The impact of the widespread adoption of generative AI tools by large companies on the economy is a topic of interest. McKinsey and Company, a global consulting leader, has attempted to quantify this impact in a new report titled “The economic potential of generative AI.” The report suggests that generative AI (GenAI) could add anywhere from $2.6 trillion to $4.4 trillion annually to the global economy, which is equivalent to adding a country the size and productivity of the United Kingdom to the Earth.
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To construct the report, McKinsey’s analysts examined 850 occupations and 2,100 detailed work activities across 47 countries, representing over 80% of the global workforce. The estimated economic impact of GenAI represents a significant increase from McKinsey’s previous estimates in 2017, indicating a fast embrace and potential use cases of GenAI tools by enterprises of all sizes.
Furthermore, McKinsey finds “current generative AI and other technologies have the potential to automate work activities that absorb 60 to 70% of employees’ time today.”
What about job losses?
However, McKinsey’s report suggests that massive job loss is not inevitable. Instead, GenAI has the potential to make jobs more efficient and precise, adding 0.2 to 3.3 percentage points annually to productivity growth in the global economy. Workers will need support in learning new skills, and some may need to change occupations. If worker transitions and other risks can be managed, generative AI could contribute substantively to economic growth and foster a more sustainable and inclusive world.
McKinsey believes that while generative AI has captured public interest, other AI applications and technologies will also play a significant role in reshaping the global economy. Generative AI and large language models (LLMs) are well-suited for white-collar knowledge worker roles and tasks, while general AI, robotics, and automation technologies may be more suitable for physical tasks in fields such as manufacturing, construction, engineering, transportation, mining, and search and rescue.
The advent of accessible GenAI has pushed up McKinsey’s previous estimates for workplace automation: “Half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045, or roughly a decade earlier than in our previous estimates.”
The report highlights that generative AI and AI technologies can augment various tasks and jobs rather than replace them. New tasks and jobs will be created, and industries may undergo readjustments. McKinsey’s report identifies customer operations, marketing and sales, software engineering, and R&D as areas where generative AI is likely to have a significant impact.
Generative AI and the large language models (LLM) at the center of the uptake of this technology are well-suited for certain kinds of white-collar, so-called “knowledge worker” roles and tasks, as opposed to general AI, robotics, and automation technologies, which may be more useful for more physical tasks such as manufacturing, construction, engineering, transportation, mining and search and rescue.
Regarding customer operations, McKinsey noted that their “research indicated that nearly half of customer engagements in banking, telecommunications, and utilities sectors in North America are already handled by machines, including but not limited to AI. Depending on the level of automation already in place, we estimate that generative AI could further decrease the volume of human-assisted interactions by up to 50%.”
Bigger impact faster than we think
In customer operations, generative AI can reduce human-serviced contacts by up to 50%, depending on the level of existing automation. In marketing and sales, it can increase productivity by 5-15% of total marketing spending and 3-5% of sales spending globally. In software engineering, generative AI can increase productivity by 20-45% on software spending by automating tasks like code generation, correction, and system design. In R&D, generative AI can help reduce costs by optimizing designs, material selection, and manufacturing processes.
Overall, McKinsey sees generative AI as a “technology catalyst” that pushes industries further along their automation journeys while unlocking the creative potential of employees. It suggests that we are entering an age of creativity and creation, where AI tools can support and enhance human capabilities.
It’s important to note that while AI was used to analyze and fetch data for the report, the entire report itself was written by human authors.