Generative AI Could Raise Global GDP by 7%

It submits that generative AI is poised to transform roles and boost performance across functions such as sales and marketing, customer operations, and software development. In the process, it could unlock trillions of dollars in value across sectors from banking to life sciences. Generative AI–fueled chatbots can give immediate and personalized responses to complex customer inquiries regardless of the language or location of the customer.

This implies that more than 85% of employment growth over the last 80 years is explained by the technology-driven creation of new positions, our economists write. A report by McKinsey & Company found that AI could automate up to 45% of the tasks currently performed by retail, hospitality, and healthcare workers. While this could lead to job displacement, the report also noted that just because AI could automate a job doesn’t necessarily mean that it will, as cost, regulations, and social acceptance can also be limiting factors.

Will Generative AI Eliminate Jobs or Create Jobs?

Now, it’s fascinating to see how our initial ideas have merged into this larger wave of technological change. In this article, I share insights from this journey, highlighting both challenges and unexpected developments. The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over.

The speed with which this technology can create content can help employees develop more content in less time and/or work more efficiently. This can reduce the need for human labor, raising concerns about the economic potential of generative ai job displacement and income inequality. Generative AI (Gen AI) is a type of artificial intelligence designed to generate new content without human intervention, such as text, images, and even music.

How we projected the value potential of generative AI use cases

▶ State of Space-Based Solar Radiation Management – Planetary Sunshade Foundation | Placing a physical structure, a planetary sunshade, between the Sun and the Earth can reduce solar energy and provide a long-term, sustainable wind-down from SAI. While SAI can be deployed quickly and inexpensively, it must be replenished constantly and maintained until carbon is removed from the atmosphere. On the other hand, deploying the sunshade will take longer and cost more, but it is a cleaner, more sustainable proposal. The sunshade also has many positive benefits beyond addressing climate change that should be understood by policy makers.

Goldman Sachs estimates that generative AI could automate tasks that take up to one-fourth of employees’ time today. These assessments have sparked concerns about job displacement and an uncertain future of work. Traditional models have been trained on smaller, specialized datasets to serve a specific purpose (e.g., analyze previous machine maintenance patterns to predict when servicing is necessary). Generative AI models are trained on large databases, such as the entire publicly available internet, and so can serve a much wider range and versatility of use cases. Has the potential to change the anatomy of work, augmenting the capabilities of individual workers by automating some of their individual activities,” the report said.

As tools using advances in natural language processing work their way into businesses and society, they could drive a 7% (or almost $7 trillion) increase in global GDP and lift productivity growth by 1.5 percentage points over a 10-year period. Our analysis finds that generative AI could have a significant impact on the pharmaceutical and medical-product industries—from 2.6 to 4.5 percent of annual revenues across the pharmaceutical and medical-product industries, or $60 billion to $110 billion annually. This big potential reflects the resource-intensive process of discovering new drug compounds.

• Our estimates are based on the structure of the global economy in 2022 and do not consider the value generative AI could create if it produced entirely new product or service categories.
• Documenting code functionality for maintainability (which considers how easily code can be improved) can be completed in half the time, writing new code in nearly half the time, and optimizing existing code (called code refactoring) in nearly two-thirds the time.
• The story told by the companies is of supplying “baseline” power in support of intermittent sources such as solar and wind—and doing so in a way that avoids the widespread public fear of an otherwise-obvious alternative, nuclear fission.
• Briggs also previously worked as an economist with the Vanguard Research Initiative and taught at Johns Hopkins University and New York University.
• Because of its ability to rapidly process data on customers and their browsing histories, the technology can identify product suggestions and deals tailored to customer preferences.

Lucia Rahilly is global editorial director and deputy publisher of McKinsey Global Publishing and is based in the New York office. And we’re going to spend more and more time thinking about how we’re going to make older workers productive. At the same time, how do we get those leaders who are providing mentorship and coaching back into the office? This research underlines the importance of a nuanced approach to implementing AI in business settings, especially in developing economies.

The Uneven Impact of Generative AI on Entrepreneurial Performance

No, according to Alex Sukharevsky, senior partner and global leader of QuantumBlack, McKinsey’s in-house AI division and report co-author. 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 an entire new country the size and productivity of the United Kingdom to the Earth ($3.1 trillion GDP in 2021). A new McKinsey survey shows that the vast majority of workers—in a variety of industries and geographic locations—have tried generative AI tools at least once, whether in or outside work. One surprising result is that baby boomers report using gen AI tools for work more than millennials. Our research found that marketing and sales leaders anticipated at least moderate impact from each gen AI use case we suggested. They were most enthusiastic about lead identification, marketing optimization, and personalized outreach.

In this visual Explainer, we’ve compiled all the answers we have so far—in 15 McKinsey charts. We expect this space to evolve rapidly and will continue to roll out our research as that happens. To stay up to date on this topic, register for our email alerts on “artificial intelligence” here. Artificial intelligence can solve many problems that humans can’t, such as traffic congestion, parking shortages, and long commutes.