Generative AI (GenAI) looks ready to challenge and dominate the labour market, but potentially only the part of the market that graduates don’t need to do anymore that deteriorate their wellbeing. One of the main reasons for AI adoption is the “need to reduce costs and automate key processes”, and GenAI has greatly addressed the bottleneck in product development, sales activities, prototyping, media creation, and many other fields of work (Bashynska et al., 2023). However, fear and insecurity can arise when the work activities known to graduates are being replaced by GenAI tools.
In building the sales infrastructure of online businesses I use GenAI very often. The more I use it the more I realise how much I overlooked the true value of being able to relate to people. Szufang Chuang’s study on the impact of robots and AI on human employee skills goes further by defining the key skillsets as social skillset and decision-making skillset (Chuang, 2024). The key in both skillsets is ‘nuance’. The ability to recognise the nuance of a context and make a high level decision is only going to be in more need to complement GenAI tools. Thus, recent graduates are in the best position to design the jobs of the future that haven’t been created yet. GenAI as a support tool is creating the demand for a labour force that is experienced with GenAI, has technical training on IT tools, and is aware of higher level business activities (Soni, 2023). It is no longer enough to be a pure technician or just a manager.
a.k.a. An IT or BIM graduate
There are entire industries that are rapidly shifting to employing graduates with both technical and social skillsets, but no one knows what these jobs will truly look like. The answer is not in this blog post, but in the decisions of the next cohort of graduates. It is an opportunity to shape the nature of work to reduce burnouts, to reduce financial insecurities, and to simply advocate for the wellbeing of people.
References:
Bashynska, I., Prokopenko, O., & Sala, D. (2023). Managing human capital with AI: Synergy of talent and technology. Zeszyty Naukowe Wyższej Szkoły Finansów i Prawa w Bielsku-Białej, 27(3), 39-45.
Chuang, S. (2024). Indispensable skills for human employees in the age of robots and AI. European Journal of Training and Development, 48(1/2), 179-195.
Soni, V. (2023). Impact of generative AI on small and medium enterprises’ revenue growth: the moderating role of human, technological, and market factors. Reviews of Contemporary Business Analytics, 6(1), 133-153.
I like your optimism – seeing GenAI not as a threat but as a filter that removes the low-value work. Your argument that “nuance” and social skills become premium complements to automation fits well with what we discussed about human-AI collaboration. I’d add that the timing might also create a skills bifurcation: graduates who learn to design GenAI-supported workflows will rise fast, while those who just use GenAI tools could stagnate. Do you think universities are adapting quickly enough to teach that higher-order design mindset?