The Economic Potential of Generative AI│Vinayak HV (McKinsey&Company, Senior Partner)

The latest generative AI applications can perform a range of routine tasks, such as the reorganization and classification of data. 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. 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.
Generative AI can create value in a wide range of use cases. While the tech industry is brimming with excitement and anticipation, CEOs are wondering how they can integrate AI tools into business strategies and processes. We believe it is an ideal time to discuss the relevance of the topic and offer a generative AI primer to help executives better understand the fast-evolving state of AI and the technical options available.
With proper guardrails in place, generative AI can not only unlock novel use cases for businesses but also speed up, scale, or otherwise improve existing ones. Generative AI’s potential in R&D is perhaps less well recognized than its potential in other business functions. Still, our research indicates the technology could deliver productivity with a value ranging from 10 to 15 percent of overall R&D costs. Software engineering is a significant function in most companies, and it continues to grow as all large companies, not just tech titans, embed software in a wide array of products and services. According to our analysis, the direct impact of AI on the productivity of software engineering could range from 20 to 45 percent of current annual spending on the function.
Businesses have been pursuing AI ambitions for years, and many have realized new revenue streams, product improvements, and operational efficiencies. Much of the successes in these areas have stemmed from AI technologies that remain the best tool for a particular job, and businesses should continue scaling such efforts. However, generative AI represents another promising leap forward and a world of new possibilities. While the technology’s operational and risk scaffolding is still being built, business leaders know they should embark on the generative AI journey.
But where and how should they start? The answer will vary from company to company as well as within an organization. Some will start big; others may undertake smaller experiments. The best approach will depend on a company’s aspiration and risk appetite. Whatever the ambition, the key is to get under way and learn by doing. #ai #chatgpt #generativeai

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