why artificial intelligence is the future of growth - accenture - 埃森哲：人工智能——經(jīng)濟(jì)發(fā)展新動力

1、,,By Mark Purdy and Paul Daugherty,CONTENTS,2,|,Why artificial intelligence is the future of growth,The new factor of productionThree channels of AI-led growth Factoring in AIClearing the path to an AI future,41

2、21521,3,|,Why artificial intelligence is the future of growth,There has been marked decline in the ability of increases in capital investment and in labor to propel economic progress. These two levers are the tra

3、ditional drivers of production, yet they are no longer able to sustain the steady march of prosperity enjoyed in previous decades in most developed economies.,But long-term pessimism is unwarranted. With the recent conve

4、rgence of a transformative set of technologies, economies are entering a new era in which artificial intelligence (AI) has the potential to overcome the physical limitations of capital and labor and open up new sources o

5、f value and growth.,Increases in capital and labor are no longer driving the levels of economic growth the world has become accustomed to and desires. Fortunately, a new factor of production is on the horizon, and it pro

6、mises to transform the basis of economic growth for countries across the world.,Indeed, Accenture analyzed 12 developed economies and found that AI has the potential to double their annual economic growth rates by 2035.,

7、To avoid missing out on this opportunity, policy makers and business leaders must prepare for, and work toward, a futurewith artificial intelligence. They must do so not with the idea that AI is simply another productiv

8、ity enhancer. Rather, they must see AI as the tool that can transform our thinking about how growth is created.,4,|,Why artificial intelligence is the future of growth,That missing element is how new technologies affect

9、growth in the economy.,Traditionally, capital and labor are the “factors of production” that drive growth in the economy (see Figure 5). Growth occurs when the stock of capital or labor increase, or when they are used mo

10、re efficiently. The growth that comes from innovations and technological change in the economy is captured in total factor productivity (TFP).,Economists have always thought of new technologies as driving growth through

11、their ability to enhance TFP. This made sense for the technologies that we have seen until now. The great technological breakthroughs over the last century— electricity, railways and IT—boosted productivity dramatically

12、but did not create entirely new workforces.,Given this poor outlook, commentators say that a stagnant economy is the “newnormal.” On an even more pessimistic note, economist Robert Gordon argues that productivity growth

13、 over the next quarter century will continue at the sluggish pace we have experienced since 2004.1 He believes that the past two centuries of “Great Inventions,” such as the steamship and telegraph, are unlikely to be re

14、peated. And this deficit of innovation, combined with unfavorable demographic trends, flagging educational attainment andrising wealth inequality, will slow economic progress.,So, are we experiencing the end of growth a

15、nd prosperity as we know it?,As grim as much of the data undoubtedly is, it misses an important part of the story.,THE NEW FACTOR OF PRODUCTION,Across the globe, rates of gross domestic product (GDP) growth have been shr

16、inking. Moreover, this has been true for three decades. Key measures of economic efficiency are trending sharply downward, while labor-force growth across the developed world is largely stagnant. It is even in decline in

17、 some countries (see Figures 1 to 4).,,Similarly, AI can take the form of physical capital such as robots and intelligent machines. And unlike conventional capital, such as machines and buildings, it can actually improve

18、 over time, thanks to its self-learning capabilities.,Based on our analysis and modeling, we can illustrate what happens when AI is seen as a new factor of production rather than just a productivity enhancer. The impact

19、on projected growth for the United States, for example, is dramatic. As Figure 6 shows, the first scenario is business-as- usual, assuming no AI effect. The second indicates the traditional view of AI as a TFP enhancer w

20、here it has a limited impacton growth. The third scenario shows what happens when AI can act as a new factor of production—there is a transformative effect on growth. This ability of AI to complement and enhance traditi

21、onal factors of production is where its true potential lies.,Today, we are witnessing the take- off of another transformative set oftechnologies, commonly referred to as artificial intelligence (see “What is artificial

22、intelligence?”). Many see AI as similar to past technological inventions. If we believe this, then we can expect some growth, but nothing transformational.,But what if AI has the potential to be not just another driver o

23、f TFP, but an entirely new factor of production? How can this be?,The key is to see AI as a capital-labor hybrid. AI can replicate labor activities at much greater scale and speed, and to even perform some tasks beyond t

24、he capabilities of humans. Not to mention that in some areas it has the ability to learn faster than humans, if not yet as deeply. For example, by using virtual assistants, 1,000 legal documents can be reviewed in a matt

25、er of days instead of taking three people six months to complete.2,,,,,The advance of AI is leading us to rethink fundamental economicrelationships and how value is created.DAVID LEHRER, CEO, CONATIX,5,|,Why artifici

