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How generative AI & ChatGPT will change business | McKinsey
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How tools like ChatGPT could change your business</div></h1></div><div data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-10 mck-u-animation-blur-in-800 ArticleDefault_mck-c-article-default__description__sjoe9"><div><time datetime="2022-12-20T00:00:00Z">December 20, 2022</time> | Commentary</div></div></div></div></div></div></div><div class="mck-o-container"><div class="mck-o-container--wrapped mck-o-container--mobile-spacing mdc-u-grid mdc-u-grid-gutter-xxl"><section data-layer-region="article-body-header" class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-animation-blur-in-400 byline-share-container"><div class="mdc-u-grid-col-md-start-2 mdc-u-grid-col-md-end-8 mdc-u-grid-col-lg-start-3 mdc-u-grid-col-lg-end-8 mdc-u-ts-9"><span> </span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/michael-chui" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Michael Chui</span></a> </span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/roger-roberts" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Roger Roberts</span></a><span> </span></span></span><span class="AuthorsByLine_mck-c-authors-byline__author__XdrlD"><span class="AuthorsByLine_mck-c-authors-byline__no-wrap__Ced0j"><a data-component="mdc-c-link" href="/our-people/lareina-yee" class="mdc-c-link-inline___7DRrt_2734c4f mdc-c-link-inline--secondary___YKoOK_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Lareina Yee</span></a></span></span></div><div class="mdc-u-grid-col-md-start-8 mdc-u-grid-col-md-end-12 mdc-u-grid-col-lg-start-8 mdc-u-grid-col-lg-end-11 ArticleContent_mck-c-article-content__share-tools__kWRRw"></div></section><section class="mdc-u-grid mdc-u-grid-col-md-12 mck-u-animation-blur-in-400"><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 data-component="mdc-c-description" class="mdc-c-description___SrnQP_2734c4f mdc-u-ts-5"><div class="mck-u-links-inline">Generative AI and other foundation models are changing the AI game, taking assistive technology to a new level, reducing application development time, and bringing powerful capabilities to nontechnical users.</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 class="mck-o-sidebar mck-o-xs-right-span"><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%2Fgenerative%20ai%20is%20here%20how%20tools%20like%20chatgpt%20could%20change%20your%20business%2Fgenerative-ai-is-here-how-tools-like-chatgpt-could-change-your-business.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="generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business" data-layer-report-name="generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business>"><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"> (5 pages)</span></a></div></div></div></div></div> <p><strong>In the spirit of</strong> this article’s topic, we asked ChatGPT—a generative AI language model that can create original content in response to a user prompt—how it would set the context. Our prompt to the system:</p> <blockquote> <p>Write the opening paragraph for an article about how transformative <a href="/featured-insights/mckinsey-explainers/what-is-generative-ai">generative AI</a> will be for business, in the style of McKinsey & Company.</p> </blockquote> <p>ChatGPT’s response:</p> <blockquote> <p>The rise of generative AI has the potential to be a major game-changer for businesses. This technology, which allows for the creation of original content by learning from existing data, has the power to revolutionize industries and transform the way companies operate. By enabling the automation of many tasks that were previously done by humans, generative AI has the potential to increase efficiency and productivity, reduce costs, and open up new opportunities for growth. As such, businesses that are able to effectively leverage the technology are likely to gain a significant competitive advantage.</p> </blockquote> <p>Not perfect but overwhelmingly impressive.</p> <p>For us and many executives we’ve spoken to recently, entering one prompt into ChatGPT, developed by OpenAI, was all it took to see the power of generative AI. In the first five days of its release, more than a million users logged into the platform to experience it for themselves. OpenAI’s servers can barely keep up with demand, regularly flashing a message that users need to return later when server capacity frees up.</p> <!-- --> <p>Products like ChatGPT and GitHub Copilot, as well as the underlying AI models that power such systems (Stable Diffusion, DALL·E 2, GPT-3, to name a few), are taking technology into realms once thought to be reserved for humans. With generative AI, computers can now arguably exhibit creativity. They can produce original content in response to queries, drawing from data they’ve ingested and interactions with users. They can develop blogs, sketch package designs, <a href="/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech-2023">write computer code</a>, or even theorize on the reason for a production error.