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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 early 2024: Gen AI adoption spikes and starts to generate value</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="2024-05-30T00:00:00Z">May 30, 2024</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 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mdc-u-grid-col-lg-end-11"><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-5"><div class="mck-u-links-inline">As generative AI adoption accelerates, survey respondents report measurable benefits and increased mitigation of the risk of inaccuracy. A small group of high performers lead the way.</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"> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-o-edge-to-edge mck-c-module-wrapper"><div class="mck-u-screen-only" id="interactive-bespoke-state-of-ai-in-early-2024" aria-label="" role="document"></div></div> <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%2F2024%2Fthe-state-of-ai-in-early-2024-final.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-early-2024-final" data-layer-report-name="the-state-of-ai-in-early-2024-final>"><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"> (23 pages)</span></a></div></div></div></div> <p><strong>If 2023</strong> was the year the world discovered <a href="/featured-insights/mckinsey-explainers/what-is-generative-ai">generative AI (gen AI)</a>, 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest <a href="/featured-insights/mckinsey-global-surveys">McKinsey Global Survey</a> on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high <a href="/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year">as they were last year</a>, with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="lightest-grey" data-module-category="" data-module-gradient-position="bottom-right" class="mck-c-inline-module-container SideBar_mck-c-sidebar__bgimg-wrapper__Qj4Dt mck-o-sm-left-span SideBar_mck-c-sidebar__sidebar-wrapper__Dpjw2 SideBar_mck-c-sidebar__sidebar-wrapper--istablet__IQ6ii mck-u-screen-only mck-c-module-wrapper" data-layer-region="sidebar"><div class="SideBar_mck-c-sidebar__epoAm mck-o-md-center"><div class="SideBar_mck-c-sidebar__share-icons-wrapper__9gB_c"><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f mdc-c-link-container--display-column___X0HDD_2734c4f SideBar_mck-c-sidebar__share-icons___eQy6"><button data-component="mdc-c-button" aria-label="Expandable Sidebar" type="button" id="button_id" class="mdc-c-button___U4iY2_2734c4f mdc-c-button--ghost mdc-c-button--size-medium SideBar_mck-c-sidebar__toggle-btn__EL8iE" aria-expanded="false" data-layer-event-prefix="UI Item" data-layer-action="click" data-layer-category="sidebar" data-layer-subcategory="open" data-layer-text="open sidebar"><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mdc-c-icon--radial___y3csX_2734c4f mdc-c-icon--size-xxl___cL3ZT_2734c4f mck-plus-no-circle-icon"></span></button></div></div><div class="SideBar_mck-c-sidebar__content-outer__UdWCq"><div class="SideBar_mck-c-sidebar__eyebrow__5GSEq"></div><div class="SideBar_mck-c-sidebar__content__raEwe"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-3 SideBar_mck-c-sidebar__content-heading__NJekY"><div>About the authors</div></h2><div class="SideBar_mck-c-sidebar__content-description__4p9iI mdc-u-ts-7"><div class="mdc-o-content-body"><p>This article is a collaborative effort by <a href="/our-people/alex-singla">Alex Singla</a>, <a href="/our-people/alexander-sukharevsky">Alexander Sukharevsky</a>, <a href="/our-people/lareina-yee">Lareina Yee</a>, and <a href="/our-people/michael-chui">Michael Chui</a>, with <a href="/our-people/bryce-hall">Bryce Hall</a>, representing views from QuantumBlack, AI by McKinsey, and McKinsey Digital.</p></div></div></div></div></div></div> <p>Organizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI—most notably, inaccuracy—as well as the emerging practices of top performers to mitigate those challenges and capture value.</p> <h2 id="surging-ai-adoption">AI adoption surges</h2> <p id="intro-paragraph">Interest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in <em>any</em> region; however, this year more than two-thirds of respondents in nearly <em>every</em> region say their organizations are using AI.<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="36c8a441-bba4-47a9-9860-2c25db8b630a"><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="36c8a441-bba4-47a9-9860-2c25db8b630a" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption.</span></span></span></a></span> Looking by industry, the biggest increase in adoption can be found in professional services.