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The state of AI in 2023: Generative AI’s breakout year | McKinsey
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class="mdc-o-container__wrapper mdc-u-spaced-mobile mdc-u-grid mdc-u-grid-gutter-xxl FullHero_mck-c-full-hero__title-container__YfybZ"><div class="mdc-u-grid mdc-u-grid-col-md-12"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11 mdc-u-spaced-mobile mdc-u-align-center mdc-u-grid"><div><h1 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-2 FullHero_mck-c-full-hero__heading__RgATx"><div>The state of AI in 2023: Generative AI’s breakout year</div></h1></div><div><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 FullHero_mck-c-full-hero__date__jb4gN"><div><time datetime="2023-08-01T00:00:00Z">August 1, 2023</time> | Survey</div></div></div><div><button data-component="mdc-c-button" aria-label="" type="button" id="button_id" class="mdc-c-button___U4iY2_2734c4f mdc-c-button--ghost mdc-c-button--size-medium FullHero_mck-c-full-hero__arrow__jtXdj" 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data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-5"><div class="mck-u-links-inline">As organizations rapidly deploy generative AI tools, survey respondents expect significant effects on their industries and workforces.</div></div></div></section><main data-layer-region="article-body" class="mdc-u-grid mdc-u-grid-gutter-xxl"><div class="mdc-u-grid mdc-u-grid-col-1 mdc-u-grid-col-md-12"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><div class="mdc-o-content-body mck-u-dropcap"><h4>You have reached a page with older survey data. Please see our 2024 survey results <span style="color:#2155ff"><a href="/capabilities/quantumblack/our-insights/the-state-of-ai">here</a></span>.</h4> <!-- --> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="DownloadsSidebar_mck-c-downloads-sidebar__iFmyt mck-o-xs-right-span"><div data-layer-region="downloads-right-rail"><h3 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-c-heading--border___K8dj3_2734c4f"></h3><div><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f"><a data-component="mdc-c-link" href="#/download/%2F~%2Fmedia%2Fmckinsey%2Fbusiness%20functions%2Fquantumblack%2Four%20insights%2Fthe%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year%2Fthe-state-of-ai-in-2023-generative-ais-breakout-year-v3.pdf%3FshouldIndex%3Dfalse" class="DownloadsSidebar_mck-c-downloads-sidebar__download-link__fPqFQ mdc-c-link___lBbY1_2734c4f" target="_self" data-layer-event-prefix="Download Link" data-layer-action="click" data-layer-report-type="" data-layer-file-name="the-state-of-ai-in-2023-generative-ais-breakout-year-v3" data-layer-report-name="the-state-of-ai-in-2023-generative-ais-breakout-year-v3>"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mdc-c-icon--size-md___yi5fA_2734c4f mck-download-icon"></span><span class="mdc-c-link__label___Pfqtd_2734c4f"> (24 pages)</span></a></div></div></div></div> <p><strong>The latest annual <a href="/featured-insights/mckinsey-global-surveys">McKinsey Global Survey</a></strong> on the current state of AI confirms the explosive growth of <a href="/featured-insights/mckinsey-explainers/what-is-generative-ai">generative AI (gen AI) tools</a>. Less than a year after many of these tools debuted, one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function. Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using gen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards’ agendas. What’s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI. The findings show that these are still early days for managing gen AI–related risks, with less than half of respondents saying their organizations are mitigating even the risk they consider most relevant: inaccuracy.</p> <p>The organizations that have already embedded AI capabilities have been the first to explore gen AI’s potential, and those seeing the most value from more traditional AI capabilities—a group we call AI high performers—are already outpacing others in their <a href="/capabilities/people-and-organizational-performance/our-insights/gen-ais-next-inflection-point-from-employee-experimentation-to-organizational-transformation">adoption of gen AI</a> tools.<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_inactive__VZfCp" aria-describedby="a64f0a37-8b7a-42c8-852a-c2c493f22db4"><sup class="FootNote_footnotesup__e73z_">1</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="a64f0a37-8b7a-42c8-852a-c2c493f22db4" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">We define AI high performers as organizations that, according to respondents, attribute at least 20 percent of their EBIT to AI adoption.</span></span></span></a></span></p> <p>The expected business disruption from gen AI is significant, and respondents predict meaningful changes to their workforces. They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs. Yet while the use of gen AI might spur the adoption of other AI tools, we see few meaningful increases in organizations’ adoption of these technologies. The percent of organizations adopting any AI tools has held steady since 2022, and adoption remains concentrated within a small number of business functions.</p> <h3>Table of Contents</h3> <ol> <li><a href="#widespread">It’s early days still, but use of gen AI is already widespread</a></li> <li><a href="#leading">Leading companies are already ahead with gen AI</a></li> <li><a href="#talent">AI-related talent needs shift, and AI’s workforce effects are expected to be substantial</a></li> <li><a href="#steady">With all eyes on gen AI, AI adoption and impact remain steady</a></li> <li><a href="#research">About the research</a></li> </ol> <a id="widespread"></a> <p> </p> <h2>1. It’s early days still, but use of gen AI is already widespread</h2> <p>The findings from the survey—which was in the field in mid-April 2023—show that, despite gen AI’s nascent public availability, experimentation with <a href="/capabilities/quantumblack/our-insights/exploring-opportunities-in-the-generative-ai-value-chain">the tools</a> is already relatively common, and respondents expect the new capabilities to transform their industries. Gen AI has captured interest across the business population: individuals across regions, industries, and seniority levels are using gen AI for work and outside of work. Seventy-nine percent of all respondents say they’ve had at least some exposure to gen AI, either for work or outside of work, and 22 percent say they are regularly using it in their own work. While reported use is quite similar across seniority levels, it is highest among respondents working in the technology sector and those in North America.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span>Interactive </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><div class="flourish-chart flourish-embed" data-src="visualisation/14236237?956372"></div></div><div class="mck-u-sr-only"></div></div> <p>Organizations, too, are now commonly using gen AI. One-third of all respondents say their organizations are already regularly using generative AI in at least one function—meaning that 60 percent of organizations with reported AI adoption are using gen AI. What’s more, 40 percent of those reporting AI adoption at their organizations say their companies expect to invest more in AI overall thanks to generative AI, and 28 percent say generative AI use is already on their board’s agenda. The most commonly reported business functions using these newer tools are the same as those in which AI use is most common overall: marketing and sales, product and service development, and service operations, such as customer care and back-office support. This suggests that organizations are pursuing these new tools where the most value is. <a href="/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier">In our previous research</a>, these three areas, along with software engineering, showed the potential to deliver about 75 percent of the total annual value from generative AI use cases.