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In collaboration withNovember 2021The Cultural Benefits of Artificial Intelligence in the Enterpriseby Sam Ransbotham, Franois Candelon, David Kiron, Burt LaFountain, and Shervin KhodabandehAUTHORSSam Ransbotham is a professor in the information systems department at the Carroll School of Management at Boston College, as well as guest editor for MIT Sloan Management Reviews Artificial Intelligence and Business Strategy Big Ideas initiative.Franois Candelon is a senior partner and managing director at BCG and the global director of the BCG Henderson Institute. He can be contacted at .David Kiron is the editorial director of MIT Sloan Management Review and is program lead for its Future of the Workforce and Artificial Intelligence and Business Strategy projects. He can be contacted at dkironmit.edu.Burt LaFountain is a partner and managing director at BCG and a core member of BCG GAMMA. He can be reached at . Shervin Khodabandeh is a senior partner and managing director at BCG and the coleader of BCG GAMMA (BCGs AI practice) in North America. He can be contacted at .SPECIAL CONTRIBUTORSMichael Chu, Matthieu Gombeaud, Su Min Ha, Allison Ryder, and Barbara SpindelCONTRIBUTORSSylvain Duranton, Todd Fitz, Carolyn Ann Geason-Beissel, Michele Lee DeFilippo, Janet Parkinson, Martin Reeves, Lauren Rosano, Lu Sun, and Rachel ZhaiThe research and analysis for this report was conducted under the direction of the authors as part of an MIT Sloan Management Review research initiative in collaboration with and sponsored by Boston Consulting Group.To cite this report, please use:S. Ransbotham, F. Candelon, D. Kiron, B. LaFountain, and S. Khodabandeh, “The Cultural Benefits of Artificial Intelligence in the Enterprise,” MIT Sloan Management Review and Boston Consulting Group, November 2021. REPRINT NUMBER 63270 Copyright Massachusetts Institute of T echnology, 2021. All rights reserved.SUPPORTING SPONSORSCONTENTS1 Executive Summary3 Introduction: Cultural Benefits of AI6 T eam-Level Cultural Benefits13 Organization-Level Cultural Benefits17 ConclusionExecutive SummaryThe benefits of artificial intelligence go well beyond improved efficiency and decision-making. AI can also improve organizational effectiveness and strengthen teams and enterprise cultures.Artificial intelligence can generate cultural as well as financial benefits for organizations. With AI systems in place, teams can perform tasks with more pride and confidence and collaborate more effectively: They can actually get stronger. These cultural benefits can penetrate the foundation of business operations, improving assumptions that drive organizational behaviors and ensuring the pursuit of smarter goals. When conducting our research, we heard story after story from executives familiar with AI implementations in their organizations. The overarching message was clear and backed up by survey data: Business culture affects AI deployments, and AI deployments affect business culture. This MIT SMR-BCG report based on a global survey of 2,197 managers and interviews with 18 executives identifies a wide range of AI-related cultural benefits at both the team and organizational levels. Among survey respondents with AI implementations that improved efficiency and decision-making, for example, more than 75% also saw improvements in team morale, collabora-tion, and collective learning. Culture change from using AI transcends the legitimate, but myopic, promise that AI will liberate workers from drudgery.These cultural changes are more than a side benefit. AI-related cultural and financial benefits build on each other. Survey respondents who saw signifi-cant financial benefits from their AI initiatives were 10 times more likely to change how they measure success than those who saw no such benefits. In some cases, AI helped leaders identify new performance drivers, which led to new assumptions, objectives, measures, and patterns of behavior, along with new areas of accountability. AI also helped these organizations realign behaviors and become more competitive. Building a culture that supports innovation with AI has an effect on com-petitiveness. Our research found that respondents who use AI primarily to explore new ways of creating value are far more likely to improve their abil-ity to compete with AI than those who use AI primarily to improve existing processes. Respondents who said they use AI primarily to explore were 2.7 times more likely to agree that their company captures opportunities from adjacent industries because of AI than respondents who use AI primarily to improve existing processes.Whether its reconsidering business assumptions or empowering teams, man-aging relationships among culture, AI use, and