Workforce reduction and the areas of people touched by AI
While AI drives employment numbers, the same technology is also powering election information, romantic and child-rearing advice, cancer predictions, and military and pharmaceutical operations. IT giants are reported to have cut nearly 200,000 jobs worldwide, but the scale of the cuts is just part of the changes taking place. Only 8% of American adults get election information from AI chatbots, and if a major AI dating service goes bankrupt, users' partners will be deleted. Regardless of whether the numbers are large or small, humans are increasingly receiving answers from AI and using them as the basis for decisions and relationships. What I would like readers to take away from this half-day is the question of how far we can leave things to AI, and where we should draw the line. The sections below show how the line is positioned differently in different industries and situations.
Indian economic newspaper Livemint reported that major IT companies have cut nearly 200,000 jobs worldwide due to AI transformation. The scale of reductions has already exceeded that of any one company or country. Al Jazeera highlighted that the UK is leading the way in layoffs related to AI and discussed the reasons for this. In the financial sector, Barclays has been reported to have both layoffs due to AI and excessive concerns about bank taxes (Seeking Alpha). Similar movements are occurring in different industries and regions, such as IT, the UK, and banking. Therefore, it is necessary to view AI and employment not as management decisions for one company, but as phenomena common to multiple industries.
This movement is also spreading outside of employment. The IMF cited both high energy prices and AI as burdens in its assessment of the challenges facing Asian economies (India Today). While AI transformation is a cost-saving measure for businesses, it also creates an adjustment burden for the economy as a whole. Furthermore, in the case of banks, the topic of layoffs is discussed in the same context as the institutional issue of bank taxes (Seeking Alpha). When reading a company's reduction plans, unless you look at them in conjunction with tax and regulatory developments, you will not be able to tell whether the decision was made independently or whether it was influenced by the system.
The same trend is appearing in medical organizations. According to Hospitalogy, the CEO of Navvis, head of healthcare, said that while value-based care (VBC) has moved towards outcomes, LEAD has been put on hold. He then talks about preparing for risk models that could become mandatory. What's going on here isn't the AI itself. Payment and evaluation mechanisms are changing, and organizations are being forced to restructure accordingly. Even if the mandate is postponed, the need to be prepared remains. This point overlaps with the example of the United Kingdom, where personnel reductions proceeded faster than institutional improvements.