</p> <p>This latest class of generative AI systems has emerged from foundation models—large-scale, <a href="/capabilities/quantumblack/our-insights/an-executives-guide-to-ai">deep learning models</a> trained on massive, broad, unstructured data sets (such as text and images) that cover many topics. Developers can adapt the models for a wide range of use cases, with little fine-tuning required for each task. For example, GPT-3.5, the foundation model underlying ChatGPT, has also been used to translate text, and scientists used an earlier version of GPT to create novel protein sequences. In this way, the power of these capabilities is accessible to all, including developers who lack specialized machine learning skills and, in some cases, people with no technical background. Using foundation models can also reduce the time for developing new <a href="/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review">AI applications</a> to a level rarely possible before.</p> <p>Generative AI promises to make 2023 one of the most exciting years yet for AI. But as with every new technology, business leaders must proceed with eyes wide open, because the technology today presents many ethical and practical challenges.</p> <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="Moving illustration of wavy blue lines that was produced using computer code" src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/what%20every%20ceo%20should%20know%20about%20generative%20ai/gen-ai-ceo-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>What CEOs need to know about generative AI</div></h3></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="/capabilities/quantumblack/our-insights/generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business" class="mdc-c-link-cta___NBQVi_2734c4f"><span class="mdc-c-link__label___Pfqtd_2734c4f">Read the article</span><span data-component="mdc-c-icon" class="mdc-c-icon___oi7ef_2734c4f mck-link-arrow-right-icon"></span></a></div></div></div></div> <h2>Pushing further into human realms</h2> <p>More than a decade ago, we wrote an article in which we sorted economic activity into three buckets—production, transactions, and interactions—and examined the extent to which technology had made inroads into each. Machines and factory technologies transformed production by augmenting and automating human labor during the Industrial Revolution more than 100 years ago, and AI has further amped up efficiencies on the manufacturing floor. Transactions have undergone many technological iterations over approximately the same time frame, including most recently digitization and, frequently, automation.</p> <p>Until recently, interaction labor, such as customer service, has experienced the least mature technological interventions. Generative AI is set to change that by undertaking interaction labor in a way that approximates human behavior closely and, in some cases, imperceptibly. That’s not to say these tools are intended to work without human input and intervention. In many cases, they are most powerful in combination with humans, augmenting their capabilities and enabling them to get work done faster and better.</p> <p>Generative AI is also pushing technology into a realm thought to be unique to the human mind: creativity. The technology leverages its inputs (the data it has ingested and a user prompt) and experiences (interactions with users that help it “learn” new information and what’s correct/incorrect) to generate entirely new content. While dinner table debates will rage for the foreseeable future on whether this truly equates to creativity, most would likely agree that these tools stand to unleash more creativity into the world by prompting humans with starter ideas.</p> <h2>Business uses abound</h2> <p>These models are in the early days of scaling, but we’ve started seeing the first batch of applications across functions, including the following (exhibit):</p> <ul> <li><em>Marketing and sales</em>—crafting personalized marketing, social media, and technical sales content (including text, images, and video); creating assistants aligned to specific businesses, such as retail</li> <li><em>Operations</em>—generating task lists for efficient execution of a given activity</li> <li><em>IT/engineering</em>—writing, documenting, and reviewing code</li> <li><em>Risk and legal</em>—answering complex questions, pulling from vast amounts of legal documentation, and drafting and reviewing annual reports</li> <li><em>R&D</em>—accelerating drug discovery through better understanding of diseases and discovery of chemical structures</li> </ul> <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/generative%20ai%20is%20here%20how%20tools%20like%20chatgpt%20could%20change%20your%20business/svg-chatgpt-marks-a-tipping-ex1-v3.svgz?cq=50&cpy=Center"/><img alt="There are many possible