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex2.svgz?cq=50&cpy=Center"/><img alt="The most commonly reported uses of generative AI tools are in marketing and sales, product and service development, and service operations." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex2.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>In these early days, expectations for <a href="/mgi/our-research/generative-ai-how-will-it-affect-future-jobs-and-workflows">gen AI’s impact are high</a>: three-quarters of all respondents expect gen AI to cause significant or disruptive change in the nature of their industry’s competition in the next three years. Survey respondents working in the technology and financial-services industries are the most likely to expect disruptive change from gen AI. <a href="/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier">Our previous research shows</a> that, while all industries are indeed likely to see some degree of disruption, the level of impact is likely to vary.<span class="FootNote_footnote-holder__tjRqy"><a aria-label="footnote" href="javascript:void(0);" class="FootNote_footnote-wrapper__AIRwL undefined FootNote_inactive__VZfCp" aria-describedby="312a2c9f-f498-4aa0-9cab-dbbd9ae8151c"><sup class="FootNote_footnotesup__e73z_">2</sup><span class="FootNote_notch-wrapper__b_5NS"><span class="FootNote_notch__omKtY"></span></span><span class="FootNote_tooltip__QtrbA mdc-u-mt-2"><span class="FootNote_footnote-content__r2OVl"><span id="312a2c9f-f498-4aa0-9cab-dbbd9ae8151c" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">“<a href="/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier">The economic potential of generative AI: The next productivity frontier</a>,” McKinsey, June 14, 2023.</span></span></span></a></span> Industries relying most heavily on knowledge work are likely to see more disruption—and potentially reap more value. While our estimates suggest that tech companies, unsurprisingly, are poised to see the highest impact from gen AI—adding value equivalent to as much as 9 percent of global industry revenue—knowledge-based industries such as banking (up to 5 percent), pharmaceuticals and medical products (also up to 5 percent), and education (up to 4 percent) could experience significant effects as well. By contrast, manufacturing-based industries, such as aerospace, automotives, and advanced electronics, could experience less disruptive effects. This stands in contrast to the impact of previous technology waves that affected manufacturing the most and is due to gen AI’s strengths in language-based activities, as opposed to those requiring physical labor.</p> <!-- --> <h3>Responses show many organizations not yet addressing potential risks from gen AI</h3> <p>According to the survey, few companies seem fully prepared for the widespread use of gen AI—or the business risks these tools may bring. Just 21 percent of respondents reporting AI adoption say their organizations have established policies governing employees’ use of gen AI technologies in their work. And when we asked specifically about the risks of adopting gen AI, few respondents say their companies are mitigating the most commonly cited risk with gen AI: inaccuracy. Respondents cite inaccuracy more frequently than both cybersecurity and regulatory compliance, which were the most common risks from AI overall in previous surveys. Just 32 percent say they’re mitigating inaccuracy, a smaller percentage than the 38 percent who say they mitigate cybersecurity risks. Interestingly, this figure is significantly lower than the percentage of respondents who reported mitigating AI-related cybersecurity last year (51 percent). Overall, much as we’ve seen in previous years, most respondents say their organizations are not addressing AI-related risks. </p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex3.svgz?cq=50&cpy=Center"/><img alt="Inaccuracy, cybersecurity, and intellectual-property infringement are the most-cited risks of generative AI adoption." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex3.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <!-- --> <a id="leading"></a> <p> </p> <h2>2. Leading companies are already ahead with gen AI</h2> <p>The survey results show that AI high performers—that is, organizations where respondents say at least 20 percent of EBIT in 2022 was attributable to AI use—are going all in on artificial intelligence, both with gen AI and more traditional AI capabilities. These organizations that achieve significant value from AI are already using gen AI in more business functions than other organizations do, especially in product and service development and risk and supply chain management. When looking at all AI capabilities—including more traditional machine learning capabilities, robotic process automation, and chatbots—AI high performers also are much more likely than others to use AI in product and service development, for uses such as product-development-cycle optimization, adding new features to existing products, and creating new AI-based products. These organizations also are using AI more often than other organizations in risk modeling and for uses within HR such as performance management and organization design and workforce deployment optimization.</p> <div data-module-category="" class="PullQuote_mck-c-pullquote__DbaQ5 mck-o-lg-center"><blockquote data-component="mdc-c-blockquote" class="PullQuote_mck-c-blockquote__6n21p PullQuote_mck-c-blockquote--hide-quotes__CpGpg mdc-c-blockquote mdc-c-blockquote--is-quotes___TozKo_2734c4f"><p>AI high performers are much more likely than others to use AI in product and service development.</p></blockquote></div> <p>Another difference from their peers: high performers’ gen AI efforts are less oriented toward cost reduction, which is a top priority at other organizations. Respondents from AI high performers are twice as likely as others to say their organizations’ top objective for gen AI is to create entirely new businesses or sources of revenue—and they’re <em>most </em>likely to cite the increase in the value of existing offerings through new AI-based features.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex4.svgz?cq=50&cpy=Center"/><img alt="Smaller shares of AI high performers see cost reductions as their top objective for generative AI efforts. " src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex4.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>As we’ve seen <a href="/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review">in previous years</a>, these high-performing organizations invest much more than others in AI: respondents from AI high performers are more than five times more likely than others to say they spend more than 20 percent of their digital budgets on AI. They also use AI capabilities more broadly throughout the organization. Respondents from high performers are much more likely than others to say that their organizations have adopted AI in four or more business functions and that they have embedded a higher number of AI capabilities. For example, respondents from high performers more often report embedding knowledge graphs in at least one product or business function process, in addition to gen AI and related natural-language capabilities.