<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="b46a79b2-bb94-4b60-b6ca-ab7084adb850"><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="b46a79b2-bb94-4b60-b6ca-ab7084adb850" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">Includes respondents working for organizations focused on human resources, legal services, management consulting, market research, R&D, tax preparation, and training.</span></span></span></a></span></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> 1</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/2024/stateofai-ex-1.svgz?cq=50&cpy=Center"/><img alt="Al adoption worldwide has increased dramatically in the past year, after years of little meaningful change." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-1.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>Also, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).</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> 2</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/2024/stateofai-ex-2.svgz?cq=50&cpy=Center"/><img alt="Survey findings suggest that organizations are using AI in more business functions now than in previous years." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-2.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <div data-component="mdc-c-module-wrapper" data-module-theme="default" data-module-background="transparent" data-module-category="" class="mck-c-disruptor1up mck-o-md-center mck-u-inline-module-border-top mck-u-inline-module-border-bottom mck-u-screen-only" data-layer-region="disruptor-1up"><div class="mdc-u-grid mdc-u-grid-gutter-md mdc-u-grid-col-lg-12 mdc-u-grid-col-md-12 "><div class="mdc-u-grid-col-lg-span-4 mdc-u-grid-col-md-span-5 Disruptor1Up_mck-c-disruptor1up__image___2Gc4"><picture data-component="mdc-c-picture"><img alt="McKinsey at COP29" src="/~/media/mckinsey/business%20functions/sustainability/how%20we%20help%20clients/cop/cop29/cop_29_thumb.jpg?cq=50&mh=145&car=16:9&cpy=Center" loading="lazy"/></picture></div><div class="mdc-u-grid-col-lg-span-8 mdc-u-grid-col-md-span-7"><header data-component="mdc-c-header" class="mdc-c-header"><div class="mdc-c-header__block___i1Lg-_2734c4f"><h3 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f"><div>Explore COP29 with McKinsey</div></h3><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-7"><p><div>Join our series of dynamic virtual events during COP29. Discover new research, practical strategies, and collaborations across sectors to move climate action beyond why to how.</div></p></div></div></header><div data-component="mdc-c-link-container" class="mdc-c-link-container___xefGu_2734c4f mdc-c-link-container--display-column___X0HDD_2734c4f mck-c-disruptor1up__content Disruptor1Up_mck-c-disruptor1up__content--links__VV4lE mdc-u-grid-gutter-md"><a data-component="mdc-c-link" href="https://mckinsey.cventevents.com/Q2MVE1?rt=RrQJ1iBSfEiqSK7N9VAGCw&RefId=cop" class="mdc-c-link-cta___NBQVi_2734c4f" target="_blank"><span class="mdc-c-link__label___Pfqtd_2734c4f">Register</span><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mck-external-icon"></span></a></div></div></div></div> <h3>Gen AI adoption is most common in the functions where it can create the most value</h3> <p>Most respondents now report that their organizations—and they as individuals—are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development—two functions in which <a href="/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier">previous research</a> determined that gen AI adoption could generate the most value<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="19702be0-f24a-44a1-8332-8ce88c5ea077"><sup class="FootNote_footnotesup__e73z_">3</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="19702be0-f24a-44a1-8332-8ce88c5ea077" 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>—as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.</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> 3</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/2024/stateofai-ex-3.svgz?cq=50&cpy=Center"/><img alt="Respondents most often report generative AI adoption in their marketing- and-sales, product- and service-development, and IT functions." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-3.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p>Gen AI also is weaving its way into respondents’ personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.</p>  <h3>Investments in gen AI and analytical AI are beginning to create value</h3> <p>The latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents—67 percent—expect their organizations to invest more in AI over the next three years.</p>  <p>Where are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations—in line with what we found <a href="/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year">last year</a>—as well as meaningful revenue increases from AI use in marketing and sales.