At the most basic level, AI can perform highly complex data-driven tasks and occupationsthat may be difficult for humans. An example is the optimisation of Google data centres — a challenging problem that was previously dealt with by mathematicians and engineers — is now processed by AI resulting in a major reduction of Google’s energy bills. This is achieved by training the AI with tens of millions of data points. While many of these AI applications rely on relatively old techniques, AI is becoming widely viable for diverse application due to increased computing power and data availability.
On the next level, AI can change the structure of business processes. This happens for example in fulfillment centres that store many different goods such as those operated by Amazon. Those centres do not resemble traditional warehouses any more. Goods are stored in pods and when an item is needed for packing, an AI system decides which pod to haul (by robots) to the packer and once the good has been taken by the packer the AI decides where to relocate the pod in the warehouse based on the items left in the pod and the likelihood it will be recalled again.
Finally, AI can impact business models. We expect to see new business models emerging such as personalised shopping and media. In the context of supply chains, we might expect autonomous platooning.
Debating these difference applications of AI, participants of the roundtable concluded that in all applications of AI, the legal implications for privacy and other basic human rights must be respected. How this can be regulated, however, is not self-evident. Furthermore, the roundtable addressed how AI can lead to collusion (e.g. in pricing) that is unintended by programmers. These situations present difficult issues for supply chain partners as well as regulators and judicial systems.
Different from many other technologies, AI will primarily change employment opportunities in white collar, rather than blue collar professions. It was concluded that there is a clear need for highly trained professionals who understand both business (administration) and technologies such as AI and data science. It is up to them to “ask the right questions”, a task that AI cannot take over.
Next LCL Digital Supply Chain Roundtable:
29 November 2017 16:00 – 18:30
Roundtable hosted at Goodyear facility, Colmar-Berg