Study: AI adoption surges in high-growth supply chain sectors

A recent study by Epicor and Nucleus Research reveals that nearly half of companies in the manufacturing, logistics, and retail sectors consider escalating costs as the primary challenge facing their supply chains.

The 2024 Agility Index research also shows that over half of these companies are utilising artificial intelligence (AI), automation, or machine learning to manage at least one aspect of their supply chain operations.

The study, which surveyed more than 1,700 supply chain management leaders globally, found that businesses described as high-growth—achieving a revenue growth of 20% or more over the past three years—are more likely to have integrated generative AI into their supply chain processes. Specifically, 63% of high-growth businesses reported using generative AI to address operational and cost-related challenges.

"When workers are empowered to spend more time innovating—what humans do best—that's where the real value creation happens. That is agility," stated Vaibhav Vohra, Chief Product and Technology Officer at Epicor. "Our 2024 Agility Index underscores the growing adoption of AI and other automation technologies as an essential factor in enabling supply chain businesses to better thrive and compete."

The survey indicated that companies are incorporating generative AI into various digital supply chain functions, including product descriptions, customer service chatbots, and natural language querying. The most common application is in customer service chatbots, cited by 72% of organisations. This is attributed to the technology's ability to streamline customer interactions across different sectors.

Additionally, 67% of businesses reported employing generative AI for creating product descriptions. This use leverages the technology's capacity to analyse customer sentiment and predict market demand, thereby informing product design and feature development.

The adoption of machine learning within supply chains is also notable, particularly in inventory optimisation and demand forecasting. According to the study, 45% of organisations use machine learning for inventory optimisation, while 40% use it for demand forecasting. These technologies play a crucial role in maintaining optimal inventory levels and accurately predicting future demand.

The survey also addressed the anticipated impact of automation technologies. Respondents highlighted increased efficiency and productivity (32%), cost savings (26%), and improved supply chain automation (23%) as the main benefits. This reflects a strong belief in the potential of AI and automation to drive substantial improvements in supply chain management.

The study was conducted between January and March 2024 and surveyed supply chain and operations leaders from the US, UK, Ireland, and the Asia-Pacific region. The sample was evenly split between enterprises with annual revenues between USD $250 million and USD $1 billion, and small to medium-sized businesses with annual revenues under USD $250 million.