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1{ "output": [
2 [
3 {
4 "page": 1,
5 "lines": [
6 "QuantumBlack",
7 "AI by McKinsey",
8 "The state of AI in early 2024:",
9 "Gen AI adoption spikes and",
10 "starts to generate value",
11 "May 2024"
12 ]
13 },
14 {
15 "page": 2,
16 "lines": [
17 "As generative Al adoption accelerates, survey",
18 "respondents report measurable benefits and",
19 "increased mitigation of the risk of inaccuracy.",
20 "A small group of high performers lead the way.",
21 "This article is a collaborative effort by Alex Singla, Alexander Sukharevsky, Lareina Yee, and",
22 "Michael Chui, with Bryce Hall, representing views from QuantumBlack, Al by McKinsey and",
23 "McKinsey Digital.",
24 "If 2023 was the year the world discovered generative Al (gen",
25 "Al), 2024 is the year organizations truly began using-and",
26 "deriving business value from—this new technology. In the latest",
27 "McKinsey Global Survey on Al, 65 percent of respondents report",
28 "that their organizations are regularly using gen Al, nearly double",
29 "the percentage from our previous survey just ten months ago.",
30 "Respondents' expectations for gen Al's impact remain as high as",
31 "they were last year, with three-quarters predicting that gen Al will",
32 "lead to significant or disruptive change in their industries in the",
33 "years ahead.",
34 "Organizations are already seeing material benefits from gen Al",
35 "use, reporting both cost decreases and revenue jumps in the",
36 "business units deploying the technology. The survey also provides",
37 "insights into the kinds of risks presented by gen Al-most notably,",
38 "inaccuracy-as well as the emerging practices of top performers to",
39 "mitigate those challenges and capture value.",
40 "The state of Al in early 2024: Gen Al adoption spikes and starts to generate value",
41 "1"
42 ]
43 },
44 {
45 "page": 3,
46 "lines": [
47 "AI adoption surges",
48 "Interest in generative Al has also brightened the spotlight on a broader set of Al capabilities. For",
49 "the past six years, Al adoption by respondents' organizations has hovered at about 50 percent.",
50 "This year, the survey finds that adoption has jumped to 72 percent (Exhibit 1). And the interest",
51 "is truly global in scope. Our 2023 survey found that Al adoption did not reach 66 percent in any",
52 "region; however, this year more than two-thirds of respondents in nearly every region say their",
53 "organizations are using Al.¹ Looking by industry, the biggest increase in adoption can be found in",
54 "professional services.²",
55 "Exhibit 1",
56 "Al adoption worldwide has increased dramatically in the past year, after",
57 "years of little meaningful change.",
58 "Organizations that have adopted Al in at least 1 business function,¹ % of respondents",
59 "100",
60 "80",
61 "100",
62 "Adoption of Al",
63 "80",
64 "72",
65 "58",
66 "60",
67 "56",
68 "60",
69 "65",
70 "50",
71 "50",
72 "47",
73 "55",
74 "40",
75 "40",
76 "20",
77 "20",
78 "0",
79 "T",
80 "2017",
81 "2018",
82 "2019",
83 "2020",
84 "2021",
85 "Use of generative Al",
86 "33",
87 "20",
88 "2022",
89 "2023",
90 "0",
91 "2024",
92 "'In 2017, the definition for Al adoption was using Al in a core part of the organization's business or at scale. In 2018 and 2019, the definition was embedding at",
93 "least 1 Al capability in business processes or products. Since 2020, the definition has been that the organization has adopted Al in at least 1 function.",
94 "Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024",
95 "McKinsey & Company",
96 "1 Organizations based in Central and South America are the exception, with 58 percent of respondents working for organizations",
97 "based in Central and South America reporting Al adoption.",
98 "2Includes respondents working for organizations focused on human resources, legal services, management consulting, market",
99 "research, R&D, tax preparation, and training.",
100 "The state of Al in early 2024: Gen Al adoption spikes and starts to generate value",
101 "2"
102 ]
103 }
104 ],
105 [
106 {
107 "page": 1,
108 "content": "Also, responses suggest that companies are now using Al in more parts of the business. Half of
109respondents say their organizations have adopted Al in two or more business functions, up from
110less than a third of respondents in 2023 (Exhibit 2).
111
112Exhibit 2
113Survey findings suggest that organizations are using Al in more business
114functions now than in previous years.
115
116Business functions at respondents' organizations that have adopted Al,1% of respondents
117
1181 or more functions
1192 or more functions
1203 or more functions
1214 or more functions
12272
1235 or more functions
124100
12590
12680
12770
12860
12950
13050
13140
13230
13320
13410
13527
13615
1378
1380
1392021
1402022
1412023
1422024
143'In 2021, n = 1,843; in 2022, n = 1,492; in 2023, n = 1,684; in early 2024, n = 1,363.
144Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
145
146McKinsey & Company
147
148The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
1493"
150 },
151 {
152 "page": 2,
153 "content": "Gen Al adoption is most common in the functions where it can create the most value
154Most respondents now report that their organizations-and they as individuals are using gen Al.
155Sixty-five percent of respondents say their organizations are regularly using gen Al in at least one
156business function, up from one-third last year. The average organization using gen Al is doing so
157in two functions, most often in marketing and sales and in product and service development-
158two functions in which previous research determined that gen Al adoption could generate the
159most value3-as well as in IT (Exhibit 3). The biggest increase from 2023 is found in marketing
160and sales, where reported adoption has more than doubled. Yet across functions, only two use
161cases, both within marketing and sales, are reported by 15 percent or more of respondents.
162
1633"The economic potential of generative Al: The next productivity frontier," McKinsey, June 14, 2023.
