Utilizing AI in the supply chain is rapidly evolving from a competitive advantage to a necessity.
An effective AI plan can enhance decision making, agility and visibility across supply networks.
Supply chain officers may need additional support to determine the right AI integration strategy.
The middle market is rapidly discovering the transformative value of artificial intelligence and AI technologies to boost efficiency and prioritize resilience in all key business functions. Amid unprecedented challenges and demand shifts, supply chain officers are responsible for developing and implementing an effective AI strategy to optimize the supply chain, potentially reshaping every link to deliver meaningful value.
Demonstrating the reach of AI in the middle market, the RSM Middle Market AI Survey 2024: U.S. and Canada found that 78% of executives surveyed are either formally or informally using AI. But only 20% of those respondents feel they have integrated AI meaningfully, and 67% using generative AI report they need outside help to get the most out of that tool. Additionally, while the survey found that data analytics (54%), IT (54%) and customer service (46%) were the leading functions where companies leverage generative AI, supply chain management lagged significantly behind, with only 15% of respondents indicating use of generative AI to support the function.
With the growth and potential of AI solutions, supply chain officers have a significant opportunity to transform key processes and shape the future of the business.
RSM US principals Steve Biskie, George Casey and Jake Winquist recently discussed actionable insights and best practices for leveraging AI in the supply chain to boost efficiency, reduce costs and overcome challenges during RSM’s recent webinar “AI in the supply chain: Transforming efficiency, resilience and visibility.”
Below, we take a look at some critical details for supply chain leaders to consider when developing an AI strategy, as well as potential use cases and examples of successful AI implementation.
Integrating AI in supply chain management is rapidly evolving from a competitive advantage to a necessity. Amid uncertainties around trade and tariffs and the rising costs of goods and labor, an effective AI strategy can enhance decision making, agility and visibility across global supply networks.
Multiple factors determine the successful integration of AI tools and applications within the supply chain, but leaders must establish a clear vision for AI success up front. “Do you know what your employees and colleagues are using from an AI perspective?” Winquist asked. “What is really impactful and what do we want to provide across the board? We need to be talking about this to get to a formalized vision and plan for AI.”
Do you know what your employees and colleagues are using from an AI perspective? What is really impactful, and what do we want to provide across the board? We need to be talking about this to get to a formalized vision and plan for AI.
To drive impact with AI, supply chain officers should allocate resources and investments to key areas, including:
An effective AI model starts with prepping the foundation—addressing data challenges and confirming data integrity and cleanliness. Ultimately, the output and efficacy of an AI implementation within the supply chain depend primarily on the data quality. Data governance and due diligence are crucial for realizing the true potential of AI investments.
“The fundamental data structure is critical to set yourself up for success,” said Winquist. “Don’t assume that AI can just come in and fix all of the problematic data that you may be used to. Instead, you need to focus on data cleanliness and the due diligence process up front.”
In addition, supply chain officers need to define the “why”—the objective of the strategy—and link it to business cases and the company’s overall operational goals.
“What I am excited about is that we think of innovation as the application of invention,” said Casey. “In the last couple of years, we’ve seen a lot of invention and new models and capabilities being released. A lot of companies have been in that proof-of-concept, proof-of-value phase and kicking the tires by starting with a single use case,” he added. “Over the next year to 18 months, we are going to see some of the results of those projects.”
In the last couple of years, we’ve seen a lot of invention and new models and capabilities being released. A lot of companies have been in that proof-of-concept, proof-of-value phase and kicking the tires by starting with a single use case. Over the next year to 18 months, we are going to see some of the results of those projects.
When designing and implementing an AI strategy, supply chain officers should keep the following key issues and processes in mind:
AI misinformation: Without quality data, AI can generate misinformation, leading to missed opportunities. Critical evaluation up front is mandatory for AI deployment within the supply chain.
Risk management: Companies must understand the risks involved in AI deployment in order to protect intellectual property and sensitive data and monitor ethical concerns, bias compliance and data integrity.
Governance models: An effective AI governance approach can better address risks arising from misinterpretation of results, exposure of sensitive data, vulnerability to data breaches and limited availability of data to train AI models.
AI readiness evaluation: The first step in developing a comprehensive AI strategy is to conduct an assessment that can define intent, evaluate potential use cases and establish human supervision.
As with any transformative technology implementation, companies must weigh the AI-related opportunities and positive impacts against the risks and potential negative impacts. While the opportunities for increased supply chain insight, efficiency and productivity are vast, potential risks and related impacts include:
Now that we’ve identified the risks, our next thought is, what are we going to do about them and what are the strategies? So when we talk about working with AI and helping protect organizations, it’s all about having a good governance model.
While AI tools and solutions can be challenging to implement and maintain, they have tremendous potential to strengthen the supply chain, driving increased profit, efficiency and workforce excellence. AI can contribute directly to supply chain success by providing capabilities such as:
Trend and predictive analysis: Anticipate demand, optimize inventory and mitigate risks by leveraging AI to forecast market trends, supply chain disruptions and customer behavior, driving proactive decision making. Examples include:
Workflow automation: Streamline operations and reduce manual errors by automating repetitive, rules-based tasks ranging from procurement to order processing, allowing teams to focus on strategic activities while improving efficiency and speed. Examples include:
Generative and autonomous technologies: Solve complex problems, generate new solutions and make independent decisions with minimal human intervention, transforming supply chain and operational management and driving innovation and efficiency. Examples include:
AI can revolutionize the supply chain and mitigate risk for any business, regardless of its size and scale. However, the challenges and complexities in developing an effective enterprise AI strategy may seem overwhelming, and supply chain officers may need additional support in determining the appropriate AI integration strategy.
But the potential of AI cannot be ignored—more than just a trend, it has become a fundamental element of a successful supply chain strategy.
“Your colleagues and your employees are already using AI,” said Winquist. “So how do we harness that shift and momentum into a cohesive AI strategy and plan? How do we bring that together, understand what use cases are, what the value proposition is, and establish a cohesive supply chain strategy that aligns with our overall enterprise strategy? Not only will AI last, and not only is it sticky, but it is clearly accelerating."
Your colleagues and your employees are already using AI. So how do we harness that shift and momentum into a cohesive AI strategy and plan? How do we bring that together, understand what use cases are, what the value proposition is, and establish a cohesive supply chain strategy that aligns with our overall enterprise strategy? Not only will AI last, and not only is it sticky, but it is clearly accelerating.
Ready to get started? RSM’s experienced AI advisory team understands the enterprise AI journey and the foundational elements necessary to generate increased value and reduce risk. Contact our team to learn more about how AI can transform your key business operations.
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