26、al intelligence is the future of growth,Developed economies: The end of growth?,On a variety of key measures, economic data seems to support a mood of long-term pessimism.FIGURE 1: GROSS DOMESTIC PRODUCTSince the 19

27、80s, GDP growth has steadily slowed in many large economies.,Real GDP growth (%, annual average over the period)NB: Data points across the dashed lines indicate the average for the six countries. Source: Oxford Economic

28、s,5.0,4.0,3.0,3.0,2.0,1.0,0.0,-1.0,1980s,1990s,2000s,2010s,,,,,,,,,,,,,,,,,,,,,,,,,,JAPAN,,UNITED STATES,,UNITED KINGDOM,,FRANCE,,ITALY,,GERMANY,,,,,,,,,,,2.1,,,,1.1,,,,1.1,,,,6,|,Why artificial intelligence is the futur

29、e of growth,FIGURE 2: PRODUCTIVITYA key measure of how well an economy uses its existing capital and people is “total factor productivity” (TFP). Data show a weakening of TFP, especially in the past 10 years.,Total fact

30、or productivity (%, annual average over the period)Source: The Conference Board, Total Economic Database,2.5,2.01.5,1.00.5,,0.0-0.5-1.0,,-1.5,,,,,,,3.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,JAPAN,,UNITED STAT

31、ES,,UNITED KINGDOM,,FRANCE,,ITALY,,GERMANY,,7,|,Why artificial intelligence is the future of growth,FIGURE 3: CAPITAL EFFICIENCYThe marginal capital efficiency rate, an indicator of the productivity of capital such as m

32、achines and buildings, has steadily dropped over a 50-year period.,FIGURE 4: LABORAs populations age and birth rates slow, fewer people are available to pick up the slack in the workforce.,Marginal capital efficiency (%

33、, 6-year moving average)Source: European Commission, Annual Macroeconomic Database,Working age population (%, annual average growth over the period)Source: Oxford Economics,1966,1971,1976,1981,1986,1991,1996,2001,200

34、6,2011,2016,,,,,,JAPANUNITED STATES,GERMANY,UNITED KINGDOM,50,,25,,0,,,,,-0.7,-0.1,-0.2,-0.3,0.1,-0.3,0.2,-0.05,0.4,-0.1,0.4,0.5,0.6,0,0.6,0.90.7,0.3,0.2,0.2,-0.6,0.02,,,,,,,,,,,,,,,,,,,,,,2000-2015,,-0.73,,,2016-2030

35、,,,-0.69,8,|,Why artificial intelligence is the future of growth,FIGURE 5: THE AI GROWTH MODELOur model adapts the traditional growth model by including AI as a factor of production.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,

36、,,,,,,,,,,,,,,,,,,,,,,,,,,,,,FIGURE 6: THREE GROWTH SCENARIOS FOR THE UNITED STATES’ ECONOMYAI as a new factor of production can lead to significant growth opportunities for the United States’ economy.7,408,NB:indi

37、cates the change in that factor. Source: Accenture analysis,United States’ gross value added (GVA) in 2035 (US$ billion)Source: Accenture and Frontier Economics,GROWTHADAPTED GROWTH MODEL,Capital,Labor,TFP,Capital,L

38、abor,TFP,AI,TRADITIONAL GROWTH MODEL,UNITED STATES’ GVA,AI-INDUCED TFP,ADDITIONALAI-INDUCED GROWTH,Projected growth without AI,Projected growth with AI’s impact limited to TFP,Projected growth with AI as new factor of p

39、roduction,,,,23,835,,23,835,,,897,897,23,835,,,9,|,Why artificial intelligence is the future of growth,,WCOHNAT EISNATRSTIFICIAL INTELLIGENCE?,AI is not a new field; much of its theoretical and technological underpinning

40、 was developed over the past 70 years by computer scientists such as Alan Turing, Marvin Minsky and John McCarthy. Today, the term refers to multiple technologies that can be combined in different ways to:,SenseComputer

41、 vision and audio processing, for example, are able to actively perceive the world around them by acquiring and processing images, sounds and speech. The use of facial recognition at border control kiosks is one practica

42、l example of how it can improve productivity.,ComprehendNatural language processing and inference engines can enableAI systems to analyze and understand the information collected. This technology is used to power the l

43、anguage translation feature of search engine results.,ActAn AI system can take action through technologies such as expert systems and inference engines, orundertake actions in the physical world. Auto-pilot features an

44、d assisted- braking capabilities in cars are examples of this.,All three capabilities are underpinned by the ability to learn from experience and adapt over time. AI already exists to some degree in many industries but t