generative AI cases across the business that could create early impact." src="/~/media/mckinsey/business%20functions/quantumblack/our%20insights/generative%20ai%20is%20here%20how%20tools%20like%20chatgpt%20could%20change%20your%20business/svg-chatgpt-marks-a-tipping-ex1-v3.svgz?cq=50&cpy=Center" loading="lazy"/></picture></div><div class="mck-u-sr-only"></div></div> <h2>Excitement is warranted, but caution is required</h2> <p>The awe-inspiring results of generative AI might make it seem like a ready-set-go technology, but that’s not the case. Its nascency requires executives to proceed with an abundance of caution. Technologists are still working out the kinks, and plenty of practical and ethical issues remain open. Here are just a few:</p> <ul> <li><em>Like humans, generative AI can be wrong.</em> ChatGPT, for example, sometimes “hallucinates,” meaning it confidently generates entirely inaccurate information in response to a user question and has no built-in mechanism to signal this to the user or challenge the result. For example, we have observed instances when the tool was asked to create a short bio and it generated several incorrect facts for the person, such as listing the wrong educational institution.</li> <li><em>Filters are not yet effective enough to catch inappropriate content.</em> Users of an image-generating application that can create avatars from a person’s photo received avatar options from the system that portrayed them nude, even though they had input appropriate photos of themselves.</li> <li><em>Systemic biases still need to be addressed.</em> These systems draw from massive amounts of data that might include <a href="/capabilities/quantumblack/our-insights/getting-to-know-and-manage-your-biggest-ai-risks">unwanted biases</a>.</li> <li><em>Individual company norms and values aren’t reflected.</em> Companies will need to adapt the technology to incorporate their culture and values, an exercise that requires technical expertise and computing power beyond what some companies may have ready access to.</li> <li><em>Intellectual-property questions are up for debate.</em> When a generative AI model brings forward a new product design or idea based on a user prompt, who can lay claim to it? What happens when it plagiarizes a source based on its training data?</li> </ul> <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-md-span-12"><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>Would you like to learn more about <a href="/capabilities/quantumblack/how-we-help-clients">QuantumBlack, AI by McKinsey</a>?</div></h3></div></header></div></div></div> <h2>Initial steps for executives</h2> <p>In companies considering generative AI, executives will want to quickly identify the parts of their business where the technology could have the most immediate impact and implement a mechanism to monitor it, given that it is expected to evolve quickly. A no-regrets move is to assemble a cross-functional team, including data science practitioners, legal experts, and functional business leaders, to think through basic questions, such as these:</p> <ul> <li>Where might the technology aid or disrupt our industry and/or our business’s value chain?</li> <li>What are our policies and posture? For example, are we watchfully waiting to see how the technology evolves, investing in pilots, or looking to build a new business? Should the posture vary across areas of the business?</li> <li>Given the limitations of the models, what are our criteria for selecting use cases to target?</li> <li>How do we pursue building an effective ecosystem of partners, communities, and platforms?</li> <li>What legal and community standards should these models adhere to so we can maintain trust with our stakeholders?</li> </ul> <p>Meanwhile, it’s essential to encourage thoughtful innovation across the organization, standing up guardrails along with sandboxed environments for experimentation, many of which are readily available via the cloud, with more likely on the horizon.</p> <hr/> <p>The innovations that generative AI could ignite for businesses of all sizes and levels of technological proficiency are truly exciting. However, executives will want to remain acutely aware of the risks that exist at this early stage of the technology’s development.</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><strong><a href="/our-people/michael-chui">Michael Chui</a></strong> is a partner at the McKinsey Global Institute and a partner in McKinsey’s Bay Area office, where <strong><a href="/our-people/roger-roberts">Roger Roberts</a></strong> is a partner and <strong><a href="/our-people/lareina-yee">Lareina Yee</a></strong> is a senior partner.</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" 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src="/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/the%20top%20trends%20in%20tech%202023/techtrends-1163715561-thumb-1536x1536.