This would increase the impact of all artificial intelligence by 15 to 40 percent. Our latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases we analyzed-by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. Generative AI’s impact on productivity could add trillions of dollars in value to the global economy. The following sections share our initial findings.įor the full version of this report, download the PDF. In the process, it could unlock trillions of dollars in value across sectors from banking to life sciences. It suggests that generative AI is poised to transform roles and boost performance across functions such as sales and marketing, customer operations, and software development. This research is the latest in our efforts to assess the impact of this new era of AI. AI trained on these models can perform several functions it can classify, edit, summarize, answer questions, and draft new content, among other tasks.Īll of us are at the beginning of a journey to understand generative AI’s power, reach, and capabilities. Unlike previous deep learning models, they can process extremely large and varied sets of unstructured data and perform more than one task.įoundation models have enabled new capabilities and vastly improved existing ones across a broad range of modalities, including images, video, audio, and computer code. Deep learning has powered many of the recent advances in AI, but the foundation models powering generative AI applications are a step-change evolution within deep learning. Foundation models are part of what is called deep learning, a term that alludes to the many deep layers within neural networks. These models contain expansive artificial neural networks inspired by the billions of neurons connected in the human brain. For the purposes of this report, we define generative AI as applications typically built using foundation models. To grasp what lies ahead requires an understanding of the breakthroughs that have enabled the rise of generative AI, which were decades in the making. 3 Emma Roth, “The nine biggest announcements from Google I/O 2023,” The Verge, May 10, 2023. And in May 2023, Google announced several new features powered by generative AI, including Search Generative Experience and a new LLM called PaLM 2 that will power its Bard chatbot, among other Google products. 2 “Introducing Claude,” Anthropic PBC, Ma“Introducing 100K Context Windows,” Anthropic PBC, May 11, 2023. Similarly, by May 2023, Anthropic’s generative AI, Claude, was able to process 100,000 tokens of text, equal to about 75,000 words in a minute-the length of the average novel-compared with roughly 9,000 tokens when it was introduced in March 2023. 1 “Introducing ChatGPT,” OpenAI, Novem“GPT-4 is OpenAI’s most advanced system, producing safer and more useful responses,” OpenAI, accessed June 1, 2023. Four months later, OpenAI released a new large language model, or LLM, called GPT-4 with markedly improved capabilities. The speed at which generative AI technology is developing isn’t making this task any easier. This article is a collaborative effort by Michael Chui, Eric Hazan, Roger Roberts, Alex Singla, Kate Smaje, Alex Sukharevsky, Lareina Yee, and Rodney Zemmel, representing views from QuantumBlack, AI by McKinsey McKinsey Digital the McKinsey Technology Council the McKinsey Global Institute and McKinsey’s Growth, Marketing & Sales Practice. As a result, a broader set of stakeholders are grappling with generative AI’s impact on business and society but without much context to help them make sense of it. But it is their ability to write text, compose music, and create digital art that has garnered headlines and persuaded consumers and households to experiment on their own. The latest generative AI applications can perform a range of routine tasks, such as the reorganization and classification of data. Generative AI applications such as ChatGPT, GitHub Copilot, Stable Diffusion, and others have captured the imagination of people around the world in a way AlphaGo did not, thanks to their broad utility-almost anyone can use them to communicate and create-and preternatural ability to have a conversation with a user. Clear milestones, such as when AlphaGo, an AI-based program developed by DeepMind, defeated a world champion Go player in 2016, were celebrated but then quickly faded from the public’s consciousness. As a result, its progress has been almost imperceptible. The economic potential of generative AI: The next productivity frontier (68 pages)ĪI has permeated our lives incrementally, through everything from the tech powering our smartphones to autonomous-driving features on cars to the tools retailers use to surprise and delight consumers.
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