organizational effectiveness is critical to increasing AIs value to an organization. This report offers a data-driv-en analysis of these relationships at both the team and organization levels.The Cultural Benefits of Artificial Intelligence in the Enterprise 1MIT SLOAN MANAGEMENT REVIEW BCG 2Introduction: Cultural Benefits of AIAI implementations that improve effectiveness often strengthen team and enterprise cultures. Executives intimately involved with developing and im-plementing AI solutions offered numerous examples of how artificial intel-ligence helped their organizations become more efficient and make better decisions. Whats more, their team cultures were changing in response to these new levels of effectiveness; the cultural changes encompassed what teams learned, how they learned, how they worked together, and, in some instances, what they enjoyed about their work. Many teams that used AI became stronger teams. Pierre-Yves Calloch, chief digital officer at Pernod Ricard, the worlds sec-ond-largest seller of wine and spirits, offers a case in point. The company began using AI technology to optimize salespeoples store visits. Historically, the sales staff had relied heavily on their own experience to decide which stores to visit. The company expected that its new AI-based system of digital assistants, which uses data to prioritize stores, would encounter resistance. However, salespeople embraced the technology, which augments rather than replaces their own knowledge. Calloch fostered trust in the system by involving recognized business experts in the tools design and gathering extensive feedback from pilot users. His team ensured that the reasons for the AI systems recommendations were clear, and clearly communicated, to the salespeople. In addition, his analytics team used interviews with the business experts to explore unexpected insights and feed those insights into the recommendation engine. That bolstered the tools credibility among the experts and improved the effectiveness of the tool itself. According to Calloch, salespeople told him, “Theres no way Im going back to my previous way of doing things. I trust that the system has been looking at a lot of options when recommending the 20 stores that I should visit this week. Ill add some because there is outside information that I have and the tool doesnt have.” The technology also provides employees with new recommendations that strengthen their sales pitches. “The system is recommending listing only relevant products matching the store profile, for instance, because of the category of consumers living around the store and other factors. That gives salespeople more confidence, more clarity, and higher morale,” says Calloch. Using AI not only directly improved efficiency and decision quality but indirectly changed team culture through its effects on confidence, clarity, and morale.The Cultural Benefits of Artificial Intelligence in the Enterprise 3Our global survey attests that Pernod Ricard isnt alone in experiencing AIs effect on team culture: Many respon-dents who saw improvements in efficiency and decision quality because of AI also saw team-level improvements in morale (79%) and other cultural areas.But AIs effects on culture dont stop at the team level. Our research further suggests that the cultural benefits of AI adoption can extend to organizations as a whole. For example, we found that some executives employ AI to reassess strategic and operational assumptions. In-creasingly, executives are recognizing that they can use AI to discern performance drivers that they themselves cannot identify through intuition and experience alone. Radha Subramanyam, president and chief research and analytics officer at CBS, describes the broadcast networks efforts to critically assess long-standing organizational assumptions about how it measures the success of TV shows. “I gave our AI teams 50 years of KPIs key perfor-mance indicators and 50 years of consumer research,” she recalls. “I said, Here are the things that we believe are important in this consumer research quantitative and qualitative. Im giving you all the raw data. Are the things that I habitually look at the right KPIs to drive my mega-KPI, or are they wrong?”The analysis affirmed the utility of two historical KPIs but also added two new KPIs to the set. “We got better by going through this AI exercise,” Subramanyam not-ed. “The analysis changed what we were looking for and helped improve our performance.” For CBS, AI provided both the opportunity and the means for reexamining fundamental assumptions about business operations and organizational effectiveness. The assumptions that guide team behaviors and enterprise goals are central to organizational culture.1Revising organizational