The Economic Potential of Generative AI: Interpretation of McKinsey's Latest Report

McKinsey's latest report offers a very optimistic forecast for the development of generative AI. The core conclusion of the report is that AI will reach human-level capabilities faster than expected, likely by 2030. This prediction is much more optimistic than the expectations from 2017.

The report points out that AI technology has widely infiltrated every aspect of our lives. Unlike in 2016 when AlphaGo defeated Lee Sedol and AI was limited to Go, this year generative AI products like ChatGPT, Copilot, and Stable Diffusion have swept into our daily lives. These AI tools have become productivity tools accessible to everyone, which can be used for creation, drawing, making PPTs, and various other scenarios.

The performance of ChatGPT powered by GPT-4 has significantly improved, and Anthropic's Claude has also seen a tenfold increase in processing speed. The report highlights the rapid development trend of AI in just a few months.

The report defines generative AI as applications built on large language models. These models have gained new capabilities in various fields such as images, videos, audio, and code, and the performance of existing functionalities has also seen significant improvements. However, the report believes that our understanding of the capabilities of generative AI is still in its infancy.

McKinsey analyzed the economic impact of generative AI from two perspectives:

1. Analysis of application scenarios for enterprises. The report identifies 63 generative AI use cases covering 16 business functions. If widely adopted, it could bring annual economic benefits ranging from $2.6 trillion to $4.4 trillion. This is 15%-40% higher than the predictions made in 2017.

2. Analysis of the impact on occupations. The report analyzes the potential impact of generative AI on approximately 850 occupations and simulates the timeline for AI to perform over 2,100 job tasks.

Considering these two perspectives, the report estimates that the total economic benefit of generative AI could reach between 61,000 to 79,000 USD annually.

In different business functions, customer operations, marketing and sales, software engineering, and research and development account for 75% of the total value of generative AI use cases. In contrast, the potential value in areas such as manufacturing and supply chain is lower.

Generative AI can also bring value to the entire company by improving enterprise knowledge management systems. Its natural language processing capabilities can help employees more easily retrieve internal company knowledge, thereby improving decision-making efficiency.

The impact of generative AI varies across different industries. For example, the retail sector could gain an additional value of about $310 billion by improving marketing and customer operations. The value in the high-tech industry mainly comes from increasing software development efficiency.

The report expects that with the rapid development of AI capabilities, these figures will continue to grow in the future. Compared to the predictions made in 2017, the latest report is more optimistic about the speed of AI development. For example, the time for AI to reach human-level natural language understanding has been brought forward from 2027 to 2023.

Reports estimate that the total potential of technological automation has increased from about 50% to 60-70%. The impact of generative AI on knowledge work could be the greatest, especially in activities like decision-making and collaboration, which previously had lower automation potential.

In the face of these changes, the report suggests that business leaders consider how to leverage the potential value of generative AI while managing risks, government policymakers need to formulate appropriate labor policies, and everyone also needs to think about how to strike a balance between the conveniences and impacts brought by AI.

Overall, this report provides a comprehensive analysis of the significant impact of the generative AI explosion on society, especially in economic terms, presenting a future scenario where AI rapidly develops and profoundly transforms society.