45、he extent to which it is becoming part of our daily lives is set to grow fast.,,,,,,10,|,Why artificial intelligence is the future of growth,,2C. GrOowtNh in TbigEdatNa.,TS,Two key factors are enabling AI growth:1. Unl

46、imited access to computing power.Public cloud computing was estimated to reach almost US$70 billion in 2015 worldwide. Data storage has also become abundant.,Emerging AI technologies,Global data has seen a compound annu

47、al growth rate (CAGR) of more than 50 percent since 2010 as more of the devices around us have become connected. As Barry Smyth, professor of computer science at University College Dublin, told us: “Data is to AI what fo

48、od is to humans.”So in a more digital world, the exponential growth of data is constantly feeding AI improvements.,,,Data VisualizationActSource: Accenture analysis,ILLUSTRATIVE SOLUTIONS,,,Comprehend,AI TECHNOLOGI

49、ES,,,,,,,,,,Virtual AgentsSenseIdentity Analytics,Recommendation Systems,Cognitive Robotics,Speech Analytics,,,,11,|,Why artificial intelligence is the future of growth,12,|,Why artificial intelligence is the future

50、 of growth,THREE CHANNELS OF AI-LED GROWTH,With AI as the new factor of production, it can drive growth in at least three important ways. First, it can create a new virtual workforce—what we call “intelligent automation.

51、” Second, AI can complement and enhance the skills and ability of existing workforces and physical capital. Third, like other previous technologies, AI can drive innovations in the economy. Over time, this becomes a cata

52、lyst for broad structural transformation as economies using AI not only do things differently, they will also do different things.,Intelligent automationThe new AI-powered wave of intelligent automation is already creat

53、ing growth through a set of features unlike those of traditional automation solutions.,The first feature is its ability to automate complex physical world tasks that require adaptability and agility. Consider the work of

54、 retrieving items in a warehouse, where companies have relied on people’s ability to navigate crowded spaces and avoid moving obstacles. Now, robots from Fetch Robotics use lasers and 3D depth-sensors to navigate safely

55、and work alongside warehouse workers. Used in tandem with people, the robots can handle the vast majority of items in a typical warehouse.3,Whereas traditional automation technology is task specific, the second distinct

56、feature of AI-powered intelligent automation is its ability to solve problems across industries and job titles. For instance, Amelia—an AI platform by IPsoft with natural language processing capabilities—has supported ma

57、intenance engineers in remote locations. Having read all the manuals, Amelia can diagnose a problem and suggest a solution.4 This platform has also learned the answers to the 120 questions most frequently asked by mort

58、gage brokers and has been used in a bank to handle such financial queries, traditionally a labor- intensive task.5,13,|,Why artificial intelligence is the future of growth,The third and most powerful feature of intellige

59、nt automation is self-learning, enabled by repeatability at scale. Amelia, like a conscientious employee, recognizes the gaps in her own knowledge and takes steps to close them. If Amelia is presented with a question tha

60、t she cannot answer, she escalates it to a human colleague, then observes how the person solves the problem. The self-learning aspect of AI isa fundamental change. Whereas traditional automation capital degrades over ti

61、me, intelligent automation assetsconstantly improve.,Labor and capital augmentationA significant part of the economic growth from AI will come not from replacing existing labor and capital, but in enabling them to be u

62、sed much more effectively.,For example, AI can enable humans to focus on parts of their role that add the most value. Hotel staff spend a lot of their time making routine room deliveries. Why not assign the task to Rela

63、y, an autonomous service industry robot developed by Savioke, instead? Last year, the Relay fleet made more than 11,000 guest deliveries in the five large hotel chains where it is deployed. As Steve Cousins, CEO of Savio

64、ke, told us: “Relay enables staff to redirect their time toward increasing customer satisfaction.”,Also, AI augments labor by complementing human capabilities, offering employees new tools to enhance their natural intell

65、igence. For example, Praedicat,a company providing risk modeling services to property and casualty insurers, is improving underwriters’ risk-pricing abilities. Using machine learning andbig data processing technologies

66、, its AI platform reads more than 22 million peer- reviewed scientific papers to identify serious emerging risks. As a result, underwriters can not only price riskmore accurately, but also create new insurance products.

67、6,AI can also improve capital efficiency— a crucial factor in industries where itrepresents a large sunk cost. For instance, in manufacturing, industrial robotics company Fanuc has teamed up with Cisco and other firms t

68、o create a platform to reduce factory downtime—estimated at one major automotive manufacturer to cost US$20,000 per minute.7 The Fanuc Intelligent Edge Link and Drive (FIELD) system is an analytics platform powered by ad

69、vanced machine learning. It captures and analyzes data from disparate partsof the manufacturing process to improve manufacturing production. Already FIELD has been deployed in an 18-month “zero downtime” trial at one ma