assumptions and measurements is fairly typical of organizations that adopt AI: 64% of companies that have integrated AI into their processes say that their use of AI led to changes in their KPIs. In some cases, AI solutions directly reveal new performance drivers, as at CBS, where they led to new KPIs. In other cases, using AI enables stronger performance, which obsolesces legacy measurements that no longer reflect desired goals. Realigning behaviors to achieve new ob-jectives often has a direct effect on culture.ABOUT THE RESEARCHThis report presents findings from the fifth annual research effort between MIT Sloan Management Review and Boston Consulting Group on artificial intelligence and busi-ness strategy. In the spring of 2021, we fielded a global survey and analyzed records from 2,197 total respondents representing 29 industries and 111 countries. We then interviewed 18 executives researching or leading AI initia-tives in large organizations in a broad range of industries, including financial services, media and entertainment, retail, travel and transportation, and life sciences. Our research offers a detailed analysis of a dynamic between culture, AI use, and organizational effectiveness. In addition to our own field research, we used existing organizational culture research to inform our use of the term “culture.”MIT SLOAN MANAGEMENT REVIEW BCG 4Our research identifies a continuous dynamic among culture, AI use, and organizational effectiveness. (see figure 1.) We use this Culture-Use-Effectiveness (C-U-E) dynamic to explain mutually reinforcing relationships at both the team and organization levels. These relation-ships offer a useful perspective on how AI adoption can influence managerial assumptions, team behaviors, and overall organizational competitiveness.The C-U-E dynamic is difficult to achieve at scale. Exec-utives need to learn what AI can do for teams and the organization, and develop a common language for deci-sion-making with AI. Managers need to elicit active support from employees who must work with AI solutions that replace or augment existing practices. After AI solutions initial implementation, organizations must continuously adapt them, which requires ongoing participation from AI teams and end users. Once AI solutions prove to be effective, the resulting cultural and productivity benefits encourage even more AI use throughout the enterprise. AI that is effective at the team level, however, doesnt always yield financial success at the organization level. Only 11% of organizations in our survey attributed sub-stantial financial benefits to their AI initiatives, which is the same result we obtained from our survey last year.2 It may be that few companies are implementing AI at a scale sufficient to generate “substantial” financial benefits. But another possible explanation is that those organizations that obtain substantial financial benefits have begun to master the C-U-E dynamic. They learned both how to culturally adopt and benefit from AI, and how to use AI to glean financial rewards. Our research suggests that these are connected, not separate, activities. FIGURE 1 The Culture-Use-Effectiveness DynamicImproving each component of the C-U-E dynamic can lead to a virtuous cycle of cultural improvement.The Cultural Benefits of Artificial Intelligence in the Enterprise 5Team-Level Cultural BenefitsAI-based solutions that generate new ways of working can incite resistance from teams entrenched in existing cultures. Anju Gupta, vice president of data science and analytics at Northwestern Mutual, acknowledges that when companies introduce new AI initiatives, “there is this natural resistance that youll bump up against.” Culture is like a teams immune system: It is for the group what defense mechanisms are for the individual.3 Our research indicates that managers often recognize the need to cultivate team acceptance of AI, such as by including end users in the development process, building trust in AI system performance, and encouraging teams to be open to changing their work processes. (see the sidebar “building trust to cultivate ai benefits,” page 7.) Our findings also distinguish the culture change re-quired to adopt AI from cultural changes that emerge after adopting AI. Figure 2 shows the C-U-E dynamic at the team level: Team culture can improve AI adoption, which in turn improves team effectiveness, which in turn improves team culture. Learning is a key component of each element in the dynamic.FIGURE 2 The T eam Culture-Use-Effectiveness DynamicAs AI helps improve efficiency and decision quality, team culture benefits.AI USEEFFECTIVENESSTEAMCULTUREIMPROVEIMPROVEIMPROVEMIT SLOAN MANAGEMENT REVIEW BCG 6BUILDING TRUST TO CULTIVATE AI BENEFITSBoth financial and nonfinancial benefits