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>Interactive</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/the-top-trends-in-tech-2023" class="mdc-c-link-heading___Zggl8_2734c4f mdc-c-link___lBbY1_2734c4f"><div>McKinsey Technology Trends Outlook 2023</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":"Generative AI is here How tools like ChatGPT could change your business","displayName":"Generative AI is here How tools like ChatGPT could change your business","fields":null,"databaseName":"web","deviceId":"fe5d7fdf-89c0-4d99-9aa3-b5fbd009c9f3","itemId":"738ac24d-41c1-4c89-8cca-8fcf18a6796f","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":"Generative AI is here: How tools like ChatGPT could change your business"}},"sEOTitle":{"value":"How generative AI \u0026amp; ChatGPT will change business"},"description":{"jsonValue":{"value":"Generative AI and other foundation models are changing the AI game, taking assistive technology to a new level, reducing application development time, and bringing powerful capabilities to nontechnical users."}},"sEODescription":{"value":"In this article, we look at how ChatGPT and other generative AI tools are reshaping the business world and bringing powerful capabilities to nontechnical users."},"displayDate":{"jsonValue":{"value":"2022-12-20T00:00:00Z"}},"body":{"value":"[[audio 1]]\n[[DownloadsSidebar]]\n[[MostPopularArticles 5]]\n\u003cp\u003e\u003cstrong\u003eIn the spirit of\u003c/strong\u003e this article\u0026rsquo;s topic, we asked ChatGPT\u0026mdash;a generative AI language model that can create original content in response to a user prompt\u0026mdash;how it would set the context. Our prompt to the system:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003eWrite the opening paragraph for an article about how transformative \u003ca href=\"/featured-insights/mckinsey-explainers/what-is-generative-ai\"\u003egenerative AI\u003c/a\u003e will be for business, in the style of McKinsey \u0026amp; Company.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp\u003eChatGPT\u0026rsquo;s response:\u003c/p\u003e\n\u003cblockquote\u003e\n\u003cp\u003eThe rise of generative AI has the potential to be a major game-changer for businesses. This technology, which allows for the creation of original content by learning from existing data, has the power to revolutionize industries and transform the way companies operate. By enabling the automation of many tasks that were previously done by humans, generative AI has the potential to increase efficiency and productivity, reduce costs, and open up new opportunities for growth. As such, businesses that are able to effectively leverage the technology are likely to gain a significant competitive advantage.\u003c/p\u003e\n\u003c/blockquote\u003e\n\u003cp\u003eNot perfect but overwhelmingly impressive.\u003c/p\u003e\n\u003cp\u003eFor us and many executives we\u0026rsquo;ve spoken to recently, entering one prompt into ChatGPT, developed by OpenAI, was all it took to see the power of generative AI. In the first five days of its release, more than a million users logged into the platform to experience it for themselves. OpenAI\u0026rsquo;s servers can barely keep up with demand, regularly flashing a message that users need to return later when server capacity frees up.\u003c/p\u003e\n[[Ceros Q]]\n\u003cp\u003eProducts like ChatGPT and GitHub Copilot, as well as the underlying AI models that power such systems (Stable Diffusion, DALL\u0026middot;E 2, GPT-3, to name a few), are taking technology into realms once thought to be reserved for humans. With generative AI, computers can now arguably exhibit creativity. They can produce original content in response to queries, drawing from data they\u0026rsquo;ve ingested and interactions with users. They can develop blogs, sketch package designs, \u003ca href=\"/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech-2023\"\u003ewrite computer code\u003c/a\u003e, or even theorize on the reason for a production error.\u003c/p\u003e\n\u003cp\u003eThis latest class of generative AI systems has emerged from foundation models\u0026mdash;large-scale, \u003ca href=\"/capabilities/quantumblack/our-insights/an-executives-guide-to-ai\"\u003edeep learning models\u003c/a\u003e trained on massive, broad, unstructured data sets (such as text and images) that cover many topics. Developers can adapt the models for a wide range of use cases, with little fine-tuning required for each task. For example, GPT-3.5, the foundation model underlying ChatGPT, has also been used to translate text, and scientists used an earlier version of GPT to create novel protein sequences. In this way, the power of these capabilities is accessible to all, including developers who lack specialized machine learning skills and, in some cases, people with no technical background. Using foundation models can also reduce the time for developing new \u003ca href=\"/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review\"\u003eAI applications\u003c/a\u003e to a level rarely possible before.