</p>   <div class="nav-bar-anchor" id="surging-ai-adoption-bottom"> </div> <h2 id="the-risks-of-gen-ai-use">Inaccuracy: The most recognized and experienced risk of gen AI use</h2> <p>As businesses begin to see the benefits of gen AI, they’re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.</p> <div data-component="mdc-c-module-wrapper" data-module-theme="light" data-module-background="white" data-module-category="" class="mck-o-edge-to-edge mdc-u-container-padding-primary mdc-u-container-margin-primary mck-c-module-wrapper mck-c-default-scrolly DefaultScrolly_mck-c-default-scrolly--top-spaced__FZxVL" data-module-name="scrolly-container"><div class="mck-o-container"><div class="mck-o-container--wrapped"><div class="DefaultScrolly_mck-c-default-scrolly__scrolly-content__a5dCJ DefaultScrolly_mck-c-default-scrolly__scrolly-content--three-columns__Yxplk"><div class="DefaultScrolly_mck-c-default-scrolly__scrolly-text-content__epRca mck-o-container--mobile-spacing"><div class="DefaultScrolly_mck-c-default-scrolly__text-container__YYFld"><div class="DefaultScrolly_mck-c-default-scrolly__content-text__lFvee mck-c-default-scrolly__content-text--three-columns text-content-5D5968D895AC4C08A76026F546C45C1A" data-id="D2ED8F013ED84D51A998844EFEBD7C2C" data-react-scrollama-id="react-scrollama-0"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-5"></h2><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p>Respondents to the latest survey are more likely than they were last year to say their organizations consider inaccuracy and IP infringement to be relevant to their use of gen AI, and about half continue to view cybersecurity as a risk (Exhibit 7).</p></div></div></div></div><div class="DefaultScrolly_mck-c-default-scrolly__content-text__lFvee mck-c-default-scrolly__content-text--three-columns text-content-5D5968D895AC4C08A76026F546C45C1A" data-id="2651538352884A8589488B79A478F83B" data-react-scrollama-id="react-scrollama-1"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-5"></h2><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p>Conversely, respondents are less likely than they were last year to say their organizations consider workforce and labor displacement to be relevant risks and are not increasing efforts to mitigate them.</p></div></div></div></div><div class="DefaultScrolly_mck-c-default-scrolly__content-text__lFvee mck-c-default-scrolly__content-text--three-columns text-content-5D5968D895AC4C08A76026F546C45C1A" data-id="3183A83BBDA0459D98AD375B5AEE6034" data-react-scrollama-id="react-scrollama-2"><div data-component="mdc-c-content-block" class="mdc-c-content-block___7p6Lu_2734c4f mdc-u-grid-gutter-md"><h2 data-component="mdc-c-heading" class="mdc-c-heading___0fM1W_2734c4f mdc-u-ts-5"></h2><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-8 mck-u-links-inline"><div><p>In fact, inaccuracy—<a href="/capabilities/risk-and-resilience/our-insights/implementing-generative-ai-with-speed-and-safety">which can affect use cases across the gen AI value chain</a>, ranging from customer journeys and summarization to coding and creative content—is the only risk that respondents are significantly more likely than last year to say their organizations are actively working to mitigate.</p></div></div></div></div></div></div><div class="DefaultScrolly_mck-c-default-scrolly__scrolly-media-content__PFuk7" data-module-background="white" data-module-theme="light"><div class="DefaultScrolly_mck-c-default-scrolly__container-sticky__vuA_2"><div class="media-container-5D5968D895AC4C08A76026F546C45C1A DefaultScrolly_mck-c-default-scrolly__media-container__IFEZ5"><div class="Eyebrow_mck-c-eyebrow__3dW_H mdc-u-ts-10 DefaultScrolly_mck-c-default-scrolly__eyebrow-text__S__6f mdc-u-mt-2 mdc-u-mb-4"><span>Exhibit 7 </span></div><div class="DefaultScrolly_mck-c-default-scrolly__media__7OJZA DefaultScrolly_mck-c-default-scrolly__media--visible__hDr4Z DefaultScrolly_mck-c-default-scrolly__media--eyebrow__hasWB mck-u-animation-fade-in"><picture data-component="mdc-c-picture"><img alt="Inaccuracy and intellectual property infringement are increasingly considered relevant risks to organizations’ generative AI use. (2 of 4)" src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-7b.svgz?cq=50&cpy=Center" loading="eager"/></picture><div class="mck-u-sr-only"></div></div><div class="DefaultScrolly_mck-c-default-scrolly__media__7OJZA DefaultScrolly_mck-c-default-scrolly__media--eyebrow__hasWB mck-u-animation-fade-out"><picture data-component="mdc-c-picture"><img alt="Inaccuracy and intellectual property infringement are increasingly considered relevant risks to organizations’ generative AI use. (3 of 4)" src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-7c.svgz?cq=50&cpy=Center" loading="eager"/></picture><div class="mck-u-sr-only"></div></div><div class="DefaultScrolly_mck-c-default-scrolly__media__7OJZA DefaultScrolly_mck-c-default-scrolly__media--eyebrow__hasWB mck-u-animation-fade-out"><picture data-component="mdc-c-picture"><img alt="Inaccuracy and intellectual property infringement are increasingly considered relevant risks to organizations’ generative AI use. (4 of 4)" src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-7d.svgz?cq=50&cpy=Center" loading="eager"/></picture><div class="mck-u-sr-only"></div></div></div></div></div></div></div></div></div> <p>Some organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.