Is Your Career at Risk due to Generative AI? Read This and Plan it Before It's Too Late

As generative AI continues to advance, the landscape of the job market is poised for significant changes. A recent study has provided us with a scatter plot graph that illustrates the potential impact of AI on various job roles, using two key metrics: the Exposure Score and the Friction Score. In this article we have explained how AI will impact your job role. If you have any question or want to plan how you can do better transition and reduce the impact of AI on your job role, get in touch!

This article is in continuation of my previous article, https://www.dhirubhai.net/pulse/generative-ai-could-deliver-up-1-trillion-annual-growth-pathan-ikidf/ , https://www.dhirubhai.net/pulse/1-trillion-productivity-story-generative-ai-catch-pathan-a6agf, https://www.dhirubhai.net/pulse/detailed-decoding-job-disruption-due-generative-ai-pathan-obqjf This article delves deeper into GenAI job disruption. Building on the foundation laid in the earlier discussion, here I provide more detailed insights and expanded analysis on how GenAI have a significant impact on different job roles with the help of exposer score and friction score.

Understanding the Scores

• Exposure Score: This metric gauges the extent to which a job could be automated by generative AI. It considers the number of tasks within a job that could be either fully automated or assisted by AI, as well as the importance of these tasks.
• Friction Score: This score reflects the difficulty individuals may face when seeking new employment. A high friction score indicates a challenging job market, while a low score suggests an easier transition to new work opportunities.

High-Risk Job Roles

The graph reveals that job roles with high exposure and high friction scores are at the greatest risk. These include positions where routine tasks are prevalent and where the job market is already saturated or highly specialized. For example, roles in data entry, customer service, and manufacturing show high exposure to AI disruption due to the repetitive nature of tasks that can be easily automated.

Low-Risk Job Roles

Conversely, jobs with low exposure and low friction scores are deemed safer from AI disruption. These roles often require a high degree of human interaction, creativity, or complex problem-solving that AI cannot easily replicate. Positions in healthcare, education, and creative industries fall into this category.

Role wise risk explanation

1. Management: From strategizing to decision-making, management roles rely heavily on cognitive skills that could be augmented or even replaced by advanced AI systems that can rapidly analyze data and provide recommendations. These roles face high AI exposure risk and high difficulty finding new work.
2. Business/Finance Ops: Roles like accounting, finance, and operations involve numerous analytical and administrative tasks ranging from bookkeeping to forecasting that AI could streamline or automate. This field faces high disruption risk and high friction for career transitions.
3. Computer/Math: As the makers of AI itself, roles in computer science, data science, and mathematics paradoxically face disruption from the very technologies they innovate and develop. However, they are also at high risk with high difficulties shifting to new roles.
4. Architecture/Engineering: The design and engineering of structures, systems, and products requires modeling, simulations, and calculations that AI excels at, though human creativity remains essential. These occupations face high AI exposure and high job transition friction.
5. Life/Social Sciences: From modeling biological systems to analyzing sociological data, AI capabilities could empower or disrupt roles in fields like biology, chemistry, psychology, and anthropology. However, these roles face average AI disruption risk.
6. Community/Social Services: Compassion remains core to social work, counseling, and community outreach, but AI could assist with casework, resource allocation, and identifying intervention needs. These roles have average exposure risk.
7. Legal: AI shows potential in automating legal research, drafting documents, and even advising - though roles like litigation and negotiations require human experience and judgement. The legal field faces average AI risk but high difficulty finding new roles.
8. Education: While AI tutoring could provide personalized instruction, the essential human role of educators in shaping young minds may be difficult to fully replicate, resulting in average exposure risk.
9. Arts/Media: From storytelling to graphic design, creative fields rely on human ingenuity - however, AI could become a supplemental tool for artists, musicians, and content creators. This sector sees average AI impact but lower friction to shift roles.
10. Healthcare Practitioners: Though AI diagnostic tools are emerging, human doctors, nurses, and clinicians provide vital experience, bedside manner, and ethical decision-making. Healthcare practitioners have average exposure risk but high job transition difficulty.
11. Healthcare Support: Roles like home health aides, nursing assistants, and orderlies provide crucial human care and interaction that AI systems cannot easily replicate, resulting in lower AI risk but high friction finding new work.
12. Protective Services: Law enforcement, firefighting, and security duties require skilled human judgment in dangerous situations that AI currently cannot match, leading to low AI exposure risks, though high job transition difficulty.
13. Food Service: While AI could automate some food prep tasks, human chefs, servers, and bartenders deliver the experiential essence of restaurants and hospitality, representing lower AI risks but high career change challenges.
14. Cleaning/Maintenance: Though AI could map processes, physical cleaning, repairs, and groundskeeping remain inherently human-powered services for now, with low automation risks but high job transition friction.
15. Personal Care: From hairstyling to childcare, personal care demands human empathy and dexterity that AI cannot yet provide, corresponding to low disruption risk and lower difficulty finding new roles.
16. Sales: Building customer rapport and negotiating deals taps into human skills like communication and emotional intelligence that AI lacks, indicating lower AI impact and lower friction to transition.
17. Office/Admin: AI could streamline data entry, scheduling, and clerical tasks, but human oversight remains essential, representing lower risks though average difficulty level for job changes.
18. Farming/Forestry: Roles like ranchers, farmers, loggers rely on skills interfacing with nature that defy automation, resulting in low AI risks but high obstacles to career transitions.
19. Construction: Though AI could model projects, the physical work of builders and laborers cannot be easily replicated yet, leading to lower automation risks but high job change friction.
20. Installation/Repair: Troubleshooting, maintenance, and hands-on repair require human expertise and dexterity, corresponding to lower AI risks with average career transition difficulty.
21. Production: While AI optimizes processes, human quality control remains vital, indicating lower automation risks and average difficulties moving roles.
22. Transportation: Though self-driving vehicles are emerging, human truck, delivery, and transportation workers ensure mobility, representing lower AI risks but high friction for job transitions.

Navigating the Transition

For those in high-risk roles, it’s crucial to focus on skills that are less susceptible to automation, such as emotional intelligence, critical thinking, and interpersonal communication. Additionally, exploring roles in emerging industries that are likely to expand with AI advancements can provide new career pathways.

Conclusion

The integration of generative AI into the workforce is inevitable, but it also brings opportunities for growth and innovation. By understanding the exposure and friction scores, individuals and organizations can better prepare for the future, ensuring a workforce that is resilient and adaptable in the face of AI disruption.