麥肯錫（McKinsey）：人工智能的發展與障礙（英文版）（11頁）.pdf

1、NOVEMBER 2018 MCKINSEY ANALYTICSNeil Webb Notes from the AI frontier: AI adoption advances, but foundational barriers remain Survey respondents report the rapid adoption of AI and expect only a minimal effect on head count. Yet few companies have in place the foundational building blocks that enable

2、 AI to generate value at scale. 2Notes from the AI frontier: AI adoption advances, but foundational barriers remain The adoption of artificial intelligence (AI) is rapidly taking hold across global business, according to a new McKinsey Global Survey on the topic.1 AI, typically defined as the abilit

3、y of a machine to perform cognitive functions associated with human minds (such as perceiving, reasoning, learning, and problem solving), includes a range of capabilities that enable AI to solve business problems. The survey asked about nine in particular,2 and nearly half of respondents say their o

4、rganizations have embedded at least one into their standard business processes, while another 30 percent report piloting the use of AI. Yet overall, the business world is just beginning to harness these technologies and their benefits. Most respondents whose com- panies have deployed AI in a specifi

5、c function report achieving moderate or significant value from that use, but only 21 percent of respondents report embedding AI into multiple business units or functions. Indeed, many organizations still lack the foundational practices to create value from AI at scalefor example, mapping where their

6、 AI opportunities lie and having clear strategies for sourcing the data that AI requires. One critical factor of using AI effectively, the results confirm, is an organizations progress on transforming the core parts of its business through digitization. At the most digitized firms,3 respondents repo

7、rt higher rates of AI usage in more business functions than their peers, along with greater investment in AI and greater overall value from using AI. Another foundational challenge with AI is finding skilled people to implement it effectively. Many respondents say their organizations are addressing

8、the issue by taking a diversified approach to sourcing talent. On the whole, despite reasonable concerns about AI being used to automate existing work, respondents tend to believe that AI will have only a minor effect on overall company head count in the coming years. Adopting, deploying, and applyi

9、ng AI How adoption of AI is progressing The results suggest that most organizations have already begun to adopt AI in their businesses. Forty-seven percent of respondents say their companies have embedded at least one AI capability in their business processescompared with 20 percent of respondents i

10、n a 2017 study who said their companies were using AI in a core part of their business or at scale4and another 30 percent say they are piloting AI. Still, there remains a lot more potential to use AI across the enterprise; as our previous research has shown, AI opportu- nities exist in every sector

11、and business function.5 Just 21 percent of respondents say their organizations have embedded AI in several parts of the business, and so far, investments in AI are a relatively small fraction of companies overall spending on digital technologies. A majority of respondents (58 percent) say less than

12、one-tenth of their companies digital budgets goes toward AIthough respondents overwhelmingly expect AI investments will increase in the coming years (71 percent say so). Which AI capabilities have been deployed Of the nine capabilities we asked about, robotic process automation, computer vision, and

13、 machine learning are most commonly deployed. For each of these, at least 20 percent of respondents say their companies have already embedded these technologies into their business processes. Physical robotics and autonomous vehicles are the least commonly deployed, largely because they are relevant

14、 only to companies in industries where theres a clear application; in those sectors, respondents report the outsize use of the capabilities. For example, half of respondents in automotive and assembly (compared with 16 percent of the total average) say physical robotics are embedded in at least one

15、function or business unit. 3Notes from the AI frontier: AI adoption advances, but foundational barriers remain Exhibit 1AI seems to be gaining the most traction in the areas of the business that create the most value within a given industry. Business functions in which AI has been adopted, by indust

16、ry,1 % of respondents Financial services Telecom High tech Retail Professional services Automotive and assembly 75 48 49 38 46 46 27 51 23 31 38 34 33 36 15 15 15 17 17 17 32 52 27 26 23 7 19 14 11 11 21 21 18 18 38 13 22 20 6 11 19 49 9 4 7 28 23 40 1516 17 15 14 14 14 19 4 43 3 0 2 2 9 8 8 6 6 9 4