</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> 8</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/2024/stateofai-ex-8.svgz?cq=50&cpy=Center"/><img alt="Nearly one-quarter of respondents say their organizations have experienced negative consequences from generative AI’s inaccuracy." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-8.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <p><a href="/capabilities/risk-and-resilience/our-insights/implementing-generative-ai-with-speed-and-safety">Our previous research</a> has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place.<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="4ccf406c-1b28-4e5e-90ec-138dcd6679d9"><sup class="FootNote_footnotesup__e73z_">4</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="4ccf406c-1b28-4e5e-90ec-138dcd6679d9" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">“<a href="/capabilities/risk-and-resilience/our-insights/implementing-generative-ai-with-speed-and-safety">Implementing generative AI with speed and safety</a>,” <em>McKinsey Quarterly</em>, March 13, 2024.</span></span></span></a></span> For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.</p>  <div class="nav-bar-anchor" id="the-risks-of-gen-ai-use-bottom"> </div> <h2 id="bringing-gen-ai-capabilities-to-bear">Bringing gen AI capabilities to bear</h2> <p>The latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found <a href="/capabilities/mckinsey-digital/our-insights/technologys-generational-moment-with-generative-ai-a-cio-and-cto-guide">three archetypes for implementing gen AI solutions</a>: <em>takers</em> use off-the-shelf, publicly available solutions; <em>shapers</em> customize those tools with proprietary data and systems; and <em>makers</em> develop their own foundation models from scratch.<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="322d928f-1d92-4b64-822a-d5213dfe1d5b"><sup class="FootNote_footnotesup__e73z_">5</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="322d928f-1d92-4b64-822a-d5213dfe1d5b" aria-hidden="true" data-module-theme="light" class="FootNote_footnote-text__VjKgO mck-u-links-inline">“<a href="/capabilities/mckinsey-digital/our-insights/technologys-generational-moment-with-generative-ai-a-cio-and-cto-guide">Technology’s generational moment with generative AI: A CIO and CTO guide</a>,” McKinsey, July 11, 2023.</span></span></span></a></span> Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs—though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents’ business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.</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> 9</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/2024/stateofai-ex-9.svgz?cq=50&cpy=Center"/><img alt="Organizations are pursuing a mix of off-the-shelf generative AI capabilities and also significantly customizing models or developing their own." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-9.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div>  <p>Respondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.</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> 10</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/2024/stateofai-ex-10.svgz?cq=50&cpy=Center"/><img alt="Business functions are most often able to put their generative AI capabilities to use within one to four months." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-10.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div>  <div class="nav-bar-anchor" id="bringing-gen-ai-capabilities-to-bear-bottom"> </div> <h2 id="the-practices-of-gen-ai-high-performers">Gen AI high performers are excelling despite facing challenges</h2> <p>Gen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it’s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations’ EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations’ EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions—though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.</p> <p>To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they’re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.</p> <p>What else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.</p> <p>Gen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions—that is, to “<a href="/about-us/new-at-mckinsey-blog/an-inside-look-at-how-businesses-are-or-not-managing-ai-risk">shift left</a>.” They’re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.