麦肯锡：2024每位CEO应了解的生成式人工智能报告（英文版）

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QuantumBlack, Al by McKinsey

What every CEO should

know about generative AI

Generative AI is evolving at record speed while CEOs are still learning the technology’s

business value and risks. Here, we offer some of the generative AI essentials.

May 2023

Image created by Chris Grava / Darby Films using a node-based visual programming language

This article is a collaborative eort by Michael Chui, Roger Roberts, Tanya Rodchenko, Alex Singla, Alex Sukharevsky, Lareina

Yee, and Delphine Zurkiya, representing views from the McKinsey Technology Council and QuantumBlack, AI by McKinsey,

which are both part of McKinsey Digital.

Amid the excitement surrounding generative

AI since the release of ChatGPT, Bard, Claude,

Midjourney, and other content-creating tools, CEOs

are understandably wondering: Is this tech hype, or

a game-changing opportunity? And if it is the latter,

what is the value to my business?

The public-facing version of ChatGPT reached 100

million users in just two months. It democratized AI

in a manner not previously seen while becoming by

far the fastest-growing app ever. Its out-of-the-box

accessibility makes generative AI different from all

AI that came before it. Users don’t need a degree

in machine learning to interact with or derive value

from it; nearly anyone who can ask questions can

use it. And, as with other breakthrough technologies

such as the personal computer or iPhone, one

generative AI platform can give rise to many

applications for audiences of any age or education

level and in any location with internet access.

All of this is possible because generative AI

chatbots are powered by foundation models, which

contain expansive neural networks trained on

vast quantities of unstructured, unlabeled data

in a variety of formats, such as text and audio.

Foundation models can be used for a wide range

of tasks. In contrast, previous generations of AI

models were often “narrow,” meaning they could

perform just one task, such as predicting customer

churn. One foundation model, for example, can

create an executive summary for a 20,000-word

technical report on quantum computing, draft a

go-to-market strategy for a tree-trimming business,

and provide five different recipes for the ten

ingredients in someone’s refrigerator. The downside

to such versatility is that, for now, generative AI can

sometimes provide less accurate results, placing

renewed attention on AI risk management.

With proper guardrails in place, generative AI can

not only unlock novel use cases for businesses

but also speed up, scale, or otherwise improve

existing ones. Imagine a customer sales call, for

example. A specially trained AI model could suggest

upselling opportunities to a salesperson, but

until now those were usually based only on static

customer data obtained before the start of the call,

such as demographics and purchasing patterns.

A generative AI tool might suggest upselling

opportunities to the salesperson in real time based

on the actual content of the conversation, drawing

from internal customer data, external market trends,

and social media influencer data. At the same time,

generative AI could offer a first draft of a sales pitch

for the salesperson to adapt and personalize.

The preceding example demonstrates the

implications of the technology on one job role. But

nearly every knowledge worker can likely benefit

from teaming up with generative AI. In fact, while

generative AI may eventually be used to automate

some tasks, much of its value could derive from

how software vendors embed the technology

into everyday tools (for example, email or word-

processing software) used by knowledge workers.

Such upgraded tools could substantially increase

productivity.

CEOs want to know if they should act now—and,

if so, how to start. Some may see an opportunity

to leapfrog the competition by reimagining

how humans get work done with generative AI

applications at their side. Others may want to

exercise caution, experimenting with a few use

cases and learning more before making any

large investments. Companies will also have to

assess whether they have the necessary technical

expertise, technology and data architecture,

operating model, and risk management

processes that some of the more transformative

implementations of generative AI will require.

The goal of this article is to help CEOs and their

teams reflect on the value creation case for

generative AI and how to start their journey. First,

we offer a generative AI primer to help executives

better understand the fast-evolving state of AI

and the technical options available. The next

section looks at how companies can participate in

generative AI through four example cases targeted

toward improving organizational effectiveness.

These cases reflect what we are seeing among

early adopters and shed light on the array of options

across the technology, cost, and operating model

requirements. Finally, we address the CEO’s vital

role in positioning an organization for success with

generative AI.

2What every CEO should know about generative AI

Excitement around generative AI is palpable,

and C-suite executives rightfully want to move

ahead with thoughtful and intentional speed.

We hope this article offers business leaders a

balanced introduction into the promising world of

generative AI.

A generative AI primer

Generative AI technology is advancing quickly

(Exhibit 1). The release cycle, number of start-

ups, and rapid integration into existing software

applications are remarkable. In this section,

we will discuss the breadth of generative AI

Exhibit 1

Generative AI has been evolving at a rapid pace.

Timeline of some of the major large language model (LLM) developments in the months following

ChatGPT’s launch

3What every CEO should know about generative AI

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摘要：

QuantumBlack,AlbyMcKinseyWhateveryCEOshouldknowaboutgenerativeAIGenerativeAIisevolvingatrecordspeedwhileCEOsarestilllearningthetechnology’sbusinessvalueandrisks.Here,weoffersomeofthegenerativeAIessentials.May2023ImagecreatedbyChrisGrava/DarbyFilmsusinganode-basedvisualprogramminglanguageThisarticlei...

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