\u003c/p\u003e\n\u003cp\u003eGenerative AI promises to make 2023 one of the most exciting years yet for AI. But as with every new technology, business leaders must proceed with eyes wide open, because the technology today presents many ethical and practical challenges.\u003c/p\u003e\n[[disruptor1up 1]]\n\u003ch2\u003ePushing further into human realms\u003c/h2\u003e\n\u003cp\u003eMore than a decade ago, we wrote an article in which we sorted economic activity into three buckets\u0026mdash;production, transactions, and interactions\u0026mdash;and examined the extent to which technology had made inroads into each. Machines and factory technologies transformed production by augmenting and automating human labor during the Industrial Revolution more than 100 years ago, and AI has further amped up efficiencies on the manufacturing floor. Transactions have undergone many technological iterations over approximately the same time frame, including most recently digitization and, frequently, automation.\u003c/p\u003e\n\u003cp\u003eUntil recently, interaction labor, such as customer service, has experienced the least mature technological interventions. Generative AI is set to change that by undertaking interaction labor in a way that approximates human behavior closely and, in some cases, imperceptibly. That\u0026rsquo;s not to say these tools are intended to work without human input and intervention. In many cases, they are most powerful in combination with humans, augmenting their capabilities and enabling them to get work done faster and better.\u003c/p\u003e\n\u003cp\u003eGenerative AI is also pushing technology into a realm thought to be unique to the human mind: creativity. The technology leverages its inputs (the data it has ingested and a user prompt) and experiences (interactions with users that help it \u0026ldquo;learn\u0026rdquo; new information and what\u0026rsquo;s correct/incorrect) to generate entirely new content. While dinner table debates will rage for the foreseeable future on whether this truly equates to creativity, most would likely agree that these tools stand to unleash more creativity into the world by prompting humans with starter ideas.\u003c/p\u003e\n\u003ch2\u003eBusiness uses abound\u003c/h2\u003e\n\u003cp\u003eThese models are in the early days of scaling, but we\u0026rsquo;ve started seeing the first batch of applications across functions, including the following (exhibit):\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eMarketing and sales\u003c/em\u003e\u0026mdash;crafting personalized marketing, social media, and technical sales content (including text, images, and video); creating assistants aligned to specific businesses, such as retail\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eOperations\u003c/em\u003e\u0026mdash;generating task lists for efficient execution of a given activity\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eIT/engineering\u003c/em\u003e\u0026mdash;writing, documenting, and reviewing code\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eRisk and legal\u003c/em\u003e\u0026mdash;answering complex questions, pulling from vast amounts of legal documentation, and drafting and reviewing annual reports\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eR\u0026amp;D\u003c/em\u003e\u0026mdash;accelerating drug discovery through better understanding of diseases and discovery of chemical structures\u003c/li\u003e\n\u003c/ul\u003e\n[[exhibit 1]]\n\u003ch2\u003eExcitement is warranted, but caution is required\u003c/h2\u003e\n\u003cp\u003eThe awe-inspiring results of generative AI might make it seem like a ready-set-go technology, but that\u0026rsquo;s not the case. Its nascency requires executives to proceed with an abundance of caution. Technologists are still working out the kinks, and plenty of practical and ethical issues remain open. Here are just a few:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cem\u003eLike humans, generative AI can be wrong.\u003c/em\u003e ChatGPT, for example, sometimes \u0026ldquo;hallucinates,\u0026rdquo; meaning it confidently generates entirely inaccurate information in response to a user question and has no built-in mechanism to signal this to the user or challenge the result. For example, we have observed instances when the tool was asked to create a short bio and it generated several incorrect facts for the person, such as listing the wrong educational institution.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eFilters are not yet effective enough to catch inappropriate content.\u003c/em\u003e Users of an image-generating application that can create avatars from a person\u0026rsquo;s photo received avatar options from the system that portrayed them nude, even though they had input appropriate photos of themselves.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eSystemic biases still need to be addressed.\u003c/em\u003e These systems draw from massive amounts of data that might include \u003ca href=\"/capabilities/quantumblack/our-insights/getting-to-know-and-manage-your-biggest-ai-risks\"\u003eunwanted biases\u003c/a\u003e.