Imagine a supply chain management system that can self-learn, accurately predict market demand, optimize inventory, provide early warnings for unexpected events, and automatically adjust logistics strategies. This isn't science fiction—it's the reality emerging as artificial intelligence (AI) becomes deeply integrated into Enterprise Resource Planning (ERP) systems. This article explores how AI, particularly generative AI, is driving breakthroughs in ERP systems for supply chain management and examines the opportunities and challenges businesses face in this transformation.
AI and ERP: The Core Drivers Reshaping Supply Chain Management
As a rising star in computer science, artificial intelligence (AI) is penetrating various industries at an unprecedented pace. By creating "intelligent agents" capable of autonomous learning, reasoning, and action, AI has achieved remarkable results in fields ranging from medical diagnosis to round-the-clock customer support and manufacturing quality control. Now, AI is helping ERP vendors expand their territory in supply chain software. With AI and machine learning (ML) technologies, ERP systems can analyze vast amounts of data, improve decision-making quality, and personalize user experiences.
The emergence of generative AI signals a new wave of applications for ERP systems in supply chain software. McKinsey defines "generative AI" as algorithms capable of creating entirely new content, including audio, code, images, text, simulations, and videos. In software development, generative AI can analyze large volumes of user feedback, customer reviews, and other data sources to identify patterns in user needs and preferences, thereby optimizing product design and user experience.
AI, machine learning, and generative AI are revolutionizing supply chain and logistics, which in turn profoundly influences software vendors' solution development strategies and drives continuous expansion of application functionalities. "AI emerged over the last two to three years, but it really took off in about the last three months," said Siddharth Ram, Vice President of Consumer Products, Retail, and Services at Capgemini.
Despite AI technology evolving at a "weekly" pace, supply chain and logistics managers' interest in generative AI continues to grow. "There's a lot of discussion around generative AI and the role it could play in supply chain management," Ram added. "Almost every week, there's a new product coming out or a new use case emerging in the generative AI space."
Facing this trend, ERP vendors are actively embracing change by incorporating more generative AI and related technologies into their solutions. While many efforts remain at the proof-of-concept and prototype stages, Ram believes these tested products will soon reach broader markets. "Many companies want to experiment with generative AI in supply chain, but there's still a lack of clarity about how generative AI will solve their supply chain problems or where exactly it can be applied," Ram noted. "However, companies like ours still have tremendous motivation to demonstrate the value of this technology."
ERP's Shift in Focus: From Back Office to Frontline
For years, ERP systems were considered "back office" systems primarily managing core processes like accounting, human resources, finance, and sales. However, over the past decade, ERP systems have gradually expanded their functional scope. Through independent innovation and acquisitions—many bringing their own intellectual property—ERP systems continue to adapt and evolve to meet user needs.
Logistics and supply chain represent areas of particular focus for ERP vendors. While not a new trend, this focus has intensified due to the global pandemic and the supply chain challenges it created for businesses and their customers. "ERP systems are shifting focus from finance and accounting to supply chain management," said Eric Kimberling, CEO and Founder of Third Stage Consulting Group.
The driving force behind this shift is simple: most businesses across industries prioritize supply chain, so their core business systems must align with this focus. "Overall, ERP vendors are investing more in research and development for supply chain management capabilities than ever before," Kimberling noted.
Like Ram, Kimberling sees AI and machine learning playing increasingly important roles in ERP and supply chain management. For instance, software vendors are working to determine how AI can enhance supply chain planning and provide better outputs from transactional data. "ERP has traditionally been transaction-based, but now AI is enabling ERP vendors to go deeper into supply chain management and offer more functionality than ever," Kimberling said.
ERP vs. Best-of-Breed: An Eternal Debate
As more businesses focus on supply chain management rather than enterprise-wide technology deployment, one longstanding question remains: Should companies use supply chain functionality from their ERP vendor or purchase separate applications from best-of-breed developers?
A third option exists between these extremes: purchasing a supply chain software suite from a vendor that includes Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and other related applications.
"Some companies still say, 'We're going to implement an enterprise ERP that includes SCM,'" Kimberling explained. "However, we're increasingly seeing companies prioritize SCM higher and implement these systems faster, while other traditional ERP functionalities may lag behind." This prioritization of SCM is another reason ERP vendors themselves are delving deeper into supply chain software.
In most cases, choosing between an ERP's supply chain software suite and best-of-breed options depends on a company's priorities. For instance, if a company focuses primarily on improving its supply chain, related software typically becomes the top transformation priority. Other decision drivers include whether the company urgently needs robust, fully functional TMS or WMS solutions or if the ERP-provided applications suffice.
Regarding innovation, Ram believes that as AI, generative AI, and machine learning become more prevalent in supply chain software, best-of-breed vendors may act faster. "I think we'll see generative AI solutions integrated into both ERP and SCM, but compared to best-of-breed companies, ERP may be less capable of supporting AI solution integration into their software," Ram said. "Best-of-breed vendors are typically smaller and more agile in implementing changes."
Best-of-breed supply chain software manufacturers also have deeper expertise in their own applications, whereas ERP vendors may have acquired other companies' assets to build their portfolios. These acquired assets then become part of larger enterprise-level applications. "Building AI into the SCM side is slightly easier than building it into ERP," Ram noted.
Finding the Right Balance
When evaluating ERP vendors' recent progress in supply chain management, Gartner Research Vice President Dwight Klappich stated that in most cases, their applications are "good enough" for a significant portion of the market. ERP-provided SCM applications are especially suitable for less complex, sophisticated logistics and supply chain environments.
In some cases, the line between enterprise software vendors and best-of-breed has completely blurred. "Oracle is best-of-breed [ERP] in transportation and getting close in warehousing," Klappich said. "Microsoft isn't doing much in transportation, but SAP is doing a lot in both planning and transportation. And Infor excels in warehousing. For many shippers, these ERP vendors are good enough to make the shortlist."
Beyond embedding more AI and generative AI into their solutions, ERP vendors are placing greater emphasis on end-user experience—thanks to labor shortages driving innovation in this area.
"[Logistics] industry workers are the iPhone generation, so if your user interface looks like something from 30 years ago, you're at a disadvantage," Klappich said. He cited Manhattan, Infor, and Oracle—with its Redwood next-generation user experience (UX) designed for ease of use and customization—as examples of vendors prioritizing user experience.
For companies investing in new ERP or supply chain software this year, Klappich emphasized the importance of striking the right balance between overbuying and underbuying, then doing the homework to find the right fit. "ERP vendors will never—and don't need to—be completely best-of-breed," he said. "If you're committed to an ERP system and your supply chain management requirements are 'middle of the road,' the best approach is to include your ERP vendor on the shortlist while evaluating other options."
Conclusion: The Future of Intelligent Supply Chains
As AI technology continues to develop and mature, ERP systems will play an increasingly prominent role in supply chain management. Businesses should actively embrace change, leveraging advanced technologies like AI, machine learning, and generative AI to build smarter, more efficient, and agile supply chain systems. Simultaneously, companies must make informed choices between ERP supply chain modules and best-of-breed solutions based on their specific circumstances to achieve optimal return on investment.
Looking ahead, we can confidently expect AI to continue empowering ERP systems, driving supply chain management toward greater intelligence and automation, ultimately reshaping the global supply chain landscape.