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How can leaders effectively scale generative AI?

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Dealing with data to scale gen AI

In the news

•

Better financial performance. Many business leaders who are working with AI, including generative AI (gen AI), are discovering that the maturity of their companies’ data strategies is crucial in creating value from the technologies, Fast Company reports. A survey of more than 2,300 small and medium-size businesses around the world finds that companies that have in-house data analysis capabilities are much more likely to be adopting AI and experiencing better financial outcomes than their peers. [Fast Company]

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Leaping ahead in gen AI. In the race to implement gen AI within companies, one country—China—is currently ahead, Fortune states. A survey of 1,600 organizations reveals that about 80% of Chinese enterprises have already adopted gen AI in their business processes, compared with 65% of US companies and 54% of global peers. Innovating with gen AI could give China a competitive edge in using AI platforms to glean insights from data. [Fortune]

Data and AI leaders are starting to build data pipelines by automating all the steps, achieving, in some cases, time savings of 80 to 90%.

On McKinsey.com

•

Difficulties with data. Data and AI leaders have been working feverishly on gen AI use cases for more than a year. There’s considerable value at stake and also some challenges in getting to scale, particularly with managing data. (Managing data remains one of the main barriers to value creation from gen AI.) In fact, 70% of top performers in a recent McKinsey survey say that they have encountered difficulties integrating data into AI models, McKinsey senior partner Kayvaun Rowshankish and coauthors explain.

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Improving data quality. While data quality has long been a key concern, feeding poor data into gen AI models can result in costly fixes, cyber breaches, and a loss of user trust in the outputs. The McKinsey survey finds that 63% of respondents say that output inaccuracy is the greatest risk they see in their organizations’ use of gen AI. Consider three actions that can help data and AI leaders move from gen AI pilots to scaling data solutions.

See our guide to scaling gen AI

—Edited by Belinda Yu, editor, Atlanta

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by "Only McKinsey" <publishing@email.mckinsey.com> - 11:08 - 22 Jul 2024

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See you at Black Hat, Las Vegas, on August 6! 👋

How Stripe Scaled to 5 Million Database Queries Per Second

How can leaders effectively scale generative AI?

Dealing with data to scale gen AI

In the news

Data and AI leaders are starting to build data pipelines by automating all the steps, achieving, in some cases, time savings of 80 to 90%.

On McKinsey.com

Archives

in

info@learn.odoo.com

See you at Black Hat, Las Vegas, on August 6! 👋

How Stripe Scaled to 5 Million Database Queries Per Second

How can leaders effectively scale generative AI?

Dealing with data to scale gen AI

In the news

Data and AI leaders are starting to build data pipelines by automating all the steps, achieving, in some cases, time savings of 80 to 90%.﻿

On McKinsey.com

Data and AI leaders are starting to build data pipelines by automating all the steps, achieving, in some cases, time savings of 80 to 90%.