AI Could Make These Common Jobs More Productive Without Sacrificing Quality – Stanford Graduate School of Business

Report on the Impact of Generative AI on Chile’s Workforce and Alignment with Sustainable Development Goals

Executive Summary

A recent study conducted in Chile reveals the significant potential of Generative Artificial Intelligence (GenAI) to accelerate workforce productivity and contribute to national economic growth. The findings highlight opportunities to advance several United Nations Sustainable Development Goals (SDGs), particularly SDG 8 (Decent Work and Economic Growth), SDG 4 (Quality Education), SDG 9 (Industry, Innovation, and Infrastructure), SDG 16 (Peace, Justice, and Strong Institutions), and SDG 10 (Reduced Inequalities). The report quantifies GenAI’s potential to accelerate tasks across numerous occupations, with the wage-equivalent value of time saved estimated at nearly 12% of Chile’s GDP. Realizing these benefits necessitates strategic implementation, targeted training, and supportive policies.

Fostering Economic Growth and Decent Work (SDG 8)

Macroeconomic Implications and Productivity Gains

The integration of GenAI presents a substantial opportunity for economic expansion and enhanced labor productivity, directly supporting the objectives of SDG 8. Key findings include:

• Widespread Impact: 80% of Chilean workers are employed in roles where GenAI could accelerate at least 30% of their tasks.
• Efficiency Increase: Across all analyzed roles, the average potential increase in efficiency from GenAI integration is 48%.
• Economic Value: The potential time saved translates to a wage-equivalent value of almost 12% of Chile’s Gross Domestic Product.

Sector-Specific Opportunities and Challenges

The study identifies significant potential value gains in key professional sectors, which could drive economic growth. However, it also notes challenges for Small and Medium-sized Enterprises (SMEs), which are crucial for decent work and local economies.

• High-Value Sectors:
  1. Accountants: $1.7 billion in potential annual value.
  2. Lawyers: $1.6 billion in potential annual value.
  3. Engineers: $1.3 billion in potential annual value.
• SMEs: While representing 65% of the workforce, SMEs face barriers such as a lack of digital infrastructure and skills, necessitating targeted support to ensure they can leverage GenAI and contribute to inclusive growth.

Strengthening Institutions and Essential Services (SDG 16 & SDG 4)

Modernizing Public Administration for Stronger Institutions (SDG 16)

GenAI offers a pathway to creating more effective and accountable public institutions. The study estimates that GenAI could unlock over $1.1 billion in annual value within public administration by streamlining tasks for over 84,000 government employees, including data entry, document drafting, and form processing.

Supporting Quality Education (SDG 4)

The technology can alleviate pressure on essential services like education, contributing to SDG 4. By accelerating administrative tasks for elementary school teachers, GenAI could generate over $1.2 billion in potential value. This reclaimed time is critical for addressing teacher shortages and allowing educators to focus on higher-value classroom instruction and student engagement.

Navigating Innovation and Inequality (SDG 9 & SDG 10)

Driving Technological Innovation and Infrastructure (SDG 9)

The research underscores GenAI as a transformative technology that aligns with SDG 9’s focus on innovation. The study measures an “acceleration opportunity” to identify jobs best suited for an AI boost.

• Top AI-Ready Occupations:
  1. Software Developers: 87% acceleration opportunity.
  2. Policy Specialists: 84% acceleration opportunity.
  3. Data Analysts: 80% acceleration opportunity.
• Infrastructure Gap: The uneven digital adoption among SMEs highlights the need for improved digital infrastructure and skills training to ensure broad access to this innovation.

Mitigating Potential for Increased Inequality (SDG 10)

The report indicates that the benefits of GenAI are not distributed uniformly, posing a risk to the goals of SDG 10. The relationship between wages and AI exposure is not linear; gains peak for mid-to-upper income roles and then decline. Physically intensive jobs show low potential for AI integration, while senior executive and medical roles benefit less due to their reliance on human judgment. This disparity requires policies that ensure an equitable transition and prevent the widening of skills and wage gaps.

Strategic Recommendations for Sustainable Implementation

To harness the full potential of GenAI in alignment with the SDGs, the researchers recommend a focused and strategic approach:

1. Target “Quick Wins”: Prioritize implementation in roles with high AI exposure and low adoption friction to build momentum.
2. Focus on High-Impact Areas: Streamline administrative-heavy workflows in schools, government, and SMEs where early successes can demonstrate significant value.
3. Promote Inclusive Adoption: Develop targeted support, training programs, and policies to help SMEs overcome digital barriers and ensure equitable access to technology.
4. Establish a Policy Framework: Implement policies now to manage the workforce transition, foster necessary skills development, and ensure the benefits of GenAI contribute to sustainable and inclusive growth for all.

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article on the impact of Generative AI in Chile’s workforce connects to several Sustainable Development Goals by focusing on economic productivity, quality of public services and education, and the role of technology and innovation.