164
165Exhibit 3
166Respondents most often report generative Al adoption in their marketing-
167and-sales, product- and service-development, and IT functions.
168
169Respondents' organizations regularly using generative Al (gen Al), by function, % of respondents
17034
17123
17217
17316
17416
17513
17612
1778
1787
1796
1804
181----------
182..........
183................... ______
184------
185------
186----
187Marketing
188IT
189and sales
190Service
191operations
192Human
193resources
194Strategy and
195corporate finance
196Manufacturing
197Product and/or
198service development
199Other corporate
200functions
201Software
202engineering
203Risk
204Supply chain/
205inventory management
206
207Most commonly reported gen Al use cases within function, % of respondents
208
209Marketing and sales
21016
211Product and/or service development
212IT
21310
2147
215Content support for marketing strategy
216Design development
21715
218Personalized marketing
2196
220IT help desk chatbot
2217
222Scientific literature and research review
223Data management
2248
225Sales lead identification and prioritization
2266
227Accelerated early simulation/testing
2286
229IT help desk Al assistant¹
230'Eg, providing real-time assistance and script suggestions to help desk employees during human-to-human conversations.
231Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
232
233McKinsey & Company
234
235The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
2364"
237 },
238 {
239 "page": 3,
240 "content": "Gen Al also is weaving its way into respondents' personal lives. Compared with 2023,
241respondents are much more likely to be using gen Al at work and even more likely to be using
242gen Al both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen Al use
243across all regions, with the largest increases in Asia-Pacific and Greater China. Respondents at
244the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and
245outside of work compared with their midlevel-management peers. Looking at specific industries,
246respondents working in energy and materials and in professional services report the largest
247increase in gen Al use.
248
249Exhibit 4
250Respondents are much more likely now than in 2023 to say they are using generative Al.
251
252Personal experience with generative Al tools, by job title, and age, 2023-24,1% of respondents
253
254Regularly use
255Regularly use for work
256Regularly use
257Have tried
258No exposure
259for work
260and outside of work
261outside of work
262at least once
263Don't know
2642023 2024
2654
2662
2672
26823
2694
2703
2714
2725
2734
2743 3
2754
2769
2778
2788
27918
28010
2817
28218
28315
28412
28511
28617
28719
28818
28932
29035
29133
29239
29340
29431
29542
29642
29715
29828
29931
30036
30137
30235
30330
30417
30516
30616
30715
30820
30923
31024
31113 26
31216
31320
31421
31518
31616
31731
31828
31922
32034
32126
32224
32316
32414
32514
32616
32717
32818
32922
33015
33115
33215
33313
3348
3358
33610
33712
3387
3398
3406
3417
3429
3435
344Overall
345C-level
346Senior
347Midlevel
348Born in 1964
349Born
350Born
351average¹
352executives2
353managers2
354managers2
355or earlier³
3561965-803
3571981-963
358
359Note: Figures may not sum to 100%, because of rounding.
360¹In 2023, n = 1,684; in 2024, n = 1,363.
3612In 2023, C-suite respondents, n = 541; senior managers, n = 437; and middle managers, n = 339. In 2024, C-suite respondents, n = 474; senior managers, n = 406; and middle
362managers, n = 206.
3633In 2023, for respondents born in 1964 or earlier, n = 143; for respondents born between 1965 and 1980, n = 268; and for respondents born between 1981 and 1996, n = 80. In 2024,
364for respondents born in 1964 and earlier, n = 158; for respondents born between 1965 and 1980, n = 331; and for respondents born between 1981 and 1996, n = 184. Age details were
365not available for all respondents.
366Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
367
368McKinsey & Company
369
370The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
3715"
372 }
373 ],
374 {
375 "page1": {
376 "data": [
377 {
378 "2023": "4",
379 "2024": "5",
380 "industry": "Media and telecom",
381 "Don't know": "3",
382 "No exposure": "1",
383 "Have tried at least once": "6",
384 "Regularly use outside of work": "3",
385 "Regularly use for work and outside of work": "12"
386 },
387 {
388 "2023": "2",
389 "2024": "3",
390 "industry": "Technology",
391 "Don't know": "4",
392 "No exposure": "2",
393 "Have tried at least once": "4",
394 "Regularly use outside of work": "5",
395 "Regularly use for work and outside of work": "3"
396 },
397 {
398 "2023": "3",
399 "2024": "5",
400 "industry": "Business, legal, and professional services",
401 "Don't know": "8",
402 "No exposure": "10",
403 "Have tried at least once": "11",
404 "Regularly use outside of work": "8",
405 "Regularly use for work and outside of work": "7"
406 },
407 {
408 "2023": "8",
409 "2024": "17",
410 "industry": "Energy and materials",
411 "Don't know": "26",
412 "No exposure": "26",
413 "Have tried at least once": "14",
414 "Regularly use outside of work": "13",
415 "Regularly use for work and outside of work": "21"
416 },
417 {
418 "2023": "15",
419 "2024": "24",
420 "industry": "Advanced industries",
421 "Don't know": "31",
422 "No exposure": "39",
423 "Have tried at least once": "29",
424 "Regularly use outside of work": "28",
425 "Regularly use for work and outside of work": "32"
426 },
427 {
428 "2023": "23",
429 "2024": "14",
430 "industry": "Consumer goods and retail",
431 "Don't know": "26",
432 "No exposure": "44",
433 "Have tried at least once": "41",
434 "Regularly use outside of work": "9",
435 "Regularly use for work and outside of work": "6"
436 },
437 {
438 "2023": "34",
439 "2024": "42",
440 "industry": "Financial services",
441 "Don't know": "51",
442 "No exposure": "41",
443 "Have tried at least once": "43",
444 "Regularly use outside of work": "38",
445 "Regularly use for work and outside of work": "40"
446 },
447 {
448 "2023": "44",
449 "2024": "26",
450 "industry": "Healthcare, pharma, and medical products",
451 "Don't know": "30",
452 "No exposure": "13",
453 "Have tried at least once": "39",
454 "Regularly use outside of work": "27",
455 "Regularly use for work and outside of work": "38"
456 }
457 ],
458 "note": "Note: Figures may not sum to 100%, because of rounding.
