Analyst Insight: Shifting consumer expectations, fragmentation of supply, and greater cost pressures are putting extra burdens on supply chains. These challenges can be tackled by enhanced prediction and visibility gained through artificial intelligence. By using AI to achieve a deeper understanding of consumer purchasing habits, companies can deploy inventory more efficiently and closer to the end customer.
Analyst Insight: Artificial intelligence and machine learning capabilities are being claimed by just about everyone in the supply-chain market today. Equivocating writers, whether marketers, P.R. departments, bloggers, news media or analysts, are cutting a wide swath to include everything in the AI category, rather than clarifying just what it is, and the unique value it may provide. In fact, AI and ML can — and already do — provide tremendous value in augmenting supply-chain applications. And we’re just getting started.
Analyst Insight: Autonomous supply-chain systems (also known as self-driving supply chains) make most decisions automatically, without human intervention. Humans deal with exceptions and those decisions that require human judgment. The autonomous supply chain is a journey, not a destination. There is much foundational work for end users to do, with increasing benefits at each stage. Meanwhile, solution providers are continually building out various elements of autonomy across ever more functions, which are becoming more deeply embedded and intelligent.
In recent years, supply chain has become a hotbed of innovation and a darling of venture investors. A series of new technologies has matured and brought new life to this historically rather stodgy space.