As I transitioned from management consulting to strategy in banking, the topic of GenAI is brought up constantly – and it is typically mentioned in open ended questions or broad conceptual statements. Daily, I hear colleagues express sentiments like “GenAI will greatly streamline the way in which consumers browse items for purchase online and navigate the transaction process” or “GenAI will change the way that employees learn new tasks and apply knowledge”. I realized that we are all at varying stages of technological foresight, but there’s general alignment that things will be substantially different within the next five years.

I quickly understood that while the technology is somewhat advanced, we are in nascent phases of understanding how it will actually be deployed and the degree of ‘encroachment’ we can expect for our careers presently. Thankfully, we have folks who are already giving this significant thought (and publishing their findings), including the World Economic Forum.

The World Economic Forum shared a number of interesting data points in its ‘2025 Future of Jobs Report’ on this topic. The highlights are as follows:

1. Despite its nascency in workforce deployment, adoption will continue to steepen across industries – WEF estimated that investment in GenAI technology has increased 8x since ChatGPT’s initial release in November 2022!
2. The extent to which the technology will substitute versus enhance human labor remains very uncertain – but foundational and use-case specific skilling is paramount. Online learning providers are seeing an uptick in demand for GenAI courses, but ‘type’ of demand isn’t uniform
   • In countries like US, individuals are looking to develop foundational GenAI skills (e.g., how to write good prompts, GenAI risks and limitations), whereas in places like India, employers are sponsoring training for employees to learn how they can use GenAI in their particular jobs/roles to enhance productivity/output
3. As the workforce landscape evolves, the following skill groups are set to experience the most growth in demand for the 2025-2030 period (net increase, across industries): AI and big data (+87%), networks and cyber (+70%), tech literacy (+68%), creative thinking (+66%), resilience/flexibility/agility (+66%), curiosity and lifelong learning (+61%), leadership and social influence (+58%), talent management (+58%), analytical thinking (+55%), and environmental stewardship (+53%)
4. The following skill groups currently have the lowest capacity for substitution with GenAI: Empathy and active listening, sensory processing/abilities, manual dexterity/precision, environmental stewardship, creative thinking, teaching/mentoring/coaching, resilience/flexibility/agility, global citizenship, service orientation and customer service, and analytical thinking

So what?

Across the ‘top ten’ lists for skill demand growth and substitution capacity (I think of this as substitution difficulty), two skills appear on both: Creative thinking and analytical thinking.

We often think of these two skills as ‘innate’, meaning we think that people are born with or without the skill and navigate the workplace accordingly. However, the idea that these our skill levels in both of these domains are largely untrue – academic research suggests that both creative and analytical thinking are skills that can be developed through intentionality. Since these skills may be rewarded and valued uniquely in our future workforce, it may be worth it to invest in developing them.

Quick ways to develop creative thinking (from the American Psychological Association): Purposeful daydreaming, developing remote associations (writing down ideas and random thoughts/ideas that accompany them), spending time in nature, and revisiting old ideas/thoughts

Quick ways to develop analytical thinking (from the Harvard Business Online Business Insights Blog): Actively considering opposing viewpoints, playing brain games/brain teasers, taking online analytics courses, and engaging with data (viewing open datasets online or creating mock data sets to practice data analysis)

BTW: In my next piece, I’m hoping to look at the value of generalist versus technical skills in the future workforce and understand what that means from an upskilling perspective. Chat soon!