I experienced the start of the Internet and email in late ’90s when I oversaw transportation for Americas for a large OEM. All the express integrators I dealt with had major concerns about email replacing their high volume and lucrative envelop business, both domestically as well as internationally. And so, it did. What they had not expected was the creation of a new market: small parcel express business. This market saw huge growth in the following decades and continues to be more and more lucrative due to the e-commerce business.
The debate over technological achievements destroying jobs is nearly a century old. In all the waves of technical progress we have established that overall, technological unemployment (loss of jobs caused by new technologies) is a myth. I will make my point with a more recent example from our industry.
Before the Covid-19 pandemic, a large OEM I worked for had introduced industrial 3D printing. At the time, industrial and consumer 3D printing was in the headlines as a potential new revolution. Logistics service providers were concerned about 3D printing taking over their traditional warehousing and cross-dock business. What they didn’t realize then that they would be the perfect solution provider for 3D printing capabilities in their existing contract logistics sites. Combining traditional contract logistics to store raw materials for 3D printing and combining end distribution with it. 3D consumer, commercial, and industrial printing is still a developing business, but has given a lot of great solutions to the logistics industry already.
“From pick, pack, and ship to print, pack, and ship: 3D printing technology created new business opportunities rather than destroying existing ones.”
如今，人工智能（AI）技术已成为头条新闻，而它的实施及其对供应链行业的影响还没有被完全理解。我们可以选择人工智能将如何定义未来的工作：我们可以用它来简单地取代工人，也可以用它来扩展工人的技能和能力，从而带来增长和新的工作岗位¹。
问题不在于人工智能是否会改变我们所熟知的供应链，因为变革已经开始。只要观察一下劳动力、网络犯罪、地缘政治和关税、战争和自然灾害的趋势就知道了。 供应链行业的组织机构需要弄清楚的是，利用人工智能应对这种变化的最佳方式是什么，轻松应对过渡，然后凭借弹性和敏捷的供应链生态系统脱颖而出。
To make AI work for your organization, you need: data standardization and a single source of truth. AI is only as good as the data we feed into it. If it takes a week to collect data from different interfaces by downloading it from multiple spreadsheets, cleaning it up, and then preparing everything in a single format to feed into an AI engine, the results are dated. You can’t blame AI for it.
What you need is an automated solution where real-time data (time stamped and tamper proof) in a single format is being fed into an AI engine. This way AI constantly iterates on live-data and the results are useful.
The Vinturas Interoperable Network (VIN) solution is a key enabler for the AI models of our customers. After successful implementations with our customers and their AI partners, I am confident of the impact of AI in supply chain planning, manufacturing, logistics, maintenance, and many other applications.
AI will create more jobs than it destroys. Personally, I believe it will create a lot of new business and related employment opportunities. But the success will be based on entrepreneurship and being open to new technologies. Other big determinators for success are the quality of meta-data and a level of (governmental) control, to prevent traditional AI, generative AI, and augmented AI being used for evil purposes.