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ON CREATING SUSTAINABLE AND INCLUSIVE GROWTH

This week’s headline findings

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Poor-quality data can lead to inaccurate outputs, costly fixes, and a loss of user trust. Organizations struggle to process unstructured data sets, and that increases the chance of errors. In a recent McKinsey survey, 70 percent of top performers said they had difficulties integrating data into AI models. Senior partner Kayvaun Rowshankish and coauthors say moves that can help organizations remedy these problems, and scale generative AI (gen AI), include improving the quality and readiness of data for gen AI use cases; utilizing gen AI to build better data products, such as a 360-degree view of a customer; and safeguarding data at every step to mitigate risk and maintain high standards.

Productivity has slowed over the past decade or so, but AI could be a game changer in reviving it, Chad Syverson, an economist at the University of Chicago Booth School of Business, explains in an episode of the McKinsey Global Institute’s Forward Thinking podcast. Why does the slowdown matter? Because if productivity growth had remained high, US GDP would be up roughly 35 percent from current levels, Syverson says. But there are glimmers of a potential turnaround: since the end of the COVID-19 pandemic, labor market dynamism and business formation have picked up, and Syverson says optimism about new technologies such as AI and biotech could be part of the reason.

The world needs to shift its thinking on populations getting older, moving from the idea of an aging society to that of a longevity society, economist, author, and longevity expert Andrew J. Scott tells Ellen Feehan, a McKinsey partner and coleader of the McKinsey Health Institute’s healthy longevity team. Remarkably, in high-income countries, half of all children are likely to live into their late 80s or early 90s—but it’s important to make sure people remain productive and engaged as they age, Scott says. Businesses should recognize older workers as important contributors and find ways to retain them, a strategy that will yield benefits for the whole company, he explains. People also should strive to keep their biological age as low as possible by living a full, healthy life, no matter their chronological age. 

OTHER FINDINGS OF NOTE

WHAT WE’RE READING

A recent edition of Author Talks, currently exclusive to the McKinsey Insights app, features Aram Sinnreich discussing the new book he cowrote with Jesse Gilbert, The Secret Life of Data: Navigating Hype and Uncertainty in the Age of Algorithmic Surveillance (MIT Press, April 2024). Sinnreich, a professor at American University, explains one of the book’s central tenets: data is not inherently neutral or objective, as all data systems contain flaws or biases. Data surveillance, AI, and algorithms are taking on ever more importance, with potentially ominous implications. The interviews and research got so heavy that he and his coauthor “experienced depression and paranoia,” Sinnreich says—but they came out of the process optimistic about humanity’s resilience in a data-obsessed world.

The case study collection Rewired in Action illuminates companies that have launched digital transformations to build value. Supported by technical and industry expertise from McKinsey, these organizations have changed their trajectories through the integration of digital and AI.

— Edited by Jana Zabkova, senior editor, New York

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