</p> <p>While AI high performers are not immune to the challenges of capturing value from AI, the results suggest that the difficulties they face reflect their relative AI maturity, while others struggle with the more foundational, strategic elements of AI adoption. Respondents at AI high performers most often point to models and tools, such as monitoring model performance in production and retraining models as needed over time, as their top challenge. By comparison, other respondents cite strategy issues, such as setting a clearly defined AI vision that is linked with business value or finding sufficient resources.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex5.svgz?cq=50&cpy=Center"/><img alt="Models and tools pose the biggest AI-related challenge for high performers, while strategy is a common stumbling block for others." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex5.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>The findings offer further evidence that even high performers haven’t mastered best practices regarding AI adoption, such as machine-learning-operations (MLOps) approaches, though they are much more likely than others to do so. For example, just 35 percent of respondents at AI high performers report that where possible, their organizations assemble existing components, rather than reinvent them, but that’s a much larger share than the 19 percent of respondents from other organizations who report that practice.</p> <p>Many <a href="/capabilities/quantumblack/our-insights/exploring-opportunities-in-the-generative-ai-value-chain">specialized MLOps technologies and practices</a> may be needed to adopt some of the more transformative uses cases that gen AI applications can deliver—and do so as safely as possible. Live-model operations is one such area, where monitoring systems and setting up instant alerts to enable rapid issue resolution can keep gen AI systems in check. High performers stand out in this respect but have room to grow: one-quarter of respondents from these organizations say their entire system is monitored and equipped with instant alerts, compared with just 12 percent of other respondents.</p> <!-- --> <a id="talent"></a> <p> </p> <h2>3. AI-related talent needs shift, and AI’s workforce effects are expected to be substantial</h2> <p>Our latest survey results show changes in the roles that organizations are filling to support their AI ambitions. In the past year, organizations using AI most often hired data engineers, machine learning engineers, and Al data scientists—all roles that respondents commonly reported hiring in the previous survey. But a much smaller share of respondents report hiring AI-related-software engineers—the most-hired role last year—than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-edge-to-edge StoryContainer_mck-c-story-container__TLkZC mck-c-module-wrapper"><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class="StoryContainer_mck-c-story-container__item__YhXnX"><div class="mck-o-container"><div class="mck-o-container--wrapped mck-o-container--mobile-spacing mdc-u-grid mdc-u-grid-col-md-12 StoryContainer_mck-c-story-container__content-item__fg74z"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md StoryContainer_mck-c-story-container__content-text__DEQ4O StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-4"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p><strong>The findings suggest that hiring for AI-related roles remains a challenge</strong> but has become somewhat easier over the past year, which could reflect the spate of layoffs at technology companies from late 2022 through the first half of 2023. Smaller shares of respondents than in the previous survey report difficulty hiring for roles such as AI data scientists, data engineers, and data-visualization specialists, though responses suggest that hiring machine learning engineers and AI product owners remains as much of a challenge as in the previous year.</p></div></div></div><div class="StoryContainer_mck-c-story-container__content-media__o8N4Z StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-8"><div class=""><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex6.svgz?cq=50&cpy=Center"/><img alt="Hiring for AI-related roles remains a challenge, though reported difficulty has decreased since 2022 for many roles." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex6.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div></div></div></div><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class="StoryContainer_mck-c-story-container__item__YhXnX"><div class="mck-o-container"><div class="mck-o-container--wrapped mck-o-container--mobile-spacing mdc-u-grid mdc-u-grid-col-md-12 StoryContainer_mck-c-story-container__content-item__fg74z"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md StoryContainer_mck-c-story-container__content-text__DEQ4O StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-4"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p><strong>Looking ahead to the next three years, respondents predict that the adoption of AI will reshape many roles</strong> in the workforce. Generally, they expect more employees to be reskilled than to be separated. Nearly four in ten respondents reporting AI adoption expect more than 20 percent of their companies’ workforces will be reskilled, whereas 8 percent of respondents say the size of their workforces will decrease by more than 20 percent.</p></div></div></div><div class="StoryContainer_mck-c-story-container__content-media__o8N4Z StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-8"><div class=""><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex7.svgz?cq=50&cpy=Center"/><img alt="Survey respondents expect AI to meaningfully change their organizations’ workforces." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex7.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div></div></div></div><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class="StoryContainer_mck-c-story-container__item__YhXnX"><div class="mck-o-container"><div class="mck-o-container--wrapped mck-o-container--mobile-spacing mdc-u-grid mdc-u-grid-col-md-12 StoryContainer_mck-c-story-container__content-item__fg74z"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md StoryContainer_mck-c-story-container__content-text__DEQ4O StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-4"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p><strong>Looking specifically at gen AI’s predicted impact,</strong> service operations is the only function in which most respondents expect to see a decrease in workforce size at their organizations. This finding generally aligns with what <a href="/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier">our recent research</a> suggests: while the emergence of gen AI increased our estimate of the percentage of worker activities that could be automated (60 to 70 percent, up from 50 percent), this doesn’t necessarily translate into the automation of an entire role.</p></div></div></div><div class="StoryContainer_mck-c-story-container__content-media__o8N4Z StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-8"><div class=""><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex8.svgz?cq=50&cpy=Center"/><img alt="Service operations is the only function in which most respondents expect to see a decrease in workforce size because of generative AI." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex8.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div></div></div></div><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class="StoryContainer_mck-c-story-container__item__YhXnX"><div class="mck-o-container"><div class="mck-o-container--wrapped mck-o-container--mobile-spacing mdc-u-grid mdc-u-grid-col-md-12 StoryContainer_mck-c-story-container__content-item__fg74z"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md StoryContainer_mck-c-story-container__content-text__DEQ4O StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-4"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p><strong>AI high performers are expected to conduct much higher levels of reskilling</strong> than other companies are. Respondents at these organizations are over three times more likely than others to say their organizations will reskill more than 30 percent of their workforces over the next three years as a result of AI adoption.</p></div></div></div><div class="StoryContainer_mck-c-story-container__content-media__o8N4Z StoryContainer_mck-c-story-container__container-sticky__EK8hB StoryContainer_mck-c-story-container__container-sticky--extra-spacing__uDmVE mdc-u-grid-col-md-span-8"><div class=""><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex9.svgz?cq=50&cpy=Center"/><img alt="Respondents at AI high performers expect their organizations to reskill larger portions of the workforce than other respondents do." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex9.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div></div></div></div></div> <!-- --> <a id="steady"></a> <p> </p> <h2>4. With all eyes on gen AI, AI adoption and impact remain steady</h2> <p>While the use of gen AI tools is spreading rapidly, the survey data doesn’t show that these newer tools are propelling organizations’ overall AI adoption. The share of organizations that have adopted AI overall remains steady, at least for the moment, with 55 percent of respondents reporting that their organizations have adopted AI. Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope. Product and service development and service operations continue to be the two business functions in which respondents most often report AI adoption, as was true in the previous four surveys. And overall, just 23 percent of respondents say at least 5 percent of their organizations’ EBIT last year was attributable to their use of AI—essentially flat with the previous survey—suggesting there is much more room to capture value.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex10.svgz?cq=50&cpy=Center"/><img alt="Less than one-third of respondents say their organizations use AI in more than one function—a share largely unchanged since 2021." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex10.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>Organizations continue to see returns in the business areas in which they are using AI, and they plan to increase investment in the years ahead. We see a majority of respondents reporting AI-related revenue increases within each business function using AI. And looking ahead, more than two-thirds expect their organizations to increase their AI investment over the next three years.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-inline-module-container mck-o-md-center"><div class="mdc-u-grid mdc-u-grid-gutter-lg mdc-u-grid-col-sm-1 mdc-u-grid--align-start mdc-u-mb-3 GenericItem_mck-c-generic-item__sGwKL"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-xs GenericItem_mck-c-generic-item__content__gq1m0"><div class="mck-c-eyebrow mdc-u-ts-10"><span> </span></div></div></div><div class="mck-u-inline-module-border-top mck-u-inline-module-border-bottom"><picture data-component="mdc-c-picture" class="Exhibit_mck-c-exhibit__image__pyIDm"><source media="(min-width: 768px)" srcSet="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex11.svgz?cq=50&cpy=Center"/><img alt="Organizations continue to see benefits from AI adoption in the functions using AI capabilities." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai%20in%202023%20generative%20ais%20breakout%20year/svgz_stateofai2023_ex11.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <!-- --> <a id="research"></a> <p> </p> <h2>About the research</h2> <p>The online survey was in the field April 11 to 21, 2023, and garnered responses from 1,684 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 913 said their organizations had adopted AI in at least one function and were asked questions about their organizations’ AI use. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.</p></div><div class="container-placeholder"></div></div></div><div class="mdc-u-grid mdc-u-grid-gutter-xl"><section role="contentinfo" data-layer-region="article-about-authors" class="mdc-u-grid mdc-u-grid-col-md-12 AboutAuthor_mck-c-about-author__nRJzu"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-11"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-c-heading--border___K8dj3_2734c4f mdc-u-align-center"></h5><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline mck-u-links-inline--secondary mdc-u-mt-5"><div><p>The survey content and analysis were developed by <strong>Michael Chui</strong>, a partner at the McKinsey Global Institute and a partner in McKinsey’s Bay Area office, where <strong><a href="/our-people/lareina-yee">Lareina Yee</a></strong> is a senior partner; <strong><a href="/our-people/bryce-hall">Bryce Hall</a></strong>, an associate partner in the Washington, DC, office; and senior partners <strong><a href="/our-people/alex-singla">Alex Singla</a></strong> and <strong><a href="/our-people/alexander-sukharevsky">Alexander Sukharevsky</a></strong>, global leaders of QuantumBlack, AI by McKinsey, based in the Chicago and London offices, respectively.</p> <p>They wish to thank Shivani Gupta, Abhisek Jena, Begum Ortaoglu, Barr Seitz, and Li Zhang for their contributions to this work.</p> <hr> <p>This article was edited by Heather Hanselman, an editor in the Atlanta office.</p></div></div></div></section><section class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-screen-only"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-5 mdc-u-grid-col-lg-end-9"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-c-heading--border___K8dj3_2734c4f mdc-u-align-center">Explore a career with us</h5><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f mdc-c-link-container--align-center___ar3mu_2734c4f"><a data-component="mdc-c-link" href="/careers/search-jobs" class="mdc-c-button___U4iY2_2734c4f mdc-c-button--secondary___Boipq_2734c4f mdc-c-button--size-large___jwpUy_2734c4f" aria-label="Search Openings" data-layer-event-prefix="CTA Link" data-layer-action="click" data-layer-category="careers" data-layer-subcategory="search" data-layer-text="Search Openings"><span class="mdc-c-link__label___Pfqtd_2734c4f">Search Openings</span></a></div></div></section></div></main></div><div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="StandalonePromo" class="RelatedArticle_mck-c-article-related__GGA76 mck-u-screen-only" data-layer-region="related-articles"><div class="mdc-o-container__wrapper is-wrapped mdc-u-spaced-mobile"><h5 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-c-heading--title___5qyOB_2734c4f mdc-u-align-center">Related Articles</h5><div class="mdc-u-grid mdc-u-grid-col-md-3 RelatedArticle_items-container__s2uD0"><div class="mdc-u-grid