459'In 2023, media, entertainment, and telecommunications, n = 69; technology, n = 175; business, legal, and professional services, n = 215; energy and materials,
460n = 152; advanced industries (includes automotive and assembly, aerospace and defense, advanced electronics, and semiconductors), n = 112; consumer goods and retail, n =
461128; financial services, n = 248; healthcare, pharmaceuticals, and medical products, n = 130. In 2024, media, entertainment, and telecommunications, n = 70; technology, n =
462184; business, legal, and professional services, n = 166; energy and materials, n = 113; advanced industries, n = 86; consumer goods and retail, n = 100; financial services, n =
463201; healthcare, pharmaceuticals, and medical products, n = 109. Analyses for 2023 were updated to include additional industries within advanced industries and energy and
464materials.
465Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024",
466 "note2": "Note: Figures may not sum to 100%, because of rounding.
467¹In 2023, Asia-Pacific, n = 164; Europe, n = 515; North America, n = 392; Greater China (includes Hong Kong and Taiwan), n = 337; and developing markets (includes India,
468Latin America, and Middle East and North Africa), n = 276. In 2024, Asia-Pacific, n = 116; Europe, n = 457; North America, n = 401; Greater China (includes Hong Kong and
469Taiwan), n = 153; and developing markets (includes India, Latin America, and Middle East and North Africa), n = 234.
470Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024",
471 "title": "Exhibit 4 (continued)",
472 "footer": "McKinsey & Company
473The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 6",
474 "columns": [
475 "Regularly use for work",
476 "Regularly use for work and outside of work",
477 "Regularly use outside of work",
478 "Have tried at least once",
479 "No exposure",
480 "Don't know"
481 ],
482 "heading": "Respondents are much more likely now than in 2023 to say they are using generative Al.",
483 "locations": [
484 {
485 "2023": "3",
486 "2024": "1",
487 "location": "Asia-Pacific",
488 "Don't know": "14",
489 "No exposure": "19",
490 "Have tried at least once": "6",
491 "Regularly use outside of work": "1",
492 "Regularly use for work and outside of work": "3"
493 },
494 {
495 "2023": "23",
496 "2024": "30",
497 "location": "Greater China",
498 "Don't know": "34",
499 "No exposure": "45",
500 "Have tried at least once": "46",
501 "Regularly use outside of work": "36",
502 "Regularly use for work and outside of work": "34"
503 },
504 {
505 "2023": "14",
506 "2024": "30",
507 "location": "Developing markets",
508 "Don't know": "27",
509 "No exposure": "19",
510 "Have tried at least once": "13",
511 "Regularly use outside of work": "14",
512 "Regularly use for work and outside of work": "12"
513 },
514 {
515 "2023": "20",
516 "2024": "18",
517 "location": "North America",
518 "Don't know": "17",
519 "No exposure": "15",
520 "Have tried at least once": "18",
521 "Regularly use outside of work": "11",
522 "Regularly use for work and outside of work": "27"
523 },
524 {
525 "2023": "15",
526 "2024": "7",
527 "location": "Europe",
528 "Don't know": "11",
529 "No exposure": "10",
530 "Have tried at least once": "6",
531 "Regularly use outside of work": "9",
532 "Regularly use for work and outside of work": "14"
533 }
534 ],
535 "subheading": "Personal experience with generative Al tools, by industry, 2023–24,1% of respondents",
536 "subheading2": "Personal experience with generative Al tools, by location, 2023-24,1% of respondents"
537 },
538 "page2": {
539 "title": "Investments in gen Al and analytical Al are beginning to create value",
540 "footer": "The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 7",
541 "content": "The latest survey also shows how different industries are budgeting for gen Al. Responses
542suggest that, in many industries, organizations are about equally as likely to be investing more
543than 5 percent of their digital budgets in gen Al as they are in nongenerative, analytical-Al
544solutions (Exhibit 5). Yet in most industries, larger shares of respondents report that their
545organizations spend more than 20 percent on analytical Al than on gen Al. Looking ahead,
546most respondents-67 percent-expect their organizations to invest more in Al over the next
547three years.
548Where are those investments paying off? For the first time, our latest survey explored the
549value created by gen Al use by business function. The function in which the largest share of
550respondents report seeing cost decreases is human resources. Respondents most commonly
551report meaningful revenue increases (of more than 5 percent) in supply chain and inventory
552management (Exhibit 6). For analytical Al, respondents most often report seeing cost benefits
553in service operations-in line with what we found last year-as well as meaningful revenue
554increases from Al use in marketing and sales.",
555 "highlight": "Looking ahead, most respondents—
55667 percent—expect their
557organizations to invest more in
558AI over the next three years."
559 },
560 "page3": {
561 "note": "Note: Figures may not sum to 100%, because of rounding.
562'Question was asked only of respondents who said their organizations have adopted Al in at least 1 business function. For technology, n = 128; for energy and materials, n = 63;
563for financial services, n = 107; for media, entertainment, and telecommunications, n = 50;
564for consumer goods and retail, n = 67; for advanced industries, n = 50; for business, legal, and professional services, n = 101; and for healthcare,
565pharmaceuticals, and medical products, n = 58.
566Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024",
567 "title": "Exhibit 5",
568 "footer": "McKinsey & Company
569The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 8",
570 "heading": "In most industries, organizations are about equally likely to invest more than 5 percent of their digital budgets in generative Al and analytical Al.",
571 "industries": [
572 {
573 ">20%": "11",
574 "6-10%": "16",
575 "≤5%": "40",
576 "11-15%": "16",
577 "16-20%": "10",
578 "industry": "Technology",
579 "Don't know": "7"
580 },
581 {
582 ">20%": "17",
583 "6-10%": "8",
584 "≤5%": "46",
585 "11-15%": "9",
586 "16-20%": "7",
587 "industry": "Energy and materials",
588 "Don't know": "13"
589 },
590 {
591 ">20%": "11",
592 "6-10%": "47",
593 "≤5%": "12",
594 "11-15%": "26",
595 "16-20%": "4",
596 "industry": "Financial services"
597 },
598 {
599 ">20%": "7",
600 "6-10%": "7",
601 "≤5%": "63",
602 "11-15%": "6",
603 "16-20%": "4",
604 "industry": "Media and telecommunications",
605 "Don't know": "16"
606 },
607 {
608 ">20%": "5",
609 "≤5%": "64",
610 "11-15%": "12",
611 "16-20%": "6",
612 "industry": "Consumer goods and retail",
613 "Don't know": "12"
614 },
615 {
616 ">20%": "5",
617 "≤5%": "70",
618 "16-20%": "18",
619 "industry": "Advanced industries",
620 "Don't know": "6"
621 },
622 {
623 ">20%": "5",
624 "6-10%": "7",
625 "≤5%": "63",
626 "11-15%": "3",
627 "16-20%": "4",
628 "industry": "Business, legal, and professional services",
629 "Don't know": "19"
630 },
631 {
632 ">20%": "3",
633 "6-10%": "5",
634 "≤5%": "61",
635 "11-15%": "2",
636 "16-20%": "8",
637 "industry": "Healthcare, pharmaceuticals, and medical products",
638 "Don't know": "21"
639 },
640 {
641 ">20%": "6",
642 "6-10%": "13",
643 "≤5%": "55",
644 "11-15%": "7",
645 "16-20%": "7",
646 "industry": "Overall",
647 "Don't know": "19"
648 }
649 ],
650 "subheading": "Share of organization's digital budget spent on generative Al,¹ % of respondents",
651 "industries2": [
652 {
653 ">20%": "18",
654 "6-10%": "23",
655 "≤5%": "28",
656 "11-15%": "13",
657 "16-20%": "5",
658 "industry": "Technology",
659 "Don't know": "13"
660 },
661 {
662 ">20%": "3",
663 "6-10%": "11",
664 "≤5%": "66",
665 "11-15%": "9",
666 "16-20%": "5",
667 "industry": "Energy and materials",
668 "Don't know": "7"
669 },
670 {
671 ">20%": "12",
672 "6-10%": "13",
673 "≤5%": "44",
674 "11-15%": "6",
675 "16-20%": "11",
676 "industry": "Financial services",
677 "Don't know": "14"
678 },
679 {
680 ">20%": "11",
681 "6-10%": "10",
682 "≤5%": "48",
683 "11-15%": "7",
684 "16-20%": "3",
685 "industry": "Media and telecommunications",
686 "Don't know": "21"
687 },
688 {
689 ">20%": "16",
690 "6-10%": "11",
691 "≤5%": "48",
692 "11-15%": "8",
693 "16-20%": "3",
694 "industry": "Consumer goods and retail",
695 "Don't know": "13"
696 },
697 {
698 ">20%": "6",
699 "≤5%": "67",
700 "11-15%": "17",
701 "16-20%": "1",
702 "industry": "Advanced industries",
703 "Don't know": "7"
704 },
705 {
706 ">20%": "11",
707 "6-10%": "3",
708 "≤5%": "47",
709 "11-15%": "3",
710 "16-20%": "2",
711 "industry": "Business, legal, and professional services",
712 "Don't know": "34"
713 },
714 {
715 ">20%": "15",
716 "6-10%": "18",
717 "≤5%": "37",
718 "11-15%": "6",
719 "16-20%": "2",
720 "industry": "Healthcare, pharmaceuticals, and medical products",
721 "Don't know": "22"
722 },
723 {
724 ">20%": "11",
725 "6-10%": "11",
726 "≤5%": "45",
727 "11-15%": "8",
728 "16-20%": "6",
729 "industry": "Overall",
730 "Don't know": "16"
731 }
732 ],
733 "subheading2": "Share of organization's digital budget spent on analytical Al technology,¹ % of respondents"
734 }
735 },
736 [
737 {
738 "Exhibit 6": "Organizations most often see meaningful cost reductions from generative Al use in HR
739and revenue increases in supply chain management."