</p>  <p>In addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.</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> 12</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/2024/stateofai-ex-12.svgz?cq=50&cpy=Center"/><img alt="Generative AI high performers report experiencing a range of challenges in capturing value from the technology." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/the%20state%20of%20ai/2024/stateofai-ex-12.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div>  <div class="nav-bar-anchor" id="the-practices-of-gen-ai-high-performers-bottom"> </div> <h2 id="about-the-research">About the research</h2> <p>The online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. To adjust for differences in response rates, the data are weighted by the contribution of each respondent’s nation to global GDP.</p> <div class="nav-bar-anchor" id="about-the-research-bottom"> </div></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><strong><a href="/our-people/alex-singla">Alex Singla</a></strong> and <strong><a href="/our-people/alexander-sukharevsky">Alexander Sukharevsky</a></strong> are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey’s Chicago and London offices, respectively; <strong><a href="/our-people/lareina-yee">Lareina Yee</a></strong> is a senior partner in the Bay Area office, where <strong>Michael Chui,</strong> a McKinsey Global Institute partner, is a partner; and <strong><a href="/our-people/bryce-hall">Bryce Hall</a></strong> is an associate partner in the Washington, DC, office.</p> <p>They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.</p> <hr> <p>This article was edited by Heather Hanselman, a senior editor in McKinsey’s 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="/capabilities/mckinsey-digital/our-insights/moving-past-gen-ais-honeymoon-phase-seven-hard-truths-for-cios-to-get-from-pilot-to-scale" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-movin-0 { aspect-ratio: 16/9 }</style><img alt="One large blue ball in mid air above many smaller blue, green, purple and white balls" class="picture-uniqueKey-movin-0" src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/moving%20past%20gen%20ais%20honeymoon%20phase%20seven%20hard%20truths%20for%20cios/thumb-gettyimages-1551147077.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/mckinsey-digital/our-insights/moving-past-gen-ais-honeymoon-phase-seven-hard-truths-for-cios-to-get-from-pilot-to-scale" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>Moving past gen AI’s honeymoon phase: Seven hard truths for CIOs to get from pilot to scale</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/mckinsey-digital/our-insights/a-generative-ai-reset-rewiring-to-turn-potential-into-value-in-2024" class="mdc-c-link___lBbY1_2734c4f"><picture data-component="mdc-c-picture" class="Card_wrapper-image__8b4P6"><style>.picture-uniqueKey-agen-0 { aspect-ratio: 16/9 }</style><img alt="A thumb and an index finger form a circular void, resembling the shape of a light bulb but without the glass component. 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A small group of high performers lead the way."}},"sEODescription":{"value":"In this latest analysis, we look at the state of AI in early 2024 and new trends and patterns that are emerging in the wake of growing gen AI adoption."},"displayDate":{"jsonValue":{"value":"2024-05-30T00:00:00Z"}},"body":{"value":"[[Audio 1]]\n[[BespokeInteractive 1]]\n[[DownloadsSidebar]]\n\u003cp\u003e\u003cstrong\u003eIf 2023\u003c/strong\u003e was the year the world discovered \u003ca href=\"/featured-insights/mckinsey-explainers/what-is-generative-ai\"\u003egenerative AI (gen AI)\u003c/a\u003e, 2024 is the year organizations truly began using\u0026mdash;and deriving business value from\u0026mdash;this new technology. In the latest \u003ca href=\"/featured-insights/mckinsey-global-surveys\"\u003eMcKinsey Global Survey\u003c/a\u003e\u0026nbsp;on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents\u0026rsquo; expectations for gen AI\u0026rsquo;s impact remain as high \u003ca href=\"/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year\"\u003eas they were last year\u003c/a\u003e, with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead.\u003c/p\u003e\n[[Sidebar authors]]\n\u003cp\u003eOrganizations are already seeing material benefits from gen AI use, reporting both cost decreases and revenue jumps in the business units deploying the technology. The survey also provides insights into the kinds of risks presented by gen AI\u0026mdash;most notably, inaccuracy\u0026mdash;as well as the emerging practices of top performers to mitigate those challenges and capture value.