mdc-u-grid-gutter-lg Card_card__diA2r Card_hover-effect__RGb9b"><div class="Card_wrapper-image__8b4P6"><a data-component="mdc-c-link" href="/featured-insights/mckinsey-live/webinars/the-economic-potential-of-generative-ai-the-next-productivity-frontier" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-thee-0 { aspect-ratio: 16/9 }</style><img alt="McKinsey partners Lareina Yee and Michael Chui" class="picture-uniqueKey-thee-0" src="/~/media/mckinsey/featured%20insights/mckinsey%20live/mck-live_062123_economic-potential-generative-ai.jpg?cq=50&mw=767&car=16:9&cpy=Center" loading="lazy"/></picture></a></div><div class="Card_wrapper-text__U6Y3k"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f Card_content-block__pF6Z1"><span>Webcast</span><h6 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-6"><a data-component="mdc-c-link" href="/featured-insights/mckinsey-live/webinars/the-economic-potential-of-generative-ai-the-next-productivity-frontier" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>The economic potential of generative AI: The next productivity frontier</div></a></h6></div></div></div><div class="mdc-u-grid mdc-u-grid-gutter-lg Card_card__diA2r Card_hover-effect__RGb9b"><div class="Card_wrapper-image__8b4P6"><a data-component="mdc-c-link" href="/featured-insights/mckinsey-explainers/what-is-generative-ai" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-what-0 { aspect-ratio: 16/9 }</style><img alt="A green apple split into 3 parts on a gray background. 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" class="picture-uniqueKey-what-0" src="/~/media/mckinsey/featured%20insights/mckinsey%20explainers/what%20is%20generative%20ai/generative-ai-1219474321-thumb-1536x1536-v3.jpg?cq=50&mw=767&car=16:9&cpy=Center" loading="lazy"/></picture></a></div><div class="Card_wrapper-text__U6Y3k"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f Card_content-block__pF6Z1"><span>Article</span><h6 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-6"><a data-component="mdc-c-link" href="/featured-insights/mckinsey-explainers/what-is-generative-ai" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>What is generative AI?</div></a></h6></div></div></div><div class="mdc-u-grid mdc-u-grid-gutter-lg Card_card__diA2r Card_hover-effect__RGb9b"><div class="Card_wrapper-image__8b4P6"><a data-component="mdc-c-link" href="/capabilities/quantumblack/our-insights/exploring-opportunities-in-the-generative-ai-value-chain" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-explo-0 { aspect-ratio: 16/9 }</style><img alt="Circular hub element virtual reality of big data, technology concept." class="picture-uniqueKey-explo-0" src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/exploring%20opportunities%20in%20the%20generative%20ai%20value%20chain/thumb-gettyimages-1470671176.jpg?cq=50&mw=767&car=16:9&cpy=Center" loading="lazy"/></picture></a></div><div class="Card_wrapper-text__U6Y3k"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f Card_content-block__pF6Z1"><span>Article</span><h6 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-6"><a data-component="mdc-c-link" href="/capabilities/quantumblack/our-insights/exploring-opportunities-in-the-generative-ai-value-chain" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>Exploring opportunities in the generative AI value chain</div></a></h6></div></div></div></div></div></div></div></main></div><script id="__NEXT_DATA__" type="application/json">{"props":{"pageProps":{"locale":"en","dictionary":{},"sitecoreContext":{"route":{"name":"The state of AI in 2023 Generative AIs breakout year","displayName":"The state of AI in 2023 Generative AIs breakout year","fields":null,"databaseName":"web","deviceId":"fe5d7fdf-89c0-4d99-9aa3-b5fbd009c9f3","itemId":"1c71ab3e-4811-4d90-b6b8-d4a0d1ab948d","itemLanguage":"en","itemVersion":2,"layoutId":"ae753eb4-a035-40b4-83bf-4b4438df6742","templateId":"683910db-02ba-40ba-92e7-726c880160a9","templateName":"ArticleJSS","placeholders":{"jss-main":[{"uid":"232bb7e9-289f-492d-a916-2b6185e44a84","componentName":"ArticleTemplate","dataSource":"","fields":{"data":{"articleTemplate":{"title":{"jsonValue":{"value":"The state of AI in 2023: Generative AI\u0026rsquo;s breakout year"}},"sEOTitle":{"value":""},"description":{"jsonValue":{"value":"As organizations rapidly deploy generative AI tools, survey respondents expect significant effects on their industries and workforces."}},"sEODescription":{"value":"Explore McKinsey's State of AI in 2023 report, a detailed new survey that looks at how generative AI is reshaping the world's industries and workforces."},"displayDate":{"jsonValue":{"value":"2023-08-01T00:00:00Z"}},"body":{"value":"\u003ch4\u003eYou have reached a page with older survey data. Please see our 2024 survey results \u003cspan style=\"color: #2155ff;\"\u003e\u003ca href=\"/capabilities/quantumblack/our-insights/the-state-of-ai\"\u003ehere\u003c/a\u003e\u003c/span\u003e.\u003c/h4\u003e\n[[audio 1]]\n[[DownloadsSidebar]]\n\u003cp\u003e\u003cstrong\u003eThe latest annual \u003ca href=\"/featured-insights/mckinsey-global-surveys\"\u003eMcKinsey Global Survey\u003c/a\u003e\u003c/strong\u003e\u0026nbsp;on the current state of AI confirms the explosive growth of \u003ca href=\"/featured-insights/mckinsey-explainers/what-is-generative-ai\"\u003egenerative AI (gen AI) tools\u003c/a\u003e. Less than a year after many of these tools debuted, one-third of our survey respondents say their organizations are using gen AI regularly in at least one business function. Amid recent advances, AI has risen from a topic relegated to tech employees to a focus of company leaders: nearly one-quarter of surveyed C-suite executives say they are personally using\ngen AI tools for work, and more than one-quarter of respondents from companies using AI say gen AI is already on their boards\u0026rsquo; agendas. What\u0026rsquo;s more, 40 percent of respondents say their organizations will increase their investment in AI overall because of advances in gen AI. The findings show that these are still early days for managing gen AI\u0026ndash;related risks, with less than half of respondents saying their organizations are mitigating even the risk they consider most relevant: inaccuracy.\u003c/p\u003e\n\u003cp\u003eThe organizations that have already embedded AI capabilities have been the first to explore gen AI\u0026rsquo;s potential, and those seeing the most value from more traditional AI capabilities\u0026mdash;a group we call AI high performers\u0026mdash;are already outpacing others in their \u003ca href=\"/capabilities/people-and-organizational-performance/our-insights/gen-ais-next-inflection-point-from-employee-experimentation-to-organizational-transformation\"\u003eadoption of gen AI\u003c/a\u003e\u0026nbsp;tools.[[footnote 1]]\u003c/p\u003e\n\u003cp\u003eThe expected business disruption from gen AI is significant, and respondents predict meaningful changes to their workforces. They anticipate workforce cuts in certain areas and large reskilling efforts to address shifting talent needs. Yet while the use of gen AI might spur the adoption of other AI tools, we see few meaningful increases in organizations\u0026rsquo; adoption of these technologies. The percent of organizations adopting any AI tools has held steady since 2022, and adoption remains concentrated within a small number of business functions.