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eIndividual company norms and values aren\u0026rsquo;t reflected.\u003c/em\u003e Companies will need to adapt the technology to incorporate their culture and values, an exercise that requires technical expertise and computing power beyond what some companies may have ready access to.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eIntellectual-property questions are up for debate.\u003c/em\u003e When a generative AI model brings forward a new product design or idea based on a user prompt, who can lay claim to it? What happens when it plagiarizes a source based on its training data?\u003c/li\u003e\n\u003c/ul\u003e\n[[disruptor1up learnmore]]\n\u003ch2\u003eInitial steps for executives\u003c/h2\u003e\n\u003cp\u003eIn companies considering generative AI, executives will want to quickly identify the parts of their business where the technology could have the most immediate impact and implement a mechanism to monitor it, given that it is expected to evolve quickly. A no-regrets move is to assemble a cross-functional team, including data science practitioners, legal experts, and functional business leaders, to think through basic questions, such as these:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eWhere might the technology aid or disrupt our industry and/or our business\u0026rsquo;s value chain?\u003c/li\u003e\n \u003cli\u003eWhat are our policies and posture? For example, are we watchfully waiting to see how the technology evolves, investing in pilots, or looking to build a new business? Should the posture vary across areas of the business?\u003c/li\u003e\n \u003cli\u003eGiven the limitations of the models, what are our criteria for selecting use cases to target?\u003c/li\u003e\n \u003cli\u003eHow do we pursue building an effective ecosystem of partners, communities, and platforms?\u003c/li\u003e\n \u003cli\u003eWhat legal and community standards should these models adhere to so we can maintain trust with our stakeholders?\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eMeanwhile, it\u0026rsquo;s essential to encourage thoughtful innovation across the organization, standing up guardrails along with sandboxed environments for experimentation, many of which are readily available via the cloud, with more likely on the horizon.\u003c/p\u003e\n\u003chr /\u003e\n\u003cp\u003eThe innovations that generative AI could ignite for businesses of all sizes and levels of technological proficiency are truly exciting. However, executives will want to remain acutely aware of the risks that exist at this early stage of the technology\u0026rsquo;s development.\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":false},"tableOfContentsTitle":{"value":"TABLE OF CONTENTS"},"accessStatus":{"targetItem":{"key":{"value":"RegisteredUsers"},"value":{"value":"Registered Users"}}},"articleType":{"targetItem":{"displayName":"Commentary"}},"hasSpecialReport":{"boolValue":false},"contentType":{"targetItem":{"displayName":"Article"}},"sourcePublication":{"targetItem":null},"externalPublication":{"value":""},"mobileReady":{"boolValue":true},"forClientsOnly":{"boolValue":false},"excludeFromClientLink":{"boolValue":false},"originalPublishDate":{"jsonValue":{"value":"2022-12-20T00:00:00Z"}},"footnotes":{"value":""},"contributoryPractice":{"targetItems":[{"displayName":"QuantumBlack, AI by McKinsey"}]},"aboutTheAuthors":{"value":"\u003cp\u003e\u003cstrong\u003e\u003ca href=\"/our-people/michael-chui\"\u003eMichael Chui\u003c/a\u003e\u003c/strong\u003e is a partner at the McKinsey Global Institute and a partner in McKinsey\u0026rsquo;s Bay Area office, where \u003cstrong\u003e\u003ca href=\"/our-people/roger-roberts\"\u003eRoger Roberts\u003c/a\u003e\u003c/strong\u003e is a partner and \u003cstrong\u003e\u003ca href=\"/our-people/lareina-yee\"\u003eLareina Yee\u003c/a\u003e\u003c/strong\u003e is a senior partner.\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":"FF431280EF724586A7B6357C0797FE50","name":"Roger Roberts","authorTitle":{"value":"Roger Roberts"},"description":{"value":""},"thumbnailImage":{"alt":"","src":null},"profile":{"targetItems":[{"standardImage":{"src":"/~/media/mckinsey/our people/roger roberts/roger-roberts_profile_1536x1152.jpg","alt":"Roger Roberts"},"emailLinks":{"value":"Roger_Roberts@mckinsey.com"},"linkedInUrl":{"value":""},"description":{"value":"Advises clients in a broad range of industries as they address their toughest technology challenges—and make the most of emerging opportunities"},"locations":{"targetItems":[{"name":"Bay Area","displayName":"Bay Area"}]},"firmTitle":{"value":"Expert Partner"},"thumbnailImage":{"alt":"Roger Roberts","src":"/~/media/mckinsey/our people/roger roberts/roger-roberts_headshot_532x399.jpg"},"url":{"path":"/our-people/roger-roberts"}}]}},{"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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