\u003c/p\u003e\n\u003ch2 id=\"surging-ai-adoption\"\u003eAI adoption surges\u003c/h2\u003e\n\u003cp id=\"intro-paragraph\"\u003eInterest in generative AI has also brightened the spotlight on a broader set of AI capabilities. For the past six years, AI adoption by respondents\u0026rsquo; organizations has hovered at about 50 percent. This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest is truly global in scope. Our 2023 survey found that AI adoption did not reach 66 percent in \u003cem\u003eany\u003c/em\u003e region; however, this year more than two-thirds of respondents in nearly \u003cem\u003eevery\u003c/em\u003e region say their organizations are using AI.[[footnote 1]] Looking by industry, the biggest increase in adoption can be found in professional services.[[footnote 2]]\u003c/p\u003e\n[[Exhibit 1]]\n\u003cp\u003eAlso, responses suggest that companies are now using AI in more parts of the business. Half of respondents say their organizations have adopted AI in two or more business functions, up from less than a third of respondents in 2023 (Exhibit 2).\u003c/p\u003e\n[[Exhibit 2]]\n[[disruptor1up cop]]\n\u003ch3\u003eGen AI adoption is most common in the functions where it can create the most value\u003c/h3\u003e\n\u003cp\u003eMost respondents now report that their organizations\u0026mdash;and they as individuals\u0026mdash;are using gen AI. Sixty-five percent of respondents say their organizations are regularly using gen AI in at least one business function, up from one-third last year. The average organization using gen AI is doing so in two functions, most often in marketing and sales and in product and service development\u0026mdash;two functions in which \u003ca href=\"/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier\"\u003eprevious research\u003c/a\u003e\u0026nbsp;determined that gen AI adoption could generate the most value[[footnote 3]]\u0026mdash;as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing and sales, where reported adoption has more than doubled. Yet across functions, only two use cases, both within marketing and sales, are reported by 15 percent or more of respondents.\u003c/p\u003e\n[[Exhibit 3]]\n\u003cp\u003eGen AI also is weaving its way into respondents\u0026rsquo; personal lives. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia\u0026ndash;Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers. Looking at specific industries, respondents working in energy and materials and in professional services report the largest increase in gen AI use.\u003c/p\u003e\n[[Ceros Ex4]]\n\u003ch3\u003eInvestments in gen AI and analytical AI are beginning to create value\u003c/h3\u003e\n\u003cp\u003eThe latest survey also shows how different industries are budgeting for gen AI. Responses suggest that, in many industries, organizations are about equally as likely to be investing more than 5 percent of their digital budgets in gen AI as they are in nongenerative, analytical-AI solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI. Looking ahead, most respondents\u0026mdash;67 percent\u0026mdash;expect their organizations to invest more in AI over the next three years.\u003c/p\u003e\n[[Ceros Ex5]]\n\u003cp\u003eWhere are those investments paying off? For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6). For analytical AI, respondents most often report seeing cost benefits in service operations\u0026mdash;in line with what we found \u003ca href=\"/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year\"\u003elast year\u003c/a\u003e\u0026mdash;as well as meaningful revenue increases from AI use in marketing and sales.\u003c/p\u003e\n[[Ceros Ex6]]\n[[Ceros AlexSingla]]\n\u003cdiv id=\"surging-ai-adoption-bottom\" class=\"nav-bar-anchor\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ch2 id=\"the-risks-of-gen-ai-use\"\u003eInaccuracy: The most recognized and experienced risk of gen AI use\u003c/h2\u003e\n\u003cp\u003eAs businesses begin to see the benefits of gen AI, they\u0026rsquo;re also recognizing the diverse risks associated with the technology. These can range from data management risks such as data privacy, bias, or intellectual property (IP) infringement to model management risks, which tend to focus on inaccurate output or lack of explainability. A third big risk category is security and incorrect use.\u003c/p\u003e\n[[Scrolly Ex7]]\n\u003cp\u003eSome organizations have already experienced negative consequences from the use of gen AI, with 44 percent of respondents saying their organizations have experienced at least one consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected their organizations, followed by cybersecurity and explainability.\u003c/p\u003e\n[[Exhibit 8]]\n\u003cp\u003e\u003ca href=\"/capabilities/risk-and-resilience/our-insights/implementing-generative-ai-with-speed-and-safety\"\u003eOur previous research\u003c/a\u003e has found that there are several elements of governance that can help in scaling gen AI use responsibly, yet few respondents report having these risk-related practices in place.