McKinsey: Gen AI could add $4.4 trillion annually to the global economy

It seems that the leadership of almost every major company today is excited about Generative AI and rushing to announce or embrace new AI tools. But what impact will their moves have on the economy?

While it’s hard to say for sure, global consulting firm McKinsey and Company – where GenAI is already used by about half of the workforce – has tried to quantify the trend in a new report, The economic potential of generative AI.

The report finds that GenAI could add “$2.6 trillion to $4.4 trillion annually” to the global economy, close to the economic equivalent of adding a whole new country the size and productivity of the United Kingdom to the Earth ($3.1 trillion GDP in 2021).

To compile the report, McKinsey analysts examined 850 occupations and 2,100 detailed occupations in 47 countries, representing more than 80% of the global workforce.

A greater impact on an accelerated timeline

The $2.6 trillion to $4.4 trillion economic impact figure marks a huge increase over McKinsey’s previous estimates of the AI ​​field’s impact on the economy as of 2017, a 15 to 40% increase over before . This upward revision is due to the incredibly rapid adoption and potential use cases of GenAI tools by enterprises large and small.

In addition, McKinsey believes that “current generative AI and other technologies have the potential to automate work activities that today take up 60 to 70% of employees’ time.”

Does this mean massive job losses are inevitable? No, according to Alex Sukharevsky, senior partner and global leader of QuantumBlack, McKinsey’s internal AI division and co-author of the report.

“You could actually make it significantly faster to do these tasks and do so much more accurately than they are done today,” Sukharevsky told VentureBeat.

That translates to adding “0.2 to 3.3 percentage points per year in productivity growth” to the entire global economy, he said.

However, as the report notes, “Employees will need support in learning new skills, and some will change occupations. If employee transitions and other risks can be managed, generative AI can substantially contribute to economic growth and support a more sustainable, inclusive world.”

Also, the advent of accessible GenAI has boosted McKinsey’s previous estimates for workplace automation: “Half of current work activities could be automated between 2030 and 2060, with a midpoint in 2045, or about a decade earlier than our previous estimates.”

Jobs and tasks are most likely being automated by generative AI and AI in general

While generative AI has captured the public eye and imagination, McKinsey believes other AI applications and technologies will also play an important role in reshaping the global economy.

“When people talk about GenAI these days, they sometimes think of it as something interchangeable with AI and robotics, but it’s important to be precise,” Sukharevsky said.

That’s because generative AI and the large language models (LLM) that are central to the adoption of this technology are well suited to certain types of white-collar roles and tasks, so-called “knowledge workers”, as opposed to general AI, robotics and automation technologies, which can be more useful for more physical tasks such as manufacturing, construction, engineering, transportation, mining, and search and rescue.

The former is already there and is disrupting the workforce of the white-collar workers, while the latter is also there, but takes longer to deploy due to the physical machines required, and is likely to have longer-term impacts later, especially with projections that much of the current workforce will age over the next half century and there will not be enough younger people to replace them.

“How do you make a better work of art? How do you write a better book? How do you make a better movie? How do you actually create the solution for the world to recover from the worst natural disasters?” Sukharevsky asked rhetorically, citing some examples of tasks that could be “amplified” by all kinds of AI.

“Many new tasks and jobs will emerge,” he continued. “In the short term we clearly see the smooth mechanics [for LLMs]but longer term, I think entire industries will be readjusted here.

Four tasks with the most added value

Specifically, McKinsey’s report found that four types of jobs—customer operations, marketing and sales, software engineering, and R&D—probably accounted for 75% of the added value of GenAI in particular.

“Examples include generative AI’s ability to support customer interactions, generate creative content for marketing and sales, and compile computer code based on natural language cues, among many other tasks.”

For customer operations, McKinsey said that “research has shown that about half of banking, telecommunications and utilities customer interactions in North America are already handled by machines, including but not exclusively AI. We estimate that generative AI can further reduce the number of human-operated contacts by up to 50%, depending on a company’s existing level of automation.”

For marketing and sales, McKinsey found that creating more personalized and intelligent content with GenAI “could increase marketing function productivity by between 5 and 15% of total marketing spend,” and sales spend productivity by 3 to 5% could increase. worldwide.

In software engineering, McKinsey sees the technology speed up the process of “initial code draft generation, code correction and refactoring, root-cause analysis, and new system design generation,” resulting in 20 to 45% higher productivity on software releases.

When it comes to R&D, McKinsey believes generative AI “will help product designers reduce costs by selecting and using materials more efficiently. It can also optimize designs for production, which can lead to cost savings in logistics and production.”

AI as a ‘technology catalyst’ for economic growth

Overall, McKinsey views GenAI as a “technology catalyst,” pushing industries further toward automation, but also unlocking the creative potential of workers.

“I do believe that we are at least entering the age of creativity and the age of the creator,” said Sukharevsky.

When asked what kinds of AI tools he used in particular, Sukharevsky declined to comment specifically, saying he enjoys testing out new ones almost every day.

He did confirm that while the data for the report was partially analyzed and extracted by AI, the full 2023 McKinsey report on the economic impact of AI was written by human authors.