\u003c/p\u003e\n\u003ch3\u003eTable of Contents\u003c/h3\u003e\n\u003col\u003e\n \u003cli\u003e\u003ca href=\"#widespread\"\u003eIt\u0026rsquo;s early days still, but use of gen AI is already widespread\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003e\u003ca href=\"#leading\"\u003eLeading companies are already ahead with gen AI\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003e\u003ca href=\"#talent\"\u003eAI-related talent needs shift, and AI\u0026rsquo;s workforce effects are expected to be substantial\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003e\u003ca href=\"#steady\"\u003eWith all eyes on gen AI, AI adoption and impact remain steady\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003e\u003ca href=\"#research\"\u003eAbout the research\u003c/a\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003ca id=\"widespread\"\u003e\u003c/a\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e1. It\u0026rsquo;s early days still, but use of gen AI is already widespread\u003c/h2\u003e\n\u003cp\u003eThe findings from the survey\u0026mdash;which was in the field in mid-April 2023\u0026mdash;show that, despite gen AI\u0026rsquo;s nascent public availability, experimentation with \u003ca href=\"/capabilities/quantumblack/our-insights/exploring-opportunities-in-the-generative-ai-value-chain\"\u003ethe tools\u003c/a\u003e\u0026nbsp;is already relatively common, and respondents expect the new capabilities to transform their industries. Gen AI has captured interest across the business population: individuals across regions, industries, and seniority levels are using gen AI for work and outside of work. Seventy-nine percent of all respondents say they\u0026rsquo;ve had at least some exposure to gen AI, either for work or outside of work, and 22\u0026nbsp;percent say they are regularly using it in their own work. While reported use is quite similar across seniority levels, it is highest among respondents working in the technology sector and those in North America.\u003c/p\u003e\n[[exhibit 1]]\n\u003cp\u003eOrganizations, too, are now commonly using gen AI. One-third of all respondents say their organizations are already regularly using generative AI in at least one function\u0026mdash;meaning that 60\u0026nbsp;percent of organizations with reported AI adoption are using gen AI. What\u0026rsquo;s more, 40 percent of those reporting AI adoption at their organizations say their companies expect to invest more in AI overall thanks to generative AI, and 28 percent say generative AI use is already on their board\u0026rsquo;s agenda. The most commonly reported business functions using these newer tools are the same as those in which AI use is most common overall: marketing and sales, product and service development, and service operations, such as customer care and back-office support. This suggests that organizations are pursuing these new tools where the most value is. \u003ca href=\"/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier\"\u003eIn our previous research\u003c/a\u003e, these three areas, along with software engineering, showed the potential to deliver about 75 percent of the total annual value from generative AI use cases.\u003c/p\u003e\n[[exhibit 2]]\n\u003cp\u003eIn these early days, expectations for \u003ca href=\"/mgi/our-research/generative-ai-how-will-it-affect-future-jobs-and-workflows\"\u003egen AI\u0026rsquo;s impact are high\u003c/a\u003e: three-quarters of all respondents expect gen AI to cause significant or disruptive change in the nature of their industry\u0026rsquo;s competition in the next three years. Survey respondents working in the technology and financial-services industries are the most likely to expect disruptive change from gen AI. \u003ca href=\"/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier\"\u003eOur previous research shows\u003c/a\u003e\u0026nbsp;that, while all industries are indeed likely to see some degree of disruption, the level of impact is likely to vary.[[footnote 2]] Industries relying most heavily on knowledge work are likely to see more disruption\u0026mdash;and potentially reap more value. While our estimates suggest that tech companies, unsurprisingly, are poised to see the highest impact from gen AI\u0026mdash;adding value equivalent to as much as 9 percent of global industry revenue\u0026mdash;knowledge-based industries such as banking (up to 5 percent), pharmaceuticals and medical products (also up to 5 percent), and education (up to 4 percent) could experience significant effects as well. By contrast, manufacturing-based industries, such as aerospace, automotives, and advanced electronics, could experience less disruptive effects. This stands in contrast to the impact of previous technology waves that affected manufacturing the most and is due to gen AI\u0026rsquo;s strengths in language-based activities, as opposed to those requiring physical labor.\u003c/p\u003e\n[[ceros alexsingla]]\n\u003ch3\u003eResponses show many organizations not yet addressing potential risks from gen AI\u003c/h3\u003e\n\u003cp\u003eAccording to the survey, few companies seem fully prepared for the widespread use of gen AI\u0026mdash;or the business risks these tools may bring. Just 21 percent of respondents reporting AI adoption say their organizations have established policies governing employees\u0026rsquo; use of gen AI technologies in their work. And when we asked specifically about the risks of adopting gen AI, few respondents say their companies are mitigating the most commonly cited risk with gen AI: inaccuracy. Respondents cite inaccuracy more frequently than both cybersecurity and regulatory compliance, which were the most common risks from AI overall in previous surveys. Just 32 percent say they\u0026rsquo;re mitigating inaccuracy, a smaller percentage than the 38\u0026nbsp;percent who say they mitigate cybersecurity risks. Interestingly, this figure is significantly lower than the percentage of respondents who reported mitigating AI-related cybersecurity last year (51 percent). Overall, much as we\u0026rsquo;ve seen in previous years, most respondents say their organizations are not addressing AI-related risks. \u003c/p\u003e\n[[exhibit 3]]\n[[ceros alexsukharevsky]]\n\u003ca id=\"leading\"\u003e\u003c/a\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e2. Leading companies are already ahead with gen AI\u003c/h2\u003e\n\u003cp\u003eThe survey results show that AI high performers\u0026mdash;that is, organizations where respondents say at least 20 percent of EBIT in 2022 was attributable to AI use\u0026mdash;are going all in on artificial intelligence, both with gen AI and more traditional AI capabilities. These organizations that achieve significant value from AI are already using gen AI in more business functions than other organizations do, especially in product and service development and risk and supply chain management. When looking at all AI capabilities\u0026mdash;including more traditional machine learning capabilities, robotic process automation, and chatbots\u0026mdash;AI high performers also are much more likely than others to use AI in product and service development, for uses such as product-development-cycle optimization, adding new features to existing products, and creating new AI-based products. These organizations also are using AI more often than other organizations in risk modeling and for uses within HR such as performance management and organization design and workforce deployment optimization.