[[footnote 4]] For example, just 18 percent say their organizations have an enterprise-wide council or board with the authority to make decisions involving responsible AI governance, and only one-third say gen AI risk awareness and risk mitigation controls are required skill sets for technical talent.\u003c/p\u003e\n[[Ceros LareinaYee]]\n\u003cdiv id=\"the-risks-of-gen-ai-use-bottom\" class=\"nav-bar-anchor\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ch2 id=\"bringing-gen-ai-capabilities-to-bear\"\u003eBringing gen AI capabilities to bear\u003c/h2\u003e\n\u003cp\u003eThe latest survey also sought to understand how, and how quickly, organizations are deploying these new gen AI tools. We have found \u003ca href=\"/capabilities/mckinsey-digital/our-insights/technologys-generational-moment-with-generative-ai-a-cio-and-cto-guide\"\u003ethree archetypes for implementing gen AI solutions\u003c/a\u003e: \u003cem\u003etakers\u003c/em\u003e use off-the-shelf, publicly available solutions; \u003cem\u003eshapers\u003c/em\u003e customize those tools with proprietary data and systems; and \u003cem\u003emakers\u003c/em\u003e develop their own foundation models from scratch.[[footnote 5]] Across most industries, the survey results suggest that organizations are finding off-the-shelf offerings applicable to their business needs\u0026mdash;though many are pursuing opportunities to customize models or even develop their own (Exhibit 9). About half of reported gen AI uses within respondents\u0026rsquo; business functions are utilizing off-the-shelf, publicly available models or tools, with little or no customization. Respondents in energy and materials, technology, and media and telecommunications are more likely to report significant customization or tuning of publicly available models or developing their own proprietary models to address specific business needs.\u003c/p\u003e\n[[Exhibit 9]]\n[[Ceros AlexSukharevsky]]\n\u003cp\u003eRespondents most often report that their organizations required one to four months from the start of a project to put gen AI into production, though the time it takes varies by business function (Exhibit 10). It also depends upon the approach for acquiring those capabilities. Not surprisingly, reported uses of highly customized or proprietary models are 1.5 times more likely than off-the-shelf, publicly available models to take five months or more to implement.\u003c/p\u003e\n[[Exhibit 10]]\n[[Ceros MichaelChui]]\n\u003cdiv id=\"bringing-gen-ai-capabilities-to-bear-bottom\" class=\"nav-bar-anchor\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ch2 id=\"the-practices-of-gen-ai-high-performers\"\u003eGen AI high performers are excelling despite facing challenges\u003c/h2\u003e\n\u003cp\u003eGen AI is a new technology, and organizations are still early in the journey of pursuing its opportunities and scaling it across functions. So it\u0026rsquo;s little surprise that only a small subset of respondents (46 out of 876) report that a meaningful share of their organizations\u0026rsquo; EBIT can be attributed to their deployment of gen AI. Still, these gen AI leaders are worth examining closely. These, after all, are the early movers, who already attribute more than 10 percent of their organizations\u0026rsquo; EBIT to their use of gen AI. Forty-two percent of these high performers say more than 20 percent of their EBIT is attributable to their use of nongenerative, analytical AI, and they span industries and regions\u0026mdash;though most are at organizations with less than $1 billion in annual revenue. The AI-related practices at these organizations can offer guidance to those looking to create value from gen AI adoption at their own organizations.\u003c/p\u003e\n\u003cp\u003eTo start, gen AI high performers are using gen AI in more business functions\u0026mdash;an average of three functions, while others average two. They, like other organizations, are most likely to use gen AI in marketing and sales and product or service development, but they\u0026rsquo;re much more likely than others to use gen AI solutions in risk, legal, and compliance; in strategy and corporate finance; and in supply chain and inventory management. They\u0026rsquo;re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R\u0026amp;D testing and pricing and promotions. While, overall, about half of reported gen AI applications within business functions are utilizing publicly available models or tools, gen AI high performers are less likely to use those off-the-shelf options than to either implement significantly customized versions of those tools or to develop their own proprietary foundation models.