Generative AI is a branch of artificial intelligence that can create new content, such as text, images, music, code, and more, based on existing data and models. Examples of generative AI include chatbots, deepfakes, neural style transfer, and GPT-4. Generative AI has the potential to revolutionize many industries and domains, such as entertainment, education, health care, and e-commerce. But what will be the impact of generative AI on jobs and skills in the labor market?

The Global Outlook

According to the latest reports from the World Bank and the OECD, the global economy is expected to grow at a moderate pace over the next decade, but with significant variations across regions and sectors. The World Bank projects that global growth will average 2.4% per year in 2024-2030, down from 2.7% in its previous forecast, mainly due to the effects of monetary and fiscal tightening, trade tensions, and environmental challenges. The OECD forecasts a slightly higher growth rate of 2.7% in 2023 and 2.9% in 2024, driven by strong consumer spending, investment, and productivity gains in some countries.

Both reports highlight the role of generative AI as a key driver of innovation and productivity, but also as a source of disruption and uncertainty for workers and businesses. The World Bank estimates that generative AI could affect 40% of jobs and 2.5% of tasks in the global economy, with varying degrees of automation and augmentation. The OECD predicts that generative AI could create new jobs and tasks, but also displace or transform existing ones, requiring workers to adapt and reskill.

According to Goldman Sachs Research, if generative AI tools continue to advance and integrate into businesses and society, they could contribute to a 7% increase in global GDP (approximately $7 trillion) and boost productivity growth by 1.5 percentage points over a decade. This advancement could break down communication barriers between humans and machines, leading to substantial macroeconomic effects.

However, it’s essential to approach this potential impact with realism. While generative AI can drive cost reduction and productivity gains, we should not overstate its macroeconomic effects. The winners in this scenario are likely to be consumers, as technology-driven cost reductions translate into lower prices. On the other hand, some firms may lose out as cost leaders reap the benefits.

The rise of generative AI also raises questions about employment markets. As workflows shift due to AI advances, approximately 300 million full-time jobs worldwide could be exposed to automation. In the United States, around two-thirds of occupations have some degree of exposure to AI-driven automation. While a significant impact on the labor market is expected, not all automated work will necessarily lead to layoffs. Most jobs and industries are only partially exposed to automation, and AI may complement rather than fully substitute human labor.

What will be the impact of Generative AI on jobs?

The impact of generative AI on jobs and skills will depend on several factors, such as the level of education, income, and occupation of workers, the sector and location of businesses, and the policies and institutions of governments. Some general trends can be identified, based on the existing literature and data:

  • Higher-wage workers are more likely to benefit from generative AI, as they have more skills and opportunities to use and manage the new technology, and to complement it with human creativity and judgment. Lower-wage workers are more likely to face competition from generative AI, as they perform more routine and repetitive tasks that can be easily automated or outsourced. This could widen the income gap and increase inequality within and between countries.
  • Emerging markets are more likely to experience faster growth and convergence with developed markets, as they have more potential to adopt and leverage generative AI, and to benefit from its spillover effects. However, they also face more challenges in terms of infrastructure, governance, and social protection, which could limit their ability to cope with the transition and mitigate the risks. Developed markets are more likely to face slower growth and divergence with emerging markets, as they have more constraints and costs in terms of regulation, taxation, and labor market rigidities, which could hamper their innovation and competitiveness.
  • Some sectors and industries are more likely to thrive with generative AI, as they have more demand and supply for the new content and services that it can produce and deliver. These include entertainment, education, health care, and e-commerce, among others. Some sectors and industries are more likely to struggle with generative AI, as they have more exposure and vulnerability to the substitution and disruption that it can cause. These include manufacturing, retail, transportation, and finance, among others.

A recent World Economic Forum study identifies professions that have high potential for automation and task augmentation by generative AI or Large Language Models (LLMs). These professions will be most affected by generative AI and they involve routine and repetitive procedures, minimizing the need for extensive interpersonal communication.

This is based on their analysis of “exposed tasks”. That is, tasks that are exposed to automation and augmentation by Gen AI. Tasks with the highest potential for automation by Large Language Models (LLMs) typically involve routine activities, including administrative or clerical tasks, as well as elementary analytical functions like designing databases or analyzing data. Conversely, tasks with the greatest potential for augmentation necessitate advanced abstract reasoning skills, particularly those that involve a combination of intellectual acumen and interpersonal interaction. The jobs that require above skills have more exposure to be impacted by Gen AI.

According to the study, the top 5 professions that have high potential for automation by Gen AI are:

  1. Credit Authorizers, Checkers and Clerks
  2. Management Analysts
  3. Telemarketers
  4. Statistical Assistants
  5. Tellers

It also suggests that the jobs with the highest potential for augmentation by LLMs emphasize critical thinking and complex problem-solving skills, especially those in science, technology, engineering and mathematics (STEM) fields.

