shipments blocked by
US Customs and Border Protection due to forced labor links.
Today, the UFLPA is just one of many new reporting requirements for companies.
Others include modern slavery acts in the
UK
and
California,
human-rights due-diligence
regulations
in Germany, and many voluntary ESG reporting requirements.
“Transparency in supply chains is quickly becoming a factor in how companies do
business with each other, and how investors fund,” Dillon says.
Of course, AI is merely a tool; and brands must be aware of its limitations and
that it still requires a lot of work to provide it with the data it needs to
make accurate assessments of forced-labor risk — AI can’t replace bad management
practices.
“We meet companies who expect our tech to find receipts or invoices from
sub-suppliers deep in a supply chain,” Dillon says. “While AI may map supplier
relationships, it will not be able to pull a paper receipt out of the desk
drawer of a sub-supplier.”
Moreover, AI can’t make up for the fact that, in many places, data about worker
conditions is
lacking.
Adding to the challenge is deliberate attempts to hide forced
labor
— of particular concern in China, where traditional tools such as social audits
are no longer
possible;
and the government is increasingly hiding even basic
data.
“There are definitely more and more attempts to obfuscate and avoid
enforcement,” Smith asserts. “AI is not a silver bullet; it's not an all-seeing
eye.”
One area that concerns Smith is forced labor transfers of Uyghurs — in which
Uyghur workers are sent to factories around China, including outside of
Xinjiang. This was exposed in a 2020
report from the Australian
Strategic Policy Institute; but real-time data is lacking.
“There's nothing in our technology that can identify the actual movement of
Uyghur people,” he explained. “Unfortunately, I think this is going to be a
cat-and-mouse game for a long time.”
Still, Smith, Dillon and others see a real role for AI in pushing us towards a
more sustainable and ethical business future. While AI won’t make supply chains
transparent or sustainable on its own, it can be a valuable tool for dedicated
brands and enable real, meaningful action at scale.
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Media, Campaign and Research Consultant
Nithin is a freelance writer who focuses on global economic, and environmental issues with an aim at building channels of communication and collaboration around common challenges.
Published Sep 14, 2023 8am EDT / 5am PDT / 1pm BST / 2pm CEST