Generative AI can help supply chain planners get immediate, actionable insights, moving insights closer to the execution team members.

Nathan Eddy, Freelance Writer

March 4, 2024

4 Min Read
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Chroma Craft Media Group via Alamy Stock

Generative AI (GenAI) has the potential to significantly improve supply chain efficiency and risk-resiliency for businesses across multiple industries.

Using natural language, supply chain leaders can request information, navigate systems, or make changes without the need to be in the specific application. This helps eliminate manual data entry and repetitive tasks, saving time and reducing errors. 

In the next 12 months, half of supply chain leaders said they intend to implement GenAI, with an additional 14% already in the implementation stage, according to a recent Gartner survey. The data further revealed chief supply chain officers (CSCOs) allocate an average of 5.8% of their function's budget to GenAI.

Noha Tohamy, distinguished vice president analyst in Gartner’s supply chain practice, says gains in productivity come from the ability to get insights much faster than going to multiple Excel spreadsheets, source systems or even traditional BI solutions. “One executive commented that now, by the time the planner gets an answer to their question, the question is no longer relevant,” she explains in an email interview. “Using GenAI to understand key performance indicators in a timely manner can help the supply chain become more agile, responding faster to changing conditions.”

Related:Improving Supply Chain Security, Resiliency

In the study, supply chain respondents said that the top challenges are data accuracy, reliability and transparency, compatibility with legacy systems, and resistance from employees. “While compatibility with legacy systems might not be a major hurdle in a pilot -- where the emphasis is on experimenting with the technology to understand potential benefits -- for broader deployments to succeed, organizations will need to figure out how to integrate GenAI solutions with preexisting supply chain technologies,” Tohamy says.

Similarly, creating data sets to pilot a use case like key performance indicator (KPI) discovery is feasible, but deploying GenAI as a primary tool for KPI discovery will require complete and accurate data that reflects current supply chain conditions.

“Once advanced analytics allocated transportation assets, a transportation analyst can use GenAI to ask questions about those allocations to get insights about shipment status and provide customers with order updates,” Tohamy explains.

New Insights, Stronger Business Outcomes

Darcy MacClaren, global chief revenue officer for digital supply chain at SAP, says by leveraging GenAI, supply chain leaders can realize the true value of data to glean new insights, identify efficiencies, and ultimately, achieve stronger business outcomes. “Despite the buzz around ChatGPT, there is more to GenAI than open language models,” she explains in an email interview. “Supply chain leaders are using machine learning algorithms to predict demand and optimize inventory levels, reduce waste, and improve customer satisfaction.”

Related:IT Must Clean Up Its Own Supply Chain

By connecting AI with rich data from across the enterprise, organizations can create synergies that enhance productivity, improve business agility, and reduce costs. “With GenAI, companies can easily understand the conditions captured in data and use it to analyze complex data sets, help predict demand, and optimize routes for delivery,” MacClaren says.

Troy Prothero, senior vice president of product management, supply chain solutions for SymphonyAI, points out GenAI will become layered onto more complex underlying data simulations for supply chains, including scenario planning or contingency planning. “When you have aggregated data for visibility across the supply chain, underlying analytics coupled with GenAI supports very robust, intuitive, what-if scenario planning,” he explains in an email interview.

Prothero says in supply chain planning GenAI can help new or less experienced employees rapidly perform at a level expected from a much more experienced employee. “Supply chain planners are excited about how generative AI can increase in productivity and efficiency, along with significantly increasing accuracy -- which is particularly important for supply chain planners.”

Related:The Future of Resilient Supply Chains Is Circular

Resolving Issues in Plain Language

MacClaren says in 2024, supply chain leaders can expect the proliferation of GenAI-driven digital assistants, transforming the way businesses run by allowing users to ask questions in plain language and receive quick, contextualized responses.

For example, if a company has several trucks waiting to be unloaded, a worker can ask a generative AI assistant to check the cargo list, figure out what each truck contains, and suggest which one to unload first.

“These insights will lead to many benefits across the supply chain, such as faster deliveries and reduced costs, setting new standards for global market responsiveness and competitiveness,” she says.

However, for supply chain leaders looking to integrate GenAI with existing solutions, it is vital to ensure AI is relevant, reliable, and responsible, so business outcomes can be achieved in a secure, compliant way. 

MacClaren says to address adoption challenges and build foundational AI capabilities, CSCOs must educate their organizations on the power and benefits of AI. “Start by looking at practical examples for managing processes within the supply chain, including workforce management, streamlining and simplification, and reaping the full value of supply chain solutions,” she explains.

From her perspective, there are a few considerations for supply chain leaders looking to successfully scale AI across their business. These include ensuring legal framework and data access is in place to use customer data for product development and operational optimization. “Use a central data architecture that enables data integration, quality, and governance across the supply chain and establish ethics policies and advisory panels to promote trustworthy AI,” she says.

It will also be important to train and empower employees to leverage AI capabilities and drive innovation across the business. “Integrating GenAI into every level of the supply chain network will unleash a hyper-predictive and efficient logistics organization,” MacClaren says.

Read more about:

Supply Chain

About the Author(s)

Nathan Eddy

Freelance Writer

Nathan Eddy is a freelance writer for InformationWeek. He has written for Popular Mechanics, Sales & Marketing Management Magazine, FierceMarkets, and CRN, among others. In 2012 he made his first documentary film, The Absent Column. He currently lives in Berlin.

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