17、5 59 26 34 41 28 39 34 13 13 31 1 This question was asked only of respondents who said their organizations have piloted or embedded at least 1 AI capability in 1 or more functions or business units. Respondents who answered “dont know” or “none of the above” are not shown. For telecom, n = 77; for h

18、igh tech, n = 215; for fi nancial services, n = 306; for professional services, n = 221; for electric power and natural gas, n = 54; for healthcare systems and services, n = 67; for automotive and assembly, n = 120; for travel, transport, and logistics, n = 55; for retail, n = 46; and for pharma and

19、 medical products, n = 65. Electric power and natural gas Product and/or service development Strategy and corporate fi nance Supply-chain management ManufacturingRiskService operations Marketing and sales Human resources Healthcare systems and services Pharma and medical products Travel, transport,

20、and logistics 4Notes from the AI frontier: AI adoption advances, but foundational barriers remain Where AI is being used By sector, telecom, high-tech, and financial-services firms are leading the way in overall adoption. That said, looking across sectors and functions, the results suggest that comp

21、anies are generally following the money when deploying AI, which seems to be gaining the most traction in the areas of the business that create the most value within a given industry (Exhibit 1). In retail, for example, the use of AI in marketing and sales processes is most common: 52 percent of ret

22、ail respondents say they are using AI in marketing and sales, compared with 29 percent of all respondents. Where AI is creating value And while the adoption of AI is still in its early days, the results suggest that its already reaping meaningful rewards. When respondents were asked about the value

23、captured in business functions where they have deployed AI, only 1 percent say they have seen no or negative value from that usecompared with 41 percent reporting significant value and 37 percent reporting moderate value.6 Across business functions, respon- dents using AI in manufacturing and risk i

24、ndicate they are seeing the greatest value (Exhibit 2). More than half of respondents report significant value from using AI in these processes, compared with 35 percent of respondents who report significant business value from using AI in marketing and sales.7 Exhibit 2 Across functions, respondent

25、s report that the most signifi cant benefi ts come from adopting AI in manufacturing and in risk. Value to date from AI adoption, by business function,1 % of respondentsModerate value Signifi cant value Supply-chain management Service operations Marketing and sales Human resources ManufacturingRiskP

26、roduct and/or service development Strategy and corporate fi nance 80 23 57 80 29 51 76 29 47 76 31 45 74 35 39 74 35 39 69 34 35 69 36 33 1 Respondents who answered “some value,” “no value,” or “dont know” are not shown. This question was asked only about the business functions where respondents say

27、 their organizations have deployed AI, and only includes responses from respondents who say their organizations have piloted or embedded AI in 1 or more functions or business units. For manufacturing, n = 272; for risk, n = 285; for supply-chain management, n = 299; for product and/or service develo

28、pment, n = 536; for strategy and corporate fi nance, n = 155; for service operations, n = 669; for marketing and sales, n = 482; and for human resources, n = 198. 5Notes from the AI frontier: AI adoption advances, but foundational barriers remain The enablers and challenges of AI To take advantage o

29、f AIs enormous potential, the results confirm, most organizations have a long way to go in developing the core practices that enable them to realize the potential value at scale (Exhibit 3). Just 17 percent of respondents say their companies have mapped out where, across the organization, all potent

30、ial AI opportunities lie. And only 18 percent say their companies have a clear strategy in place for sourcing the data that enable AI work. Indeed, nearly one-quarter of respondents say their companies have not developed any of the 11 practices we asked about. Exhibit 3Few organizations have adopted

31、 the core practices that would enable them to realize AIs potential value at scale. Core AI practices in place at organizations,1 % of respondents Organization uses data (both internal and external) effectively to support goals of AI work Organization has access to internal and external talent with

32、right skill sets to support AI work Senior leaders demonstrate true ownership of and commitment to AI initiatives For business processes where AI has been adopted, it is integrated into day-to-day operations Organization has clear strategy in place for accessing and acquiring data that enable AI wor

33、k Organization runs effective, continual process for developing portfolio of most valuable AI opportunities Organization has right technological infrastructure and architecture in place to support AI systems All relevant data are accessible by AI systems across organization Frontline workers embed A