• SDG 8: Decent Work and Economic Growth

  The core of the article discusses how GenAI can increase productivity and efficiency across various jobs. It directly relates to economic growth by quantifying the potential value AI could add, stating that the time saved could be equivalent to “almost 12% of Chile’s gross domestic product.” The analysis of which jobs are “AI-Ready” and the focus on boosting efficiency in roles from software developers to accountants directly addresses the goal of achieving higher levels of economic productivity.

• SDG 4: Quality Education

  The article explicitly mentions the education sector as an area that could benefit significantly from GenAI. It notes that “Elementary education teachers represent more than $1.2 billion in potential gains from AI.” By suggesting that this reclaimed time could help address Chile’s “growing teacher shortage,” the article connects technological advancement to improving the conditions and effectiveness of the education system.

• SDG 9: Industry, Innovation and Infrastructure

  This goal is relevant through the article’s emphasis on technological upgrading and innovation as a driver of productivity. The study itself is an example of research promoting innovation. Furthermore, the article highlights the challenges for Small- and medium-sized enterprises (SMEs), which “may lack the digital infrastructure, skills, or tools to use these systems effectively,” pointing to the need for better infrastructure and support to ensure widespread adoption of new technologies.

• SDG 16: Peace, Justice and Strong Institutions

  The article identifies “public administration as a priority for early adoption” of GenAI. It estimates that AI could “unlock over $1.1 billion in value annually” by streamlining tasks for over 84,000 government employees. This directly relates to building more effective and efficient public institutions, as AI can help reduce red tape and improve the delivery of government services.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the issues discussed, the following specific targets can be identified:

1. Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation.

   The entire premise of the study is to quantify how GenAI, a form of technological upgrading and innovation, can boost productivity. The article states that “nearly half of the tasks performed by the country’s 100 most common jobs could be ‘accelerated’ using GenAI” and that the “average increase in AI-boosted efficiency across all roles is 48%.” This directly aligns with the objective of increasing economic productivity.

2. Target 8.3: Promote development-oriented policies that support productive activities… and encourage the formalization and growth of micro-, small- and medium-sized enterprises (SMEs).

   The article highlights that SMEs, which “account for 65% of Chile’s workforce,” show “strong acceleration potential.” However, it also points out the need for “targeted support and training” to overcome their lack of digital infrastructure and skills. This focus on enabling SMEs to adopt new technology and grow supports this target.

3. Target 4.c: By 2030, substantially increase the supply of qualified teachers…

   While the article does not discuss creating new teachers, it addresses the problem of a “growing teacher shortage” in Chile. By suggesting that GenAI can reclaim significant time for elementary teachers, it offers a way to improve their working conditions, reduce burnout, and make the profession more sustainable. This contributes to retaining the existing teacher workforce, which is a crucial part of maintaining an adequate supply of qualified educators.

4. Target 16.6: Develop effective, accountable and transparent institutions at all levels.

   The recommendation to target “quick wins” in “admin-heavy workflows in… government” directly supports this target. The article estimates that GenAI could streamline tasks like “data entry, document drafting, or form processing” for thousands of government employees, leading to more efficient and, therefore, more effective public institutions.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions and implies several quantitative and qualitative indicators that can be used to measure progress.

• Indicators for Target 8.2 (Economic Productivity):

  • Percentage of tasks accelerated by GenAI: The study finds that “nearly half of the tasks” in common jobs could be accelerated. This percentage can be tracked over time.
  • Increase in efficiency: The article provides a baseline metric: “The average increase in AI-boosted efficiency across all roles is 48%.”
  • Economic value of time saved: The study estimates the value of time saved at “almost 12% of Chile’s gross domestic product.” This monetary value serves as a powerful indicator of productivity gains.

• Indicators for Target 4.c (Supply of Teachers):

  • Value of potential gains in the education sector: The article quantifies this as “$1.2 billion in potential gains from AI” for elementary teachers. This can be used as a proxy for the amount of time and resources freed up.
  • Teacher workload reduction: While not given a number, the concept of “reclaimed time” for teachers is an implied indicator that could be measured through surveys on teacher workload and satisfaction, which in turn affects retention rates and addresses shortages.

• Indicators for Target 9.3 & 8.3 (SME Growth and Innovation):

  • Rate of digital technology adoption by SMEs: The article implies this indicator by stating that “digital adoption remains uneven for many of these businesses.” Measuring the percentage of SMEs that successfully integrate GenAI tools would indicate progress.
  • Number of SMEs receiving targeted support and training: The need for such programs is explicitly mentioned, so tracking their implementation and reach would be a relevant indicator.

• Indicators for Target 16.6 (Effective Institutions):

  • Economic value unlocked in public administration: The article estimates that “GenAI could unlock over $1.1 billion in value annually” in this sector. This serves as a direct indicator of increased efficiency.
  • Number of public sector roles impacted: The study identifies “more than 84,000 Chilean government employees” in roles that could be streamlined. Tracking the number of employees using AI tools to improve their workflow is a measurable indicator.

4. Table of SDGs, Targets, and Indicators

Source: gsb.stanford.edu