The top 5 professions that have high potential for augmentation by Gen AI are:

  1. Insurance Underwriters
  2. Bioengineers and Biomedical Engineers
  3. Mathematicians
  4. Editors
  5. Database Architects

On the other hand there are some professions that are less affected by the Gen AI. The white paper says -

“Jobs emphasizing non-language tasks are expected to be less exposed, or not exposed at all, to the potential impacts of LLMs. Results of the task analysis suggest this, indicating that jobs with the lowest potential of exposure (either automation or augmentation) are those that require a high degree of personal interaction, such as Healthcare Professionals or Teachers, or physical movement, such as Athletes or Manual Labourers.”

According to the study, the top 5 jobs that have low potential for automation or augmentation by Gen AI are:

  1. Educational, Guidance, and Career Counsellors and Advisers
  2. Clergy
  3. Paralegals and Legal Assistants
  4. Home Health Aides
  5. Anaesthesiologists

The New Skills and Jobs

Historically, jobs displaced by automation have been offset by the creation of new jobs. Technological innovations, including information technology, have given rise to new occupations and contributed to long-term employment growth. Therefore, while generative AI presents challenges, it also opens up opportunities for innovation and adaptation in the workforce. The advent of generative AI will create new skills and jobs, but also change the nature and requirements of existing ones. Workers and businesses will need to adapt and reskill to stay relevant and competitive in the changing labor market. Some of the new skills and jobs that generative AI will generate or enhance include:

  • Data and AI skills: These are the skills needed to collect, process, analyze, and interpret data, and to design, develop, and deploy generative AI models and applications. These skills are in high demand and short supply in many sectors and regions, and will become even more critical and valuable in the future. Data and AI skills include data science, machine learning, natural language processing, computer vision, and more.
  • Creative and artistic skills: These are the skills needed to produce original and engaging content, and to express and communicate ideas and emotions. These skills are less susceptible to automation and more complementary to generative AI, as they rely on human imagination and intuition. Creative and artistic skills include writing, music, design, photography, and more.
  • Ethical and social skills: These are the skills needed to ensure the responsible and beneficial use of generative AI, and to address the ethical and social implications and challenges that it poses. These skills are essential for building trust and accountability among stakeholders, and for promoting the common good and human values. Ethical and social skills include critical thinking, problem-solving, communication, collaboration, and more.

The Way Forward

Generative AI is a powerful and promising technology that can transform the future of work for the better, but also pose significant challenges and risks for workers and businesses. To harness its potential and mitigate its pitfalls, it is important to adopt a proactive and collaborative approach, involving multiple actors and perspectives. Some of the key actions and recommendations that can help achieve this include:

  • Investing in education and training: This is crucial for developing the skills and competencies that workers and businesses need to adapt and thrive with generative AI, and for reducing the skill gaps and mismatches that could hinder its adoption and diffusion. Education and training should be accessible, affordable, and relevant, and should cover both technical and non-technical skills, as well as lifelong learning opportunities.
  • Fostering innovation and entrepreneurship: This is vital for creating the products and services that generative AI can enable and enhance, and for generating the jobs and income that it can support and sustain. Innovation and entrepreneurship should be encouraged, facilitated, and rewarded, and should involve both public and private actors, as well as cross-sectoral and cross-regional collaboration.
  • Strengthening regulation and governance: This is necessary for ensuring the quality and safety of generative AI, and for addressing the legal and ethical issues and dilemmas that it raises. Regulation and governance should be clear, consistent, and coherent, and should balance the interests and rights of different stakeholders, as well as the trade-offs and tensions between innovation and protection.

Generative AI is a game-changer for the future of work, and for the future of humanity. It offers immense opportunities and challenges, and requires a collective and coordinated response. By taking the right actions and adopting the right policies, we can make generative AI work for us, not against us, and create a more prosperous, inclusive, and sustainable world.

Upskilling and reskilling are essential to staying relevant in the changing workforce landscape. Embracing emerging technologies, such as AI, and acquiring the skills required to leverage them can open avenues for personal and professional growth.

It is crucial for individuals and societies to adapt to the changing nature of work. Rethinking education, fostering a culture of lifelong learning, and investing in comprehensive job training programs are key steps towards building a workforce that can thrive in the age of Gen AI.

FAQs (Frequently Asked Questions)

Q: What is Gen AI, and what is its potential impact on jobs?

Generative AI refers to a category of artificial intelligence systems that are designed to generate new content, often in the form of images, text, or other media. Unlike traditional AI systems that may be rule-based or rely on pre-existing data patterns, generative AI has the ability to create original content that wasn’t explicitly programmed or seen during training. Check this blog post to know more.

Q: Which industries are most likely to face job disruptions due to Gen AI?

Industries such as administrative and clerical roles, manufacturing and production, transportation and delivery services, customer service and support, financial and accounting, and medical and healthcare are likely to face significant job disruptions due to Gen AI.

Q: How can individuals and societies prepare for the future of work?

Individuals and societies can prepare for the future of work by embracing emerging technologies, such as AI, and acquiring the necessary skills to leverage them effectively. This may involve upskilling, reskilling, and investing in comprehensive job training programs to stay relevant in the changing workforce landscape.