By Max Chan, Chief Information Officer, Avnet
Deployment of artificial intelligence (AI) in procurement and the supply chain is forecasted to grow hugely over the next five years. The compound annual growth rates will be 36.6% in procurement between 2024 and 2030, and 28.2% in the supply chain in the same time period. The cost of the technology enabling AI data centres undoubtedly contributes to these figures, but will OEMs see any benefits?
AI and machine learning (ML) have forced a critical juncture in component procurement. Over the past two decades, data creation has surged exponentially, with the Internet of Things (IoT) playing a significant role. Companies have already been generating and collecting vast amounts of data … now, AI and ML can offer practical advantages to data collection.
As an isolated example, logistics businesses are using AI and ML to track assets and predict the arrival of goods in transit with greater accuracy. This information is invaluable when managing resources and fulfilling service level agreements.
However, AI’s influence extends across all facets of procurement. At the product level, demand is driven by customers developing innovative solutions that leverage AI and ML at both the core and Edge of networks. Additionally, AI is transforming the way businesses respond to emerging trends and demands for their products and services.
Every fluctuation in business operations has a ripple effect that can become amplified throughout the supply chain. As business practices adapt to meet changing customer demands, so too must the supply chain infrastructures that support those industries.
This is where distributors play a key role. Established distributors own extensive customer lists and years of data. While using AI as a business tool is not new, its adoption continues to accelerate. Integrating digital transformation and AI into core business strategies is becoming increasingly common.
The strategic application of AI benefits the entire industry. Distributors have the added benefit of being at the centre of the supply chain, with access to vast amounts of data from customers and suppliers. Companies like Avnet can analyse historical data alongside market trends to predict future demand with greater accuracy.
Analysing product design trends can in turn help optimise inventory management, ensuring a smooth supply chain. For example, AI is used to take those design trends to then infer levels of demand. Analysing customer activity at a meta level identifies those trends, and using AI to determine how it impacts the demand accelerates and improves what has in the past been a manual analysis process. This proactive approach allows companies to provide accurate predictions to customers.
AI is also informing the sales process, by helping representatives suggest equivalent or alternative components based on insights provided by AI. The same technology can now also suggest complementary products based on the trends AI tools see in applications across many vertical markets.
Subject matter experts (SMEs) now use AI when identifying a customer’s best solution from supplier partners across the industry. The decision is based on function, but also global demand, availability, and the customer’s procurement requirements. With enterprise systems that are connected through AI, this holistic approach can be delivered at scale.
The direct benefits of AI in the supply chain
Generating insights into demand benefits both customers and suppliers. Take, for example, component production schedules, particularly for fab-lite semiconductor vendors, which are often set months or years in advance. For fabless manufacturers who rely on merchant fab partners, predicting future demand can improve the supply chain for integrated devices. Insights garnered through AI can help manufacturers manage their product lifecycle and development process.
This is an essential development as manufacturing semiconductors involves a global supply chain, with multiple tiers of value-added stages outsourced to specialists that are distributed across the North American and Indo-Pacific regions. Finished goods enter the part of the supply chain managed by distributors. Sharing reliable predictions about future demand, based on accurate data processed through AI, can enhance efficiency through the entire supply chain.
The integration of AI in procurement processes will continue to grow, with an increasing number of companies adopting AI-driven tools for supplier selection, contract management, and risk assessment. AI-powered analytics will enable companies to build stronger relationships with suppliers by providing real-time insights into supplier performance, quality metrics, and delivery timelines.
The use of AI to enhance supply chain resilience will lead to significant improvements in risk management and contingency planning. AI-driven predictive analytics will become standard practice in demand forecasting, allowing companies to anticipate market fluctuations and adjust procurement strategies accordingly. In addition, the adoption of AI in procurement will drive sustainable practices by optimising resource utilisation and reducing waste.
The future of AI in the supply chain
According to experts like Jensen Huang, CEO of NVIDIA, we’re on a pathway toward agentic AI and physical AI: agents that are intelligent enough to carry out tasks for people, and physical devices (robots) that can act autonomously.
By 2030, possibly sooner, we can expect AI agents representing suppliers and customers to be communicating directly. To realise this vision, every stakeholder in the supply chain would need to agree to some level of data sharing. Is this realistic? Possibly, with the right safeguards in place.
Intelligent and autonomous warehouses and logistics will lead to more efficiency in the final part of the supply chain: delivering products to the customer. Physical AI in the supply chain will involve autonomous mobile robots, automated palletising, truck loading/unloading and, eventually, autonomous delivery vehicles.
AI and the future of procurement
AI has reached an inflection point, democratising research that began decades ago. Companies are both suppliers and consumers of AI technologies, using AI and ML to transform component procurement. Investments in new business technologies will continue to benefit customers. There is no denying that AI is reshaping how we work. Leveraging data and fostering strong relationships will be key to the future of procurement.
This article originally appeared in the May/June issue of Procurement Pro.
