Generative AI could add up to $4.4 trillion a year to global economy: McKinsey

McKinsey's latest report on the technology adds that half of current work activities will be automated between 2030 and 2060

Varsha Meghani
Published: Jun 27, 2023 02:51:25 PM IST
Updated: Jun 27, 2023 03:02:31 PM IST

The report estimates that 50 percent of today’s work activities will be automated between 2030 and 2060, with a midpoint in 2045
Image: ShutterstockThe report estimates that 50 percent of today’s work activities will be automated between 2030 and 2060, with a midpoint in 2045 Image: Shutterstock

The latest wave of artificial intelligence (AI) technology has transfixed the world with its ability to write text, create images and crunch health data. Generative AI is behind applications like ChatGPT, and even as consumers experiment with it, others are grappling with the impact the technology can have on jobs, businesses, and society at large.

Consulting firm McKinsey has put together a report outlining the economic potential of generative AI. Here are the key takeaways from it:

Generative AI’s impact on productivity could add $2.6 trillion to $4.4 trillion annually to the global economy.

For perspective, the UK’s GDP in 2021 was $3.1 trillion. In effect, McKinsey says that the value generative AI could add to the global economy is close to the economic equivalent of adding an entire new country of the same size and productivity as the UK.

To come up with its findings, McKinsey examined 850 occupations and 2,100 detailed work activities across 47 countries, representing more than 80 percent of the global workforce.

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About 75 percent of the value generative AI can deliver will come from four areas: Customer operations, marketing and sales, software engineering, and R&D.

McKinsey examined 63 use cases across 16 business functions in which generative AI can address specific business challenges. The areas in which one or more measurable outcomes were seen include the technology’s ability to support customer interactions, generate creative content for marketing and sales, draft computer code and assistance in crunching data for R&D. As a result, the industry sectors most impacted by generative AI include banking, high-tech and life sciences, the report says.

Also read: Don't fear bots, just don't write like them

Generative AI has the potential to automate work activities that absorb 60 to 70 percent of employees’ time today.

Knowledge work, especially decision-making and collaboration, which was previously considered less suitable for automation will be most impacted by generative AI, according to the report. While traditional technology automation has thus far focussed on mundane tasks and physical activities, generative AI will automate cognitive tasks such as writing copy or creating images. The report estimates that 50 percent of today’s work activities will be automated between 2030 and 2060, with a midpoint in 2045, or roughly a decade earlier than McKinsey’s previous estimates connected with general AI, robotics and automation.

So, does this mean massive job losses are inevitable? Not according to the authors of the report who say that jobs will be faster to perform and will also be performed more precisely, thanks to generative AI. That translates to an addition of 0.2 to 3.3 percentage points annually to productivity growth to the entire global economy, notes the report.

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

Also read: Navigating through the ethos and sophistication of Generative AI

The era of generative AI is just beginning, and while the technology shows promise, challenges related to risk management, workforce skills, and business processes remain to be addressed.

Even as advances in generative AI lay the foundation for a new technological era, leaders in business and society have considerable challenges to address. These include managing human job losses, containing the proliferation of misinformation, overcoming biases and ensuring data protection.


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