There are, of course, exceptions, and one example is the supply chain, a vast and critical sector long held back by its dependence on outdated, often error-ridden, back-office operations based on documents and spreadsheets. Costly and chronic inefficiencies were brutally exposed during the height of the COVID era. Fast-forward to today and the advent of tariff-based trade wars, with work underway to rethink, modernize, digitize, and leverage AI and automation as fast as possible. It is important to note that few, if any, jobs are expected to be lost here—cutting costs by cutting jobs is not the intent. The goal is redesigning processes to scale and leveraging modern automation technologies to reduce errors and exceptions, in turn reducing
unnecessary costs and building in resilience and growth in a wildly erratic and unpredictable trading environment.
Technology Potential
At Deep Analysis, we believe in hon- esty and transparency. AI can be used (as it usually is) as a blunt instrument to reduce headcount, but it doesn’t have to be that way, and indeed that approach seldom works out well. Organizations, whether private or public, are driven to be more efficient, to ideally do more with less. That is how the world works. Technologists are encouraged to create and envision new systems, new tools, and new solutions. The disconnect comes between technology’s potential and its real-world application.
The first industrial revolution was powerful and enriched a few, but it took three full generations before the benefits trickled down to the majority. In other words, the mechanization of labor was merely that, and it was destructive for large swathes of the population for many years. However, we always have a chance to learn from history rather than merely repeating it. History tells us that industrial revolutions ultimately do create more jobs, but that the transition period is long and highly turbulent. Thus, when we see resistance in the workplace to AI and automation in general, we should acknowledge that the resistance and fear are well-grounded. As an industry, we need to be more honest about the hard reality of AI and automation, its potential, and its often clumsy misuse. And we must resist the platitude that it will all be OK and that those impacted will be moved to better and more fulfilling jobs. Nobody is buying that argument. We all know that they won’t.