740 },
741 {
742 "Cost decrease and revenue increase from generative Al adoption in 2023, by function,¹% of respondents": null
743 },
744 {
745 "Decrease by <10%": "Decrease by 10-19%",
746 "Decrease by ≥20%": "Increase by >10% Increase by 6-10% Increase by ≤5%"
747 },
748 {
749 "Marketing and sales": "37
75022
75111
7524
7537
75412
75534
75653"
757 },
758 {
759 "Risk, legal, and compliance": "33
76015
7613
76215
7633 13
76446
76562"
766 },
767 {
768 "Human resources": "50
76919
77016
77115
77266
77321
77433"
775 },
776 {
777 "Product or service development": "37
77823
77968
78048
78123
78235"
783 },
784 {
785 "Supply chain and inventory management": "46
78631
78711
7884
7895
79018
79130
79253"
793 },
794 {
795 "Service operations": "45
79634
79774
7983 13
79929
80045"
801 },
802 {
803 "IT": "42
80426
8059
8067
8074 10
80842
80956"
810 },
811 {
812 "Software engineering": "42
81321
81416
8155
8167
8179
81830
81946"
820 },
821 {
822 "Other corporate functions": "34 13
82312
8249
8259
82613
82710 32"
828 },
829 {
830 "Average across all functions": "39
83124
8329
8336
8345 10
83529
83644"
837 },
838 {
839 "Use of analytical Al most often yields cost reductions in service operations and revenue
840increases in marketing and sales.": null
841 },
842 {
843 "Cost decrease and revenue increase from analytical Al adoption in 2023, by function,¹ % of respondents": null
844 },
845 {
846 "Marketing and sales": "34
84728
84842
8494
85023
85134
85271"
853 },
854 {
855 "Risk, legal, and compliance": "34
85620
85759
8587
85911
86035
86153"
862 },
863 {
864 "Human resources": "37
86521
8668 8
86758
86852
86965"
870 },
871 {
872 "Product or service development": "23
87311 4 8
87410
87516
87630
87756"
878 },
879 {
880 "Supply chain and inventory management": "43
88129
88211 3
88310
88414
88539
88663"
887 },
888 {
889 "Service operations": "49
89028
89116
8925
89312 10
89435
89557"
896 },
897 {
898 "IT": "37
89922
90011
9014
90211
90312
90427
90550"
906 },
907 {
908 "Software engineering": "41
90920
91017
9114
91211
91314
91419
91544"
916 },
917 {
918 "Other corporate functions": "25 15
9199
9208 8
92124
92240
9231"
924 },
925 {
926 "Average across all functions": "35
92723
92875
9296
93017
93135
93258"
933 },
934 {
935 "Questions were asked only of respondents who said their organizations have adopted Al in a given function. Respondents who said "cost increase," "no change,"
936"not applicable," or "don't know" for the effects of analytical Al on costs are not shown, and respondents who said "revenue decrease," "no change," "not applicable," or "don't
937know" for the effects of analytical Al on revenues are not shown. Data for manufacturing and strategy and corporate finance are not shown, because the base sizes were too
938small to meet the reporting threshold.
939Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-March 5, 2024": null
940 },
941 {
942 "McKinsey & Company": "The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 9"
943 },
944 {
945 "McKinsey commentary": "Alex Singla"
946 },
947 {
948 "Senior partner and global coleader of QuantumBlack, Al by McKinsey": null
949 },
950 {
951 "In 2024, generative Al (gen Al) is no longer a novelty. Nearly two-thirds of respondents to
952our survey report that their organizations are regularly using gen Al, nearly double what our
953previous survey found just ten months ago, and four in ten are using gen Al in more than
954two business functions. The technology's potential is no longer in question. And while most
955organizations are still in the early stages of their journeys with gen Al, we are beginning to get
956a picture of what works and what doesn't in implementing-and generating actual value with-
957the technology.": null
958 },
959 {
960 "One thing we've learned: the business goal must be paramount. In our work with clients, we
961ask them to identify their most promising business opportunities and strategies and then
962work backward to potential gen Al applications. Leaders must avoid the trap of pursuing tech
963for tech's sake. The greatest rewards also will go to those who are not afraid to think big. As
964we've observed, the leading companies are the ones that are focusing on reimagining entire
965workflows with gen Al and analytical Al rather than simply seeking to embed these tools into
966their current ways of working.": null
967 },
968 {
969 "For that to be effective, leaders must be ready to manage change at every step along the
970way. And they should expect that change to be constant: enterprises will need to design a
971gen Al stack that is robust, cost-efficient, and scalable for years to come. They'll also need
972to draw on leaders from throughout the organization. Realizing profit-and-loss impact from
973gen Al requires close partnership with HR, finance, legal, and risk to constantly readjust the
974resourcing strategies and productivity expectations.": null
975 },
976 {
977 "Inaccuracy: The most recognized and experienced risk of gen AI use": null
978 },
979 {
980 "As businesses begin to see the benefits of gen Al, they're also recognizing the diverse risks
981associated with the technology. These can range from data management risks such as data
982privacy, bias, or intellectual property (IP) infringement to model management risks, which tend
983to focus on inaccurate output or lack of explainability. A third big risk category is security and
984incorrect use. Respondents to the latest survey are more likely than they were last year to say
985their organizations consider inaccuracy and IP infringement to be relevant to their use of gen Al,
986and about half continue to view cybersecurity as a risk (Exhibit 7).": null
987 },
988 {
989 "Conversely, respondents are less likely than they were last year to say their organizations
990consider workforce and labor displacement to be relevant risks and are not increasing efforts
991to mitigate them. In fact, inaccuracy-which can affect use cases across the gen Al value chain,
992ranging from customer journeys and summarization to coding and creative content-is the only
993risk that respondents are significantly more likely than last year to say their organizations are
994actively working to mitigate.": null
995 },
996 {
997 "The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 10": null
998 },
999 {
1000 "Exhibit 7": "Inaccuracy and intellectual property infringement are increasingly considered relevant
1001risks to organizations' generative Al use."
