A Single AI Cannot Build Supply Chain Capabilities
Despite the promising potential of artificial intelligence, some supply chain leaders are describing it as a solution in search of a problem.Like most executives in the electronics supply chain, professional procurement personnel are excited about artificial intelligence (AI). Among the CSCOs (Chief Supply Chain Officers) surveyed by Gartner, half plan to implement generative AI within the next 12 months, while another 14% are already in the implementation phase.Although AI shows great promise, some supply chain leaders indicate that there are still unresolved issues regarding its application in supply chain solutions. However, Noha Tohamy, distinguished vice president and analyst of Gartner’s supply chain practice, holds a different view.'Generative AI can help humans gain insights more easily, which will significantly improve productivity. Companies will be able to hire the same or fewer employees to do more,' she told EPSNews.She also added that generative AI makes interfaces more intuitive by utilizing natural language, and it can extract greater benefits from existing technologies, enhancing the usage of these technologies and offering better returns on previous technology investments.CSCOs are hopeful that generative AI can improve productivity, increase business agility, and reduce costs. However, Tohamy noted that companies are still in the early adoption phase of generative AI, and some expected benefits may be exaggerated or overestimated. Additionally, the risks may not yet be fully understood, and risk mitigation may be incomplete. 'This is especially true in supply chain and procurement fields, where many use cases require sharing and exchanging data with external partners.'Supply Chain Use CasesGartner believes that in procurement, generative AI will have the greatest impact on procurement and contract lifecycle management, as well as supplier information discovery and management. The electronics supply chain is already using AI to quickly filter and analyze large amounts of data, recommend product alternatives, and identify substitute suppliers.For example, Waldom Electronics, a major global wholesaler of electronic and electrical components, is using machine learning models to proactively predict inventory sales, and is exploring both proactive and reactive automation in procurement processes.Catalog distributor Digi-Key is using AI/ML (artificial intelligence/machine learning) to classify and code parts based on descriptions and parameter data, categorize customer reviews and company data, recommend parts based on availability, and perform data validation, auto-correction, and notifications based on invoices, contracts, and other sources.AI is also being applied to research and development (R&D) in product design. Industry experts have noted that AI-generated designs are often highly accurate with only minimal adjustments. A use case cited by the Harvard Business Review shows that rapid supplier search and auditing can enhance supply chain flexibility.One of the most impactful use cases, according to Tohamy, is 'allowing supply chain employees to interact with technology using natural language to ask questions about key performance indicators (KPIs) and supply chain performance, and to receive contextual answers.' Other applications include code augmentation, providing deeper insights into supply chain KPIs, and employee-assisting chatbots.'For example, planners no longer need to navigate multiple systems, reports, dashboards, Excel spreadsheets, and charts,' Tohamy explained. 'Users can ask generative AI something like, "What is my customer’s expected on-time delivery rate?" and better understand the factors driving that KPI, as well as take actions that could solve problems or work better with internal teams to make decisions.'Gartner found that, on average, CSCOs allocate 5.8% of their department budgets to generative AI. They believe generative AI can help companies achieve broader digital transformation goals. However, supply chain departments lag behind marketing and sales in adopting generative AI. Of the CSCOs surveyed, 65% plan to hire dedicated personnel and experts in 2024 to help deploy the technology.Tohamy said the projected budget figures suggest supply chain leaders are very focused on making progress with generative AI solutions this year. They also recognize the need for more resources to successfully move beyond small-scale pilots. CSCOs are likely to consider the impact on employees, as they will need to shift toward higher-value activities, while lower-level tasks become increasingly automated.Partial Problem SolutionsThe Harvard Business Review offers a view on AI in the supply chain: AI tools cannot solve all problems. According to the publication, in stable supplier markets where alternative suppliers are well known, the uncertainty buyers face is minimal, and AI’s value diminishes. Additionally, for partners who already share deep information and have solid relationships, the extra benefits AI tools can offer are also limited.
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