34、I into formal decision-making and execution processes Employees trust AI-generated insights None of the above Organization has mapped where all potential AI opportunities lie2 33 27 26 26 18 18 17 16 15 24 8 6 1 This question was asked only of respondents who said their organizations have piloted or

35、 embedded AI in 1 or more functions or business units, and they were asked to select all practices that are in place. Respondents who said “dont know” are not shown; n = 1,646. 2 Including required level of investment, diffi culty of implementation, and potential value at stake. 6Notes from the AI f

36、rontier: AI adoption advances, but foundational barriers remain When asked about the biggest challenges to AI adoption, respondents indicate that the most common barrier is also strategy related. They most often cite a lack of a clear AI strategy (Exhibit 4), followed by a lack of appropriate talent

37、, functional silos that constrain end-to-end AI solutions, and a lack of leaders who demonstrate ownership of and commitment to AI. Exhibit 4The most frequently cited barriers to AI adoption are a lack of a clear strategy, a lack of talent, and functional silos. Most signifi cant barriers organizati

38、ons face in adopting AI,1 % of respondents Underresourcing for AI in line organization Limited usefulness of data2 Personal judgment overrides AI-based decision making Limited relevance of insights from AI Lack of clear strategy for AI Lack of talent with appropriate skill sets for AI work Functiona

39、l silos constrain end-to-end AI solutions Lack of leaders ownership of and commitment to AI Lack of technological infrastructure to support AI Lack of available (ie, collected) data Uncertain or low expectations for return on AI investments Lack of changes to frontline processes after AIs adoption 4

40、3 42 30 27 25 24 24 21 20 12 19 18 1 This question was asked only of respondents who said their organizations have piloted or embedded AI in 1 or more functions or business units. Respondents who said “other” or “dont know/not applicable” are not shown; n = 1,646. 2 That is, not accessible to or com

41、patible with AI systems. 7Notes from the AI frontier: AI adoption advances, but foundational barriers remain One critical enabler of AI is a companys progress on its digitization journey. The organizations that have made the most progress in digitizing core business processes are also on the leading

42、 edge of AI adoption. At the most digitized firms, 67 percent of respondents say their organizations have embedded AI into standard business processes, compared with 43 percent at all other companies. They are most likely to have adopted machine learning, for example: 39 percent say it is embedded i

43、n their processes, compared with 16 percent at all other companies (Exhibit 5). Exhibit 5Respondents at the most digitized organizations report greater adoption of AI capabilities than their peers at other companies. Organizations adoption of AI capabilities,1 % of respondents At the most digitized

44、companies2At all other companies Embedded in business processes in multiple functions/business units Embedded in business processes in at least 1 function/business unit Piloted in at least 1 function/ business unit Machine learning311821 Virtual agents or conversational interfaces 281225 24511 26312

45、 Natural-language text understanding 2892126310 Robotic process automation 19152023715 Natural-language speech understanding 27717219 Natural-language generation 22716196 Physical robotics146712710 Autonomous vehicles94384 Computer vision19112122614 2 2 2 1 That is, AI products and/or services, incl

46、uding software. Respondents who answered “not at all” or ”dont know” are not shown. At the most digitized companies, n = 330; at all other companies, n = 1,798. 2 Respondents who say their companies have an average level of digitization of 51% or more. Level of digitization is based on the average p

47、ercentage of the following measures: percentage of the share of sales that come from products and/or services sold through digital channels; of core products and/or services that are digital in nature; of core operations that are automated and/or digitized; and of supply-chain volume that is digitiz

48、ed or moves through digital interactions with suppliers. 8Notes from the AI frontier: AI adoption advances, but foundational barriers remain The most digitized organizations have also deployed AI in more functions than other companies, though both groups say AI is most commonly used in service opera

49、tions and in product development. These companies are also investing much more in AI: 19 percent at the most digitized companies say more than one-fifth of their overall digitization spending goes toward AI, while just 8 percent of other respondents say the same. On average, 52 percent of respondents at these firms report significant value from using AI, compared with 38 percent of all others. And while several of the barriers to AI adoption that we asked about are much less pressing for digitized com- panies (only 27 percent cite a lack