This article is a technical explanation and implementation example generated using AI. The code and procedures presented are based on primary sources, but the author has not verified their operation on actual devices. Operation may vary depending on the environment and version.

Google AI & Understanding the Structure of AI Economics from the Expansion of the Economy Team

, based on primary information regarding the expansion of the "AI & Economy Research Program" promoted by Google, safely and practically organizes the research system and an overview of the public data platforms used to scientifically track the impact of AI on the labor market and macroeconomics. By examining the background of specific expert participation and the four core areas established by the organization, the objective is to comprehensively grasp the economic transition accompanying technological innovation.

The structure of this article is as follows.

1. Objective

2. Prerequisites and Precautions

3. AI & Components of the Economy Research Program

4. Key Participating Experts and Leadership

5. Methods for Verifying the Scientific Approach

6. Limitations of This Initiative

7. Summary

1. Objective

The purpose of this paper is to accurately understand the structure of the impact that the rapidly progressing adoption of artificial intelligence has on global economic activity, employment, and productivity, based on officially announced primary sources. Beyond a mere functional evaluation of AI technology, this paper outlines the mechanisms of macroeconomic attraction through collaboration between academia and industry, as well as the comprehensive methodology for measuring changes in the labor market.

2. Prerequisites and Precautions

• This article is research and commentary based on primary sources such as official blogs, and does not include code execution on actual devices or independent benchmark measurement results by the author.

• Google's AI &When exploring data and tools related to the Economy Research Program, please refer to the officially provided link (Google AI Economy).

• Because evaluating technological transitions and economic impacts is multifaceted, it requires continuous data tracking rather than relying on a single metric.

3. AI &Economy Research Program Components

Through Google's AI &Economy Research Program and the "AI &Economy ATLAS v1.0," initiatives are underway to visualize the usage status of AI tools in daily operations and life. Noting that technological shifts do not occur instantaneously, primary sources identify the following as core areas for measuring and analyzing evolution in real time:

• Future of Work

• Productivity and Growth

• Global Technology Diffusion

• AI’s Impact on Scientific Discovery

The structure of these programs and the relationships among key members are shown below.

flowchart TD
    A[Google AI & Economy Research Program] --> B[未来の働き方]
    A --> C[生産性と成長]
    A --> D[世界的な技術普及]
    A --> E[科学的発見へのAIの影響]

    F[Director & Academic Advisors] --> A
    F --> G[Anu Madgavkar & Daniel Rock]
    F --> H[Philippe Aghion & Ajay Agrawal]

4. Participating Key Experts and Leadership

To empirically analyze complex economic transitions and labor market fluctuations, global economists and academic advisors are participating in the program. The roles of the main members introduced in the primary sources are as follows.

• Philippe Aghion (Academic Advisor): Recipient of the 2025 Nobel Prize in Economics, and professor at INSEAD and the Collège de France. He applies insights on innovation-driven growth and creative destruction to model the long-term macroeconomic trajectory of AI.

• Ajay Agrawal (Visiting Fellow): Professor at the Rotman School of Management, University of Toronto, conducting research on the economics of AI, scientific discovery, and its integration with robotics.

• Anu Madgavkar (Director)Former Partner at the McKinsey Global Institute (MGI). With a 20-year career in labor markets and technology adoption, she leads empirical research on global AI diffusion, small and medium-sized enterprise ecosystems, and the labor impacts of generative AI.

• Daniel Rock (Director)Professor at the Wharton School of the University of Pennsylvania. He conducts pioneering research on AI and labor, bridging frontier model telemetry and rigorous econometrics to analyze enterprise productivity and labor restructuring.

In addition, Alex Imas, Director of AGI Economics at Google DeepMind, and Zanna Iscenko of the Chief Economist Office are co-driving the program.

5. Verification Methods for the Scientific Approach

The procedures and verification points for accessing research findings and data from this program are as follows.

• Verification Procedure:

  1. Visit the official overview page, Google AI Economy.

  2. Review data on usage patterns of AI tools in work and daily life through the interactive open-access site of ATLAS v1.0.

  3. Read published research papers and the latest publications from the directors to understand use cases in policy formulation and workforce training.

• Available Information:

  • Global AI adoption data

  • Trends in empirical research regarding labor markets and small business ecosystems

  • Recommendations on organizational best practices and public policy frameworks

6. Limitations of This Initiative

• Out of Scope for Hardware Verification: This article organizes the public organizational structure and research program framework, and does not execute or verify economic model simulations or proprietary data econometric analysis.

• Tracking Dynamic Changes: Because technology adoption and economic impacts unfold in real time, data or models from a specific point in time cannot fully predict all future labor market changes.

7. Summary

Based on primary sources, this article outlines the expansion of Google's AI & Economy Research Program and provides an overview of its economic approach. The items to check and constraints before execution are as follows.

• The roles of the organizations and experts listed are based on the official blog and are subject to update depending on the environment and future program developments.

• To evaluate the impact of AI on employment and productivity from multiple perspectives, continuous review of public data beyond a single announcement is essential.

• For data details and to use the latest interactive site, always refer directly to the official information (Google AI Economy).

References

• source_title: New experts join Google’s AI & Economy team

• source_url: https://blog.google/innovation-and-ai/technology/ai/expanding-ai-economy-research-bench/