Restricting innovation is necessary to address uncertainties in technologies like Artificial Intelligence (AI). Global leaders like the US, Europe, and China are implementing new rules to address potential harms and attract large investments.

The AI change could lead to fewer jobs and a smaller job market. Capital-intensive manufacturing and skill-biased tech development could make wage gaps bigger and put low-skilled workers out of work. The service industry would be hit the hardest. Chinese studies show that jobs that require a lot of skill are less likely to be taken over by AI than jobs that require less skill. In economies that are getting older, replacement caused by AI is more “complementary substitution” than “extrusion substitution.”

Due to job losses caused by AI, workers may look for jobs in a more sophisticated way, which could increase job opportunities and overall employment. The STARA awareness measure was made by academics in New Zealand. It shows that digital education and skills for all jobs may be important to reduce the need for jobs in an AI-driven future. Skill replacement is more than just a technological problem; it also has ethical and social effects that have policy implications.

The job scenario

Plans need to change to keep up with the need for more skilled workers. A UK based study shows that “feeling intelligence” will be more important than jobs that require thinking. Management should put the well-being of their employees first by choosing people with good people skills instead of analytical skills, which are more likely to be automated.

Women do well in fields that require empathy and emotional intelligence, and companies should worry less about AI taking jobs and more about how to adapt to a changed job market. AI prediction tools can help doctors use things that make sense from a theoretical point of view, and machine learning translation may be better at translating languages. Patterns of AI investment by job type and business show different things.

What about wage inequality?

A great deal of variation is possible in terms of wage income. AI may replace some skill categories and affect lower-skilled employment, affecting labour pay. As AI-dependent sectors and enterprises move to States or regions with more AI-compatible skill sets, labour market outcomes may vary by location. This could cause skill-mismatches in locations where demand for AI-compatible skills rises and others fall.

To address AI, institutions, policymakers, and governments must design skilling and vocational training. To enable this change, legislative and labour market policies must be explored. AI is neither artificial nor intelligent. Prioritising pragmatic efforts today will help prepare for this scenario.

Sahana is Associate Professor (Economics), IMI Kolkata, and Dona is Assistant Professor of Economics at Thiagarajar School of Management