\u003c/p\u003e\n[[pullquote 1]]\n\u003cp\u003eAnother difference from their peers: high performers\u0026rsquo; gen AI efforts are less oriented toward cost reduction, which is a top priority at other organizations. Respondents from AI high performers are twice as likely as others to say their organizations\u0026rsquo; top objective for gen AI is to create entirely new businesses or sources of revenue\u0026mdash;and they\u0026rsquo;re \u003cem\u003emost \u003c/em\u003elikely to cite the increase in the value of existing offerings through new AI-based features.\u003c/p\u003e\n[[exhibit 4]]\n\u003cp\u003eAs we\u0026rsquo;ve seen \u003ca href=\"/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review\"\u003ein previous years\u003c/a\u003e, these high-performing organizations invest much more than others in AI: respondents from AI high performers are more than five times more likely than others to say they spend more than 20 percent of their digital budgets on AI. They also use AI capabilities more broadly throughout the organization. Respondents from high performers are much more likely than others to say that their organizations have adopted AI in four or more business functions and that they have embedded a higher number of AI capabilities. For example, respondents from high performers more often report embedding knowledge graphs in at least one product or business function process, in addition to gen AI and related natural-language capabilities.\u003c/p\u003e\n\u003cp\u003eWhile AI high performers are not immune to the challenges of capturing value from AI, the results suggest that the difficulties they face reflect their relative AI maturity, while others struggle with the more foundational, strategic elements of AI adoption. Respondents at AI high performers most often point to models and tools, such as monitoring model performance in production and retraining models as needed over time, as their top challenge. By comparison, other respondents cite strategy issues, such as setting a clearly defined AI vision that is linked with business value or finding sufficient resources.\u003c/p\u003e\n[[exhibit 5]]\n\u003cp\u003eThe findings offer further evidence that even high performers haven\u0026rsquo;t mastered best practices regarding AI adoption, such as machine-learning-operations (MLOps) approaches, though they are much more likely than others to do so. For example, just 35 percent of respondents at AI high performers report that where possible, their organizations assemble existing components, rather than reinvent them, but that\u0026rsquo;s a much larger share than the 19 percent of respondents from other organizations who report that practice.\u003c/p\u003e\n\u003cp\u003eMany \u003ca href=\"/capabilities/quantumblack/our-insights/exploring-opportunities-in-the-generative-ai-value-chain\"\u003especialized MLOps technologies and practices\u003c/a\u003e\u0026nbsp;may be needed to adopt some of the more transformative uses cases that gen AI applications can deliver\u0026mdash;and do so as safely as possible. Live-model operations is one such area, where monitoring systems and setting up instant alerts to enable rapid issue resolution can keep gen AI systems in check. High performers stand out in this respect but have room to grow: one-quarter of respondents from these organizations say their entire system is monitored and equipped with instant alerts, compared with just 12 percent of other respondents.\u003c/p\u003e\n[[ceros Bryce]]\n\u003ca id=\"talent\"\u003e\u003c/a\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3. AI-related talent needs shift, and AI\u0026rsquo;s workforce effects are expected to be substantial\u003c/h2\u003e\n\u003cp\u003eOur latest survey results show changes in the roles that organizations are filling to support their AI ambitions. In the past year, organizations using AI most often hired data engineers, machine learning engineers, and Al data scientists\u0026mdash;all roles that respondents commonly reported hiring in the previous survey. But a much smaller share of respondents report hiring AI-related-software engineers\u0026mdash;the most-hired role last year\u0026mdash;than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year.\u003c/p\u003e\n[[story 1]]\n[[ceros lareina]]\n\u003ca id=\"steady\"\u003e\u003c/a\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e4. With all eyes on gen AI, AI adoption and impact remain steady\u003c/h2\u003e\n\u003cp\u003eWhile the use of gen AI tools is spreading rapidly, the survey data doesn\u0026rsquo;t show that these newer tools are propelling organizations\u0026rsquo; overall AI adoption. The share of organizations that have adopted AI overall remains steady, at least for the moment, with 55 percent of respondents reporting that their organizations have adopted AI. Less than a third of respondents continue to say that their organizations have adopted AI in more than one business function, suggesting that AI use remains limited in scope. Product and service development and service operations continue to be the two business functions in which respondents most often report AI adoption, as was true in the previous four surveys. And overall, just 23 percent of respondents say at least 5 percent of their organizations\u0026rsquo; EBIT last year was attributable to their use of AI\u0026mdash;essentially flat with the previous survey\u0026mdash;suggesting there is much more room to capture value.\u003c/p\u003e\n[[exhibit 10]]\n\u003cp\u003eOrganizations continue to see returns in the business areas in which they are using AI, and\nthey plan to increase investment in the years ahead. We see a majority of respondents reporting AI-related revenue increases within each business function using AI. And looking ahead, more than two-thirds expect their organizations to increase their AI investment over the next three years.\u003c/p\u003e\n[[exhibit 11]]\n[[ceros michael]]\n\u003ca id=\"research\"\u003e\u003c/a\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAbout the research\u003c/h2\u003e\n\u003cp\u003eThe online survey was in the field April 11 to 21, 2023, and garnered responses from 1,684 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 913 said their organizations had adopted AI in at least one function and were asked questions about their organizations\u0026rsquo; AI use. To adjust for differences in response rates, the data are weighted by the contribution of each respondent\u0026rsquo;s nation to global GDP.\u003c/p\u003e"},"isFullScreenInteractive":{"boolValue":false},"hideStickySocialShareBar":{"boolValue":false},"desktopID":{"value":""},"mobileID":{"value":""},"desktopURL":{"value":""},"mobileURL":{"value":""},"desktopPaddingPercentage":{"value":""},"mobilePaddingPercentage":{"value":""},"desktopOverrideHeight":{"value":""},"mobileOverrideHeight":{"value":""},"cerosOembedURL":{"value":""},"cerosRenderMode":{"targetItem":null},"cerosBackgroundColor":{"targetItem":null},"hideByLine":{"boolValue":true},"tableOfContentsTitle":{"value":"TABLE OF CONTENTS"},"accessStatus":{"targetItem":{"key":{"value":"RegisteredUsers"},"value":{"value":"Registered Users"}}},"articleType":{"targetItem":{"displayName":"Survey"}},"hasSpecialReport":{"boolValue":false},"contentType":{"targetItem":{"displayName":"Article"}},"sourcePublication":{"targetItem":null},"externalPublication":{"value":""},"mobileReady":{"boolValue":true},"forClientsOnly":{"boolValue":false},"excludeFromClientLink":{"boolValue":false},"originalPublishDate":{"jsonValue":{"value":"2023-08-01T00:00:00Z"}},"footnotes":{"value":"\u003col\u003e\n \u003cli\u003eWe define AI high performers as organizations that, according to respondents, attribute at least 20 percent of their EBIT to AI adoption.