The McKinsey and Company report describes updates to the automation adoption estimation process, a brief overview of the steps involved in assessing automation adoption, and methodology for estimating the impact of automation on work hours (FTEs, where one FTE equals 2,080 hours) and GDP.

The following is the summary of insights present in the report:

• There is the potential for generative AI to add trillions of dollars to the global economy through its impact on productivity. According to their newest analysis, generative AI may add the equivalent of $2.6 trillion to $4.4 trillion yearly across the 63 use cases they examined—by comparison, the United Kingdom's total GDP in 2021 was $3.1 trillion. It would boost the overall impact of artificial intelligence by 15 to 40%. This estimate nearly doubles when we consider the effect of embedding generative AI into software that is being utilised for activities other than those listed above.
• Customer operations, marketing and sales, software engineering, and R&D account for over 75% of the value that generative AI use cases might bring. We analysed 63 use cases across 16 business functions in which the technology can handle specific business difficulties in ways that result in one or more measurable outcomes. Among many other things, generative AI may enhance customer interactions, develop unique material for marketing and sales, and draught computer code based on natural-language cues.
• The impact of generative AI will be felt across all industry sectors. Banking, high technology, and life sciences are among the areas that could experience the most significant impact from generative AI in terms of income. If the use cases were completely implemented, the technology could provide an additional $200 billion to $340 billion in value to the banking industry. The potential impact on retail and consumer packaged products ranges from $400 billion to $660 billion annually.
• Generative AI can modify the anatomy of labour by augmenting individual individuals' capacities by automating some of their specific operations. Generative AI and other technologies can automate labour processes that currently use 60% to 70% of people's time. Previously, they calculated that technology can automate 50% of employees' time working. The growing ability of generative AI to understand natural language, which is essential for labour tasks that account for 25% of total work time, is mainly responsible for accelerating the potential for technological automation. As a result, generative AI has a more significant impact on knowledge employment linked with higher wage and educational requirements than on other forms of work.
• Given the increased potential for technical automation, workforce change is anticipated to accelerate. The improved adoption scenarios suggest that 50% of today's labour tasks might be automated between 2030 and 2060, with a midpoint in 2045, or approximately a decade earlier than their previous forecasts.
• While generative AI has the potential to boost labour productivity across the economy significantly, it will necessitate investments to support workers when they move to work activities or change occupations. Generative AI could enable yearly labour productivity gains of 0.1 to 0.6 per cent through 2040, depending on the technology adoption rate and redeployment of worker time into other tasks. When combined with all other technologies, work automation might bring 0.2 to 3.3 percentage points to annual productivity increase. However, workers will require assistance learning new skills, and some will change occupations. If labour transitions and other risks can be controlled, generative AI has the potential to significantly contribute to economic growth while also supporting a more sustainable, inclusive world.
• It's only the beginning of the age of generative AI. This technology has tangible excitement, and the initial pilots are impressive. However, corporate and societal leaders still face significant difficulties that must be addressed before the full benefits of the technology can be realised. 

For their comprehensive approach, McKinsey and Company recommend that readers consult the report's technical appendix.