\u003c/p\u003e\n\u003cp\u003eWhat else are these high performers doing differently? For one thing, they are paying more attention to gen-AI-related risks. Perhaps because they are further along on their journeys, they are more likely than others to say their organizations have experienced every negative consequence from gen AI we asked about, from cybersecurity and personal privacy to explainability and IP infringement. Given that, they are more likely than others to report that their organizations consider those risks, as well as regulatory compliance, environmental impacts, and political stability, to be relevant to their gen AI use, and they say they take steps to mitigate more risks than others do.\u003c/p\u003e\n\u003cp\u003eGen AI high performers are also much more likely to say their organizations follow a set of risk-related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve the legal function and embed risk reviews early on in the development of gen AI solutions\u0026mdash;that is, to \u0026ldquo;\u003ca href=\"/about-us/new-at-mckinsey-blog/an-inside-look-at-how-businesses-are-or-not-managing-ai-risk\"\u003eshift left\u003c/a\u003e.\u0026rdquo; They\u0026rsquo;re also much more likely than others to employ a wide range of other best practices, from strategy-related practices to those related to scaling.\u003c/p\u003e\n[[Ceros Ex11]]\n\u003cp\u003eIn addition to experiencing the risks of gen AI adoption, high performers have encountered other challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value. High performers are also more likely than others to report experiencing challenges with their operating models, such as implementing agile ways of working and effective sprint performance management.\u003c/p\u003e\n[[Exhibit 12]]\n[[Ceros BryceHall]]\n\u003cdiv id=\"the-practices-of-gen-ai-high-performers-bottom\" class=\"nav-bar-anchor\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ch2 id=\"about-the-research\"\u003eAbout the research\u003c/h2\u003e\n\u003cp\u003eThe online survey was in the field from February 22 to March 5, 2024, and garnered responses from 1,363 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. Of those respondents, 981 said their organizations had adopted AI in at least one business function, and 878 said their organizations were regularly using gen AI in at least one function. 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\n\u003cdiv id=\"about-the-research-bottom\" class=\"nav-bar-anchor\"\u003e\u0026nbsp;\u003c/div\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":false},"forClientsOnly":{"boolValue":false},"excludeFromClientLink":{"boolValue":false},"originalPublishDate":{"jsonValue":{"value":"2024-05-30T00:00:00Z"}},"footnotes":{"value":"\u003col\u003e\n \u003cli\u003eOrganizations based in Central and South America are the exception, with 58 percent of respondents working for organizations based in Central and South America reporting AI adoption.\u003c/li\u003e\n \u003cli\u003eIncludes respondents working for organizations focused on human resources, legal services, management consulting, market research, R\u0026amp;D, tax preparation, and training.\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 \u003cli\u003e\u0026ldquo;\u003ca href=\"/capabilities/risk-and-resilience/our-insights/implementing-generative-ai-with-speed-and-safety\"\u003eImplementing generative AI with speed and safety\u003c/a\u003e,\u0026rdquo; \u003cem\u003eMcKinsey Quarterly\u003c/em\u003e, March 13, 2024.\u003c/li\u003e\n \u003cli\u003e\u0026ldquo;\u003ca href=\"/capabilities/mckinsey-digital/our-insights/technologys-generational-moment-with-generative-ai-a-cio-and-cto-guide\"\u003eTechnology\u0026rsquo;s generational moment with generative AI: A CIO and CTO guide\u003c/a\u003e,\u0026rdquo; McKinsey, July 11, 2023.\u003c/li\u003e\n\u003c/ol\u003e"},"contributoryPractice":{"targetItems":[{"displayName":"QuantumBlack, AI by McKinsey"},{"displayName":"McKinsey Digital"}]},"aboutTheAuthors":{"value":"\u003cp\u003e\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\u0026nbsp;are global coleaders of QuantumBlack, AI by McKinsey, and senior partners in McKinsey\u0026rsquo;s Chicago and London offices, respectively; \u003cstrong\u003e\u003ca href=\"/our-people/lareina-yee\"\u003eLareina Yee\u003c/a\u003e\u003c/strong\u003e\u0026nbsp;is a senior partner in the Bay Area office, where \u003cstrong\u003eMichael Chui,\u003c/strong\u003e a McKinsey Global Institute partner, is a partner; and \u003cstrong\u003e\u003ca href=\"/our-people/bryce-hall\"\u003eBryce Hall\u003c/a\u003e\u003c/strong\u003e\u0026nbsp;is an associate partner in the Washington, DC, office.\u003c/p\u003e\n\u003cp\u003eThey wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.\u003c/p\u003e\n\u003chr\u003e\n\u003cp\u003eThis article was edited by Heather Hanselman, a senior editor in McKinsey\u0026rsquo;s Atlanta office.\u003c/p\u003e"},"authors":{"targetItems":[{"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; 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