Supply chains have been rising to technological challenges for centuries, and will do so again with regards to AI-driven operations, says a leading EY manufacturing leader.
Alison Clark is Advanced Manufacturing & Mobility Leader for EY in the UK.
Speaking to Supply Chain Digital, Clark says that, although digitalisation is a seriously testing business objective “supply chains have existed for centuries and have always leveraged new technologies to adapt and improve”.
She says that the most important thing for organisations on transformation journeys is that they ensure AI initiatives are “strategically aligned, operationally purposeful and commercially viable, all while empowering IT to serve business needs”.
Clark adds that supply chain and technology chiefs must also never lose sight of the fact AI requires two “essential ingredients”: data and channels for data to travel.
The problem for supply chains, she points out, is that most lack the digital infrastructure needed to capture data, and that there is also “misalignment in communication and incentives” for the data that does exist to be shared".
Clark says organisations can avoid “AI deployments pilot purgatory” by identifying real business problems to solve. “AI is enabled by technology but must be led by business,” she observes.
“By identifying and prioritising the right business problems, companies can start deploying point solutions to solve them,” Clark explains. “These separate solutions, if well-orchestrated, will grow and help drive data standardisation and interoperability for the company to reach the next stage of AI maturity.”
The main challenges to AI deployment in supply chain, she adds, is that they are hard to map, monitor and manage.
“These inefficiencies lead both to low coordination and also misalignment in overall data quality and compatibility,” she says.
EY: AI in supply chain 'needs actionable data'
Clark also warns that, without actionable data, “solutions are not effective, and ineffective solutions don’t generate momentum”.
She adds: “Leading companies understand that despite the opaque return on IT investment, this is necessary to upgrade data architecture and data skill-sets.
Empowered IT teams, she says, “enable faster experimentation and more successful AI deployments for everyone”.
“This seems simple enough,” she says, “but it’s not, as it involves breaking organisational silos, overhauling legacy IT architectures, and helping people navigate this change successfully.”
Clark adds: “Timing is another key consideration. AI upgrades don’t happen overnight. Decision makers are uncertain not only about the technology impact on their market standing and value proposition, but also how to put a reskilling plan and how to start developing the technical capabilities needed – either internally or through partnerships."
Clark's views on AI adoption in supply chain are borne out by a a recent Gartner survey that shows half of supply chain leaders plan to embrace Gen AI in the coming 12 months, and that a further 14% are already implementing such solutions.
The survey also reveals chief supply chain officers are dedicating 5.8% of their budget to Gen AI, and that CSCOs see it as “supportive of their broader digital transformation objectives”, commented Noha Tohamy -- Distinguished Analyst with Gartner’s Supply Chain Practice -- in the report.