“Generative AI is redefining the frontiers of creativity and innovation, becoming a milestone in technological progress.”

Marcio Sampaio

Generative Artificial Intelligence

Generative AI is poised to unleash the next wave of productivity. We take a first look at where business value could accrue and the potential impacts on the workforce.

AI has gradually permeated our lives, through everything from the technology powering our smartphones to the autonomous driving features in cars and the tools retailers use to surprise and delight consumers. As a result, its progress has been almost imperceptible. Clear milestones, such as when AlphaGo, an AI-based program developed by DeepMind, defeated a world Go champion in 2016, were celebrated but quickly faded from public consciousness.

Generative AI applications like ChatGPT, GitHub Copilot, Stable Diffusion, and others have captured people's imagination around the world in a way that AlphaGo did not, thanks to their broad utility - almost anyone can use them to communicate and create - and the supernatural ability to have a conversation with a user. The latest generative AI applications can perform a range of routine tasks such as data reorganization and classification. But it's their ability to write text, compose music, and create digital art that has grabbed headlines and persuaded consumers and families to try them out for themselves. As a result, a broader set of stakeholders is grappling with the impact of generative AI on business and society, but without much context to help make sense of it.

The speed at which generative AI technology is developing doesn't make this task any easier. ChatGPT was launched in November 2022. Four months later, OpenAI released a new large language model, or LLM, called GPT-4 with notably improved capabilities. Similarly, by May 2023, Anthropic's generative AI, Claude, was able to process 100,000 text tokens, equivalent to about 75,000 words in a minute - the length of the average novel - compared to about 9,000 tokens when it was introduced in March 2023. And in May 2023, Google announced several new generative AI-powered features, including the Search Generative Experience and a new LLM called PaLM 2 that will power its chatbot Bard, among other Google products.

To understand what's to come, one must understand the advances that have made generative AI possible, which have been decades in the making. For the purposes of this report, we define generative AI as applications typically built using base models. These models contain extensive artificial neural networks inspired by the billions of interconnected neurons in the human brain. Base models are part of what's called deep learning, a term that alludes to the many deep layers within neural networks. Deep learning has powered many recent AI advances, but the base models that power generative AI applications are a radical evolution within deep learning. Unlike previous deep learning models, they can process extremely large and varied unstructured datasets and perform more than one task.

Base models have enabled new capabilities and greatly improved existing ones across a wide range of modalities, including images, video, audio, and computer code. AI trained on these models can perform various functions; it can classify, edit, summarize, answer questions, and generate new content, among other tasks.

We are all at the beginning of a journey to understand the power, reach, and capabilities of generative AI. This research is the latest in our efforts to assess the impact of this new era of AI. It suggests that generative AI is poised to transform roles and enhance performance in functions like sales and marketing, customer operations, and software development. In the process, it could unlock trillions of dollars in value across industries ranging from banking to life sciences. The following sections share our initial findings.