\u003c/li\u003e\n \u003cli\u003e\u0026ldquo;\u003ca href=\"/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier\"\u003eThe economic potential of generative AI: The next productivity frontier\u003c/a\u003e,\u0026rdquo; McKinsey, June 14, 2023.\u003c/li\u003e\n\u003c/ol\u003e"},"contributoryPractice":{"targetItems":[{"displayName":"QuantumBlack, AI by McKinsey"}]},"aboutTheAuthors":{"value":"\u003cp\u003eThe survey content and analysis were developed by \u003cstrong\u003eMichael Chui\u003c/strong\u003e, a partner at the McKinsey Global Institute and a partner in McKinsey\u0026rsquo;s Bay Area office, where \u003cstrong\u003e\u003ca href=\"/our-people/lareina-yee\"\u003eLareina Yee\u003c/a\u003e\u003c/strong\u003e is a senior partner; \u003cstrong\u003e\u003ca href=\"/our-people/bryce-hall\"\u003eBryce Hall\u003c/a\u003e\u003c/strong\u003e, an associate partner in the Washington, DC, office; and senior partners \u003cstrong\u003e\u003ca href=\"/our-people/alex-singla\"\u003eAlex Singla\u003c/a\u003e\u003c/strong\u003e and \u003cstrong\u003e\u003ca href=\"/our-people/alexander-sukharevsky\"\u003eAlexander Sukharevsky\u003c/a\u003e\u003c/strong\u003e, global leaders of QuantumBlack, AI by McKinsey, based in the Chicago and London offices, respectively.\u003c/p\u003e\n\u003cp\u003eThey wish to thank Shivani Gupta, Abhisek Jena, Begum Ortaoglu, Barr Seitz, and Li Zhang for their contributions to this work.\u003c/p\u003e\n\u003chr\u003e\n\u003cp\u003eThis article was edited by Heather Hanselman, an editor in the Atlanta office.\u003c/p\u003e"},"authors":{"targetItems":[{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"36DD0837215D49E78AB6162F78A61DC7","name":"Michael Chui","authorTitle":{"value":"Michael Chui"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/michael chui/michael chui_00168-1_fc-mask_profile_1536x1152.png","alt":""},"emailLinks":{"value":"Michael_Chui@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/chuimichael"},"description":{"value":"Leads research on the impact of artificial intelligence, information technologies and innovation on business, the economy, and society"},"locations":{"targetItems":[{"name":"Bay Area","displayName":"Bay Area"}]},"firmTitle":{"value":"Senior Fellow"},"thumbnailImage":{"alt":"","src":"/~/media/mckinsey/our people/michael chui/michael chui_00168-1_fc-mask_headshot_988x741.png"},"url":{"path":"/our-people/michael-chui"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"53ACD38C0EF34BD2933A6D350B110B74","name":"Bryce Hall","authorTitle":{"value":"Bryce Hall"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/bryce hall/bryce-hall_headshot_988x741.jpg","alt":"Bryce Hall"},"emailLinks":{"value":"Bryce_Hall@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/brycewilliamhall/"},"description":{"value":"Advises organizations on digital and analytics transformations to help develop meaningful insights and maximize value"},"locations":{"targetItems":[{"name":"Washington DC","displayName":"Washington DC"}]},"firmTitle":{"value":"Solution Associate Partner"},"thumbnailImage":{"alt":"Bryce Hall","src":"/~/media/mckinsey/our people/bryce hall/bryce-hall_headshot_988x741.jpg"},"url":{"path":"/our-people/bryce-hall"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"DC8CA716CDAB4962ABA013B6C019C96D","name":"Alex Singla","authorTitle":{"value":"Alex Singla"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/alex singla/alex_singla-5144_standard_profile_1536x1152.jpg","alt":"Alex Singla"},"emailLinks":{"value":"Alex_Singla@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/alexsingla/"},"description":{"value":"Global leader of QuantumBlack, AI by McKinsey; advises clients on strategy, digital and analytics, operations, enterprise transformation, and value creation across industries with a focus on financial services and insurance"},"locations":{"targetItems":[{"name":"Chicago","displayName":"Chicago"}]},"firmTitle":{"value":"Senior Partner"},"thumbnailImage":{"alt":"Alex Singla","src":"/~/media/mckinsey/our people/alex singla/alex_singla-5144_headshot_988x741.jpg"},"url":{"path":"/our-people/alex-singla"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"401CBA860DAA461E925889FB1A8F9F13","name":"Alexander Sukharevsky","authorTitle":{"value":"Alexander Sukharevsky"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/alex sukharevsky/alex_sukharevsky_standard_profile_1536x1152-new.jpg","alt":"Photo of Alexander Sukharevsky, Senior Partner, McKinsey \u0026 Company"},"emailLinks":{"value":"Alex_Sukharevsky@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/alexander-sukharevsky/"},"description":{"value":"Global leader of QuantumBlack, AI by McKinsey, working across industries to redefine business models and improve performance through the responsible use of artificial intelligence and technology"},"locations":{"targetItems":[{"name":"London","displayName":"London"}]},"firmTitle":{"value":"Senior Partner"},"thumbnailImage":{"alt":"Photo of Alexander Sukharevsky, Senior Partner, McKinsey \u0026 Company","src":"/~/media/mckinsey/our people/alex sukharevsky/alex_sukharevsky_headshot_988x741-new.jpg"},"url":{"path":"/our-people/alexander-sukharevsky"}}]}},{"template":{"id":"3FBABDB63A094F68B1F8E1BBE1BA124E","name":"Author"},"id":"B5FC5264C6CD4777A29C9A1851C1A852","name":"Lareina Yee","authorTitle":{"value":"Lareina Yee"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/lareina yee/v2/lareina_lee_standard_profile_1536x1152.jpg","alt":"Lareina Yee"},"emailLinks":{"value":"Lareina_Yee@mckinsey.com"},"linkedInUrl":{"value":"https://www.linkedin.com/in/lareinayee/"},"description":{"value":"Advises companies on growth, organization, and tech-led transformation; chair of McKinsey's Technology Council, expert in generative AI and emerging technologies"},"locations":{"targetItems":[{"name":"Bay Area","displayName":"Bay Area"}]},"firmTitle":{"value":"Senior Partner"},"thumbnailImage":{"alt":"Lareina Yee","src":"/~/media/mckinsey/our people/lareina yee/v2/lareina_lee_headshot_988x741.jpg"},"url":{"path":"/our-people/lareina-yee"}}]}}]},"nonPartnerAuthors":{"targetItems":[]},"interactiveToUse":{"targetItem":null},"enableArticleComponents":{"boolValue":false},"relatedArticles":{"targetItems":[{"sourcePublication":null,"publicationSource":null,"externalPublication":null,"title":{"value":"The economic potential of generative AI: The next productivity frontier"},"url":{"path":"/featured-insights/mckinsey-live/webinars/the-economic-potential-of-generative-ai-the-next-productivity-frontier"},"eyebrow":null,"articleType":null,"contentType":{"targetItem":{"name":"Webcast"}},"description":{"value":"Business leaders who understand the new technology and its potential effects are on the way to benefiting from the coming surge in global productivity."},"standardImage":{"src":"/~/media/mckinsey/featured insights/mckinsey live/mck-live_062123_economic-potential-generative-ai.jpg","alt":"McKinsey partners Lareina Yee and Michael Chui"},"heroImage":null,"thumbnailImage":null},{"sourcePublication":{"targetItem":null},"publicationSource":null,"externalPublication":{"value":""},"title":{"value":"What is generative AI?"},"url":{"path":"/featured-insights/mckinsey-explainers/what-is-generative-ai"},"eyebrow":{"targetItem":{"name":"Article"}},"articleType":{"targetItem":{"name":"Article"}},"contentType":{"targetItem":{"name":"Article"}},"description":{"value":"Generative artificial intelligence (AI) describes algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and videos. 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