McKinsey released： The Economic Potential of Generative Artificial Intelligence： The Next Wave of Productivity.

(1) Generative AI may contribute "one British GDP" to the global economy every year.

McKinsey pointed out that if the 63 kinds of generative AI analyzed are applied to all walks of life, it will bring about an annual growth of 2.6 trillion to 4.4 trillion US dollars for the global economy (the total GDP of the UK in 2021 is 3.1 trillion US dollars). This forecast has not counted all the applications of generative AI. If the applications that have not been studied are counted, the economic impact of generative AI may double.

Figure 1 Potential impact of generative AI on the global economy

(2) The potential value of generative AI (about 75%) is mainly concentrated in four aspects: customer operation, marketing and sales, software engineering and product research and development, which means that the above four businesses are most affected by generative AI.

Figure 2 Influence of Generative AI on Different Services

(1) customer operation: improve customer experience and enhance customer service productivity.

Generative AI may completely change the whole customer operation business and improve customer experience and customer service productivity through digital self-service. Because this technology can automatically interact with customers using natural language, it has attracted much attention in the field of customer service. It is found that in a company with 5,000 customer service staff, the application of generative AI improves the hourly problem solving rate by 14%, and reduces the time spent dealing with problems by 9%. It also reduced the turnover rate of customer service seats by 25%. Crucially, generative AI can improve the productivity and service quality of inexperienced customer service staff, while AI assistants do not improve (sometimes even reduce) the productivity and quality index of highly skilled customer service staff.Application scenarios for using generative AI to improve operations include:

McKinsey estimates that applying generative AI to customer service business can improve productivity and save 30% to 45% of current business costs.

(2) Marketing and sales: improve the efficiency of personalization, content creation and sales.

Generative AI will quickly dominate the marketing and sales business. This technology can create personalized messages according to customers’ interests, preferences and behaviors, and perform tasks such as making the first draft of brand advertisements, headlines, slogans, social media posts and product descriptions. In addition, generative AI can be integrated into various applications to provide higher quality data insight, bring new ideas to marketing activities and better locate customer groups. Marketing departments can allocate funds to producing higher quality content and reduce outsourcing expenses.The potential operational advantages of using generative AI for marketing include:

McKinsey estimates that generative AI can increase the economic value of marketing productivity by 5% to 15%. In addition, in addition to having a direct impact on marketing productivity, generative AI will also have a chain reaction, which will increase sales productivity by 3% to 5%.

(3) Software engineering: as a coding assistant to speed up the work of developers.

(4) product research and development: reduce research and design time and improve product simulation and testing.

It is found that generative AI can increase the productivity of product development by 10% to 15%. Taking life science and chemical industry as an example, generative AI can accelerate the process of developing new drugs and materials, which may increase the profits of pharmaceutical companies and medical products companies by as much as 25%.McKinsey believes that generative AI can speed up the time to market of products, and bring productivity improvement and operational convenience from the following two aspects:

Generative AI will have a great impact on all walks of life. Among them, the retail and consumer goods, banking, pharmaceutical and medical industries are the most affected.

Figure 3 Generative AI applications have different impacts on business functions in all walks of life.

(1) Generative AI is a key element driven by the value of retail and consumer goods.

Generative AI can increase productivity by 1.2% to 2.0% and create economic value of 400 billion to 660 billion US dollars every year. In order to simplify the process, generative AI can automate key businesses such as customer service, marketing and sales, inventory and supply chain management.The following are the applications of generative AI in retail and consumer goods:

(2) Generative AI helps the banking industry realize great value.

Generative AI may have a major impact on the banking industry. By increasing productivity by 2.8% to 4.7%, it can create economic value of 200 billion to 340 billion US dollars every year.The following is the application of generative AI in banking:

(3) Productive AI improves the speed and quality of pharmaceutical and medical research and development.

Productive AI can increase the productivity of pharmaceutical and medical care by 2.6% to 4.5%, and create economic value of 60 billion to 110 billion US dollars every year. Pharmaceutical companies usually spend about 20% of their income on research and development, and the research and development of a new drug takes an average of 10 to 15 years. Generative AI can greatly improve the speed and quality of pharmaceutical and medical research and development.The following are the applications of generative AI in pharmaceutical and medical fields:

(A) the development of generative AI and other technologies may make employees60 to 70%Work is automated.

Generative AI may change the work structure, and enhance the individual ability of employees by automating some work activities. The accelerated growth of Technical automation is largely due to the fact that generative AI has improved the ability to understand natural languages. For example, the specific work of middle school English or Chinese teachers includes preparing tests and correcting students’ homework. With the enhancement of AI’s ability in natural language, many of these activities can be done by machines, so that these teachers can spare more time for other jobs.

Figure 4 Potential level of automation of production AI technology

(2) The time when production AI replaces human work has been advanced by 10 years, and 50% of occupations will be gradually replaced by AI between 2030 and 2060 (the midpoint is 2045).

Fig. 5 The global automation level of the time spent in human work activities at present.

(3) Developed countries may adopt automation faster.

Due to the higher salary of employees in developed countries, the economic feasibility of adopting generative AI to realize automation will appear earlier. Although generative AI has great potential to automate specific work activities, the cost must also be compared with the labor compensation cost. In countries with low salaries such as China, Indian and Mexican, the adoption rate of automation is expected to be slower than that of developed countries.

Figure 6 automation adoption rate in some countries

(D) Compared with other types of jobs, generative AI has a greater impact on highly paid and highly educated knowledge workers.

It is not surprising that generative AI has a strong natural language ability, so its influence on manual workers is much less, because the function of generative AI is basically designed to complete cognitive tasks. It is found that generative AI has a greater impact on high-paid and highly educated knowledge workers, especially those activities involving decision-making, collaboration and application of professional knowledge. Therefore, many work activities involving communication, supervision, recording and interaction with people may be automated through generative AI, thus accelerating the transformation of professional work such as education and technology.

Fig. 7 The influence of generative AI on people with different salary levels in some countries

Fig. 8 Influence of Generative AI on People with Different Educational Levels

Fig. 9 Influence of Generative AI on Different Work Activities

(5) By 2040, productive AI can increase labor productivity by 0.1% to 0.6% every year.

Generative AI can greatly improve the labor productivity of the whole economy, but it requires funds to support employees to change their work activities. Combining generative AI with other technologies can increase productivity by 0.2% to 3.3% every year. However, employees need training when learning new skills, and some even change their careers. If employee transition and other risks can be managed, generative AI will make substantial contributions to economic growth and make the world more sustainable and inclusive.

Fig. 10 Influence of generative AI on global and some countries’ productivity