1002 },
1003 {
1004 "Gen Al risks that organizations consider relevant,¹ % of respondents": "2023
10052024"
1006 },
1007 {
1008 "63
100956": "53
101052
101151
101246
101345
101443
101542
101639
101740
101839
101934
102031
102130
102227
102329
102424"
1025 },
1026 {
1027 "Inaccuracy": "Cybersecurity
1028Regulatory
1029compliance
1030Equity and
1031fairness
1032Organizational
1033reputation
1034Environmental
1035impact
1036Physical
1037safety
1038National
1039security
1040Political
1041stability
1042None
1043of the
1044above"
1045 },
1046 {
1047 "Intellectual
1048property
1049infringement": "Personal/
1050individual
1051privacy
1052Explainability
1053Workforce
1054labor
1055displacement"
1056 },
1057 {
1058 "Gen Al risks that organizations are working to mitigate,1% of respondents": null
1059 },
1060 {
1061 "38
106238": "33
106332,
106428
106525 25
106623
106724
106820
106918
107017
107116
107216
107313
107412
107512
107611
10779
10788
107955
10806
10814 4
10823
10833
10842"
1085 },
1086 {
1087 "Inaccuracy": "Cybersecurity
1088Regulatory
1089compliance
1090Equity and
1091fairness
1092Organizational
1093reputation
1094Environmental
1095impact
1096Physical
1097safety
1098National
1099security
1100Political
1101stability
1102None
1103of the
1104above"
1105 },
1106 {
1107 "Intellectual
1108property
1109infringement": "Personal/
1110individual
1111privacy
1112Explainability
1113Workforce
1114labor
1115displacement"
1116 },
1117 {
1118 "Question was asked only of respondents whose organizations have adopted Al in at least 1 function. Respondents who said "don't know/not applicable" are
1119not shown. In 2023, n = 913; in 2024, n = 1,052.
1120Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024": null
1121 },
1122 {
1123 "McKinsey & Company": "The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
112411"
1125 }
1126 ],
1127 {
1128 "page1": {
1129 "text": "In fact, some organizations have already experienced negative consequences from the use of
1130gen Al, with 44 percent of respondents saying their organizations have experienced at least one
1131consequence (Exhibit 8). Respondents most often report inaccuracy as a risk that has affected
1132their organizations, followed by cybersecurity and explainability.
1133Exhibit 8
1134Nearly one-quarter of respondents say their organizations have
1135experienced negative consequences from generative Al's inaccuracy.
1136Generative-Al-related risks that caused negative consequences for organizations,¹% of respondents
113739
113823
113916
114012
114111
114210
11439
11448
11457
11467
11474
11484
11494
11504
1151Inaccuracy
1152Cybersecurity
1153Explainability Regulatory Organizational
1154Equity and
1155National
1156Environmental
1157compliance
1158reputation
1159fairness
1160security
1161impact
1162Intellectual
1163Personal/
1164Workforce
1165property
1166individual
1167labor
1168Physical
1169Political
1170None
1171safety
1172stability
1173of the
1174infringement
1175privacy
1176displacement
1177above
1178'Question was asked only of respondents whose organizations have adopted generative Al in at least 1 function, n = 876. The 17 percent of respondents who
1179said "don't know/not applicable" are not shown.
1180Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
1181McKinsey & Company
1182The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
118312"
1184 },
1185 "page2": {
1186 "text": "Our previous research has found that there are several elements of governance that can help in
1187scaling gen Al use responsibly, yet few respondents report having these risk-related practices
1188in place. For example, just 18 percent say their organizations have an enterprise-wide council or
1189board with the authority to make decisions involving responsible Al governance, and only
1190one-third say gen Al risk awareness and risk mitigation controls are required skill sets for
1191technical talent.
11924"Implementing generative Al with speed and safety," McKinsey Quarterly, March 13, 2024.
1193McKinsey commentary
1194Lareina Yee
1195Senior partner, McKinsey; chair, McKinsey Technology Council
1196Responsible Al needs to start on day one, and there is still much work to be done in terms
1197of education and action. It begins with a company's values-organizations must establish
1198clear principles for how they apply generative Al (gen Al) and set up guardrails to ensure its
1199safe implementation. For example, recognizing the importance of data security means that
1200company-level data and prompts remain within the enterprise walls. For that to happen, the
1201enterprise must have secure contracts with large language model and application providers,
1202as well as robust training, to make sure employees understand the difference between
1203enterprise tools and public tools so that code or proprietary data are not inadvertently shared
1204in public models.
1205Responsible Al also starts upstream of compliance and monitoring. Leading companies in
1206deploying gen Al incorporate risk practices in the development of their Al applications. This
1207includes ensuring that technical teams understand risk and mitigation practices. Gen Al
1208solutions are probabilistic models that can make mistakes or inadvertently amplify biases
1209in training data, so testing models before they are deployed is essential. Without a robust
1210testing approach, it is hard to deliver on responsible Al.
1211Finally, companies must develop a clear governance model to help ensure that gen Al
1212applications conform to governing principles. What we see in the survey results and in
1213our conversations with clients is a growing awareness of responsible Al and an urgency to
1214get it right. Still, even with increasing understanding, a little less than one-quarter of the
1215respondents in our survey report having a clear process to embed risk mitigation in their
1216solutions. Moving from awareness to action will be critical.
1217The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
121813"
1219 },
1220 "page3": {
1221 "text": "Bringing gen AI capabilities to bear
1222The latest survey also sought to understand how, and how quickly, organizations are deploying
1223these new gen Al tools. We have found three archetypes for implementing gen Al solutions:
1224takers use off-the-shelf, publicly available solutions; shapers customize those tools with
1225proprietary data and systems; and makers develop their own foundation models from scratch.5
1226Across most industries, the survey results suggest that organizations are finding off-the-shelf
1227offerings applicable to their business needs-though many are pursuing opportunities to
1228customize models or even develop their own (Exhibit 9). About half of reported gen Al uses within
1229respondents' business functions are utilizing off-the-shelf, publicly available models or tools,
1230with little or no customization. Respondents in energy and materials, technology, and media
1231and telecommunications are more likely to report significant customization or tuning of publicly
1232available models or developing their own proprietary models to address specific business needs.
12335 "Technology's generational moment with generative AI: A CIO and CTO guide," McKinsey, July 11, 2023.
1234Exhibit 9
1235Organizations are pursuing a mix of off-the-shelf generative Al capabilities
1236and also significantly customizing models or developing their own.
1237Strategy for developing generative Al (gen Al) capabilities, % of reported instances of gen Al use¹
1238Energy and materials
123960
1240Technology
124156
124240
1243Significant
1244customization
1245or developed
1246own model
124744
1248Primarily off
1249Media and telecommunications
125054
125146
1252the shelf, with
1253little or no
1254customization
1255Consumer goods and retail
125650
125750
1258Financial services
125947
126053
1261Healthcare, pharmaceuticals,
126247
126353
1264and medical products
1265Advanced industries
126642
126758
1268Business, legal, and
126937
127063
1271professional services
1272Overall
127347
127453
1275'Question was asked only of respondents who said their organizations regularly use generative Al in at least 1 business function. Figures were calculated after
1276removing respondents who said "don't know."
1277Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
1278McKinsey & Company
1279The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
128014"
1281 }
1282 },
1283 [
1284 {
1285 "page": 1,
1286 "text": "Gen AI high performers are much
1287more likely than others to use
1288gen AI solutions in risk, legal,
1289and compliance; in strategy and
1290corporate finance; and in supply
1291chain and inventory management.
1292What else are these high performers doing differently? For one thing, they are paying more
1293attention to gen-Al-related risks. Perhaps because they are further along on their journeys,
1294they are more likely than others to say their organizations have experienced every negative
1295consequence from gen Al we asked about, from cybersecurity and personal privacy to
1296explainability and IP infringement. Given that, they are more likely than others to report that their
1297organizations consider those risks, as well as regulatory compliance, environmental impacts, and
1298political stability, to be relevant to their gen Al use, and they say they take steps to mitigate more
1299risks than others do.
1300Gen Al high performers are also much more likely to say their organizations follow a set of risk-
1301related best practices (Exhibit 11). For example, they are nearly twice as likely as others to involve
1302the legal function and embed risk reviews early on in the development of gen Al solutions-that
1303is, to "shift left." They're also much more likely than others to employ a wide range of other best
1304practices, from strategy-related practices to those related to scaling.
1305The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
130618"
1307 },
1308 {
1309 "page": 2,
1310 "text": "Exhibit 11
1311Organizations seeing the largest returns from generative Al are more likely than others
1312to follow a range of best practices.
1313Organizations engaging in each practice,¹ % of respondents
1314Risk
1315Strategy
1316All other respondents
1317Gen Al high performers2
1318Gen Al risk awareness and mitigation
1319are required skills for technical talent
132034
132168
1322Have clear processes to embed risk mitigation in
1323gen Al solutions (eg, involving the legal function)
132423
132544
1326Gen Al models are designed to allow audits,
1327bias checks, and risk assessment
132818
132943
1330Have an enterprise-wide council or board to make
1331decisions on responsible Al governance
133218
133324
1334|
1335|
13361
13371
13380
133920
134040
134160
13421
134380
1344100
1345Senior leaders understand how gen Al
1346can create value for the business
134739
1348Have an enterprise-wide road map for gen Al,
1349prioritized based on value, feasibility, and risk
135025
1351Have appointed a credible, empowered
1352leader of gen Al initiatives
135321
135432
135559
135664
1357Talent
13580
135920
136040
136160
13621
136380
1364|
1365100
1366Have curated learning journeys, tailored by role,
1367to build critical gen Al skills for technical talent
136818
136943
1370Have clearly defined the talent (ie, both roles and skills)
1371needed to execute the gen Al strategy
137215
137332
1374Have a talent strategy that allows effective recruitment,
1375onboarding, and integration of gen-Al-related talent
137616
137731
13780
137920
138040
138160
138280
1383100
1384Operating model
1385Have a centralized team that coordinates
1386and links gen Al efforts across the organization
138735
138849
1389Deliver gen Al solutions following well-defined
1390agile team processes and standards
139119
139243
1393Have funding and budgeting processes that
1394support agile delivery of gen Al solutions
139514
139627
13971
13980
139920
140040
140160
140280
1403100
1404'Asked only of respondents who said their organizations are regularly using generative Al in at least 1 business function.
14052Respondents who said that at least 11% of their organizations' EBIT in 2023 was attributable to their use of gen Al. For gen Al high performers, n = 46; for all other
1406respondents, n = 830.
1407Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
1408McKinsey & Company
1409The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
141019"
1411 },
1412 {
1413 "page": 3,
1414 "text": "Exhibit 11 (continued)
1415Organizations seeing the largest returns from generative Al are more likely than others
1416to follow a range of best practices.
1417Organizations engaging in each practice,¹ % of respondents
1418Technology and data
1419All other respondents
1420Gen Al high performers2
1421Testing and validation are embedded
1422in release process for each model
142317
142458
1425Clear processes are in place to iteratively
1426improve model outputs
1427Processes are defined to determine when models
1428need human validation (eg, human in the loop)
1429Gen Al foundations are built with a
1430strategy to enable reuse across solutions
1431There is a defined, comprehensive data strategy
1432to enable the gen Al road map
143315
143446
143519
143643
143715
143843
1439Live monitoring of entire system is set up,
1440enabling rapid issue resolution
14417
1442Modular components are developed that
1443can be reused across solutions
144411
1445Adoption and scaling
1446Nontechnical personnel understand the potential value
1447and risks of using gen Al in their day-to-day work
1448Data are used consistently to create
1449insights that affect bottom-line performance
1450There is a clear performance management infrastructure
1451(eg, KPIs) to measure and track value of gen Al
145217
145342
145441
145531
1456|
14571
14580
145920
146040
146160
146280
1463100
146413
146521
146624
146744
146837
146952
14700
147120
147240
147360
147480
1475100
1476'Asked only of respondents who said their organizations are regularly using generative Al in at least 1 business function.
14772Respondents who said that at least 11% of their organizations' EBIT in 2023 was attributable to their use of gen Al. For gen Al high performers, n = 46; for all other
1478respondents, n = 830.
1479Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024
1480McKinsey & Company
1481The state of Al in early 2024: Gen Al adoption spikes and starts to generate value
148220"
1483 }
1484 ],
1485 [
1486 {
1487 "page": 21,
1488 "text": "In addition to experiencing the risks of gen Al adoption, high performers have encountered other
1489challenges that can serve as warnings to others (Exhibit 12). Seventy percent say they have
1490experienced difficulties with data, including defining processes for data governance, developing
1491the ability to quickly integrate data into Al models, and an insufficient amount of training data,
1492highlighting the essential role that data play in capturing value. High performers are also more
1493likely than others to report experiencing challenges with their operating models, such as
1494implementing agile ways of working and effective sprint performance management.
1495Exhibit 12
1496Generative Al high performers report experiencing a range of challenges in
1497capturing value from the technology.
1498Elements that have posed challenges in capturing value from generative Al (gen Al), % of respondents"
1499 },
1500 {
1501 "page": 21,
1502 "text": "Data
1503Risk and responsible Al
1504Operating model
1505Technology
1506Strategy
1507Talent
1508Adoption and scaling
1509Gen Al high performers¹
151070
151148
151247
151343
151442
151537
151633
1517All other respondents
151836
151934
152028
152130
152239
152335
152438
1525Note: Figures do not sum to 100%, because respondents could choose multiple answer options.
1526'Respondents who said that at least 11% of their organizations' EBIT in 2023 was attributable to their use of generative Al. For respondents at Al high perform-
1527ers, n = 46; for all other respondents, n = 830. Respondents who said "don't know/not applicable" are not shown.
1528Source: McKinsey Global Survey on Al, 1,363 participants at all levels of the organization, Feb 22-Mar 5, 2024"
1529 },
1530 {
1531 "page": 21,
1532 "text": "McKinsey & Company
1533The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 21"
1534 },
1535 {
1536 "page": 22,
1537 "text": "Find more content like this on the
1538McKinsey Insights App
1539McKinsey
1540& Company
1541Scan Download Personalize"
1542 },
1543 {
1544 "page": 22,
1545 "text": "McKinsey commentary
1546Bryce Hall
1547Associate partner
1548We've been conducting research on Al for seven years now, and the pace of innovation,
1549the evolution of new companies and capabilities, and the wave of investment have been
1550remarkable. And now we're seeing how leading companies are capturing business value from
1551these often-dazzling Al and generative Al (gen Al) capabilities.
1552One of the most interesting findings in this year's survey is that among the high performers
1553capturing the most value from gen Al, most solutions are highly customized or bespoke (what
1554we refer to as "shaper" or "maker" archetypes of gen Al solutions). While many companies
1555are finding value from off-the-shelf gen Al solutions (or the "taker" archetype), capturing the
1556full value of this technology often requires significant customization-for example, training
1557models on proprietary company and customer data or tuning models to improve performance
1558within a specific industry or business context.
1559The survey also sheds new light on high performers' practices. High performers, for example,
1560are significantly more likely than others to embed testing and validation in the release process
1561for models, as well as to develop clear processes to iteratively improve model outputs. Over
1562time, these kinds of practices will become even more important, as highly customized and
1563bespoke solutions are the ones that will truly be differentiating for companies. Off-the-shelf
1564solutions, by contrast, are likely to become table stakes. Collectively, these data on practices
1565are consistent with our ongoing work and research on digital and Al transformations, which
1566shows that competitive advantage comes from building organizational and technological
1567capabilities to broadly innovate, deploy, and improve solutions at scale-in effect, rewiring the
1568business for distributed digital and Al innovation."
1569 },
1570 {
1571 "page": 22,
1572 "text": "About the research
1573The online survey was in the field from February 22 to March 5, 2024, and garnered responses
1574from 1,363 participants representing the full range of regions, industries, company sizes,
1575functional specialties, and tenures. Of those respondents, 981 said their organizations had
1576adopted Al in at least one business function, and 878 said their organizations were regularly
1577using gen Al in at least one function. To adjust for differences in response rates, the data are
1578weighted by the contribution of each respondent's nation to global GDP."
1579 },
1580 {
1581 "page": 22,
1582 "text": "Alex Singla and Alexander Sukharevsky are global coleaders of Quantum Black, Al by McKinsey, and senior
1583partners in McKinsey's Chicago and London offices, respectively; Lareina Yee is a senior partner in the Bay Area
1584office, where Michael Chui, a McKinsey Global Institute partner, is a partner; and Bryce Hall is an associate partner
1585in the Washington, DC, office.
1586They wish to thank Kaitlin Noe, Larry Kanter, Mallika Jhamb, and Shinjini Srivastava for their contributions to this work.
1587Designed by McKinsey Global Publishing
1588Copyright © 2024 McKinsey & Company. All rights reserved.
1589The state of Al in early 2024: Gen Al adoption spikes and starts to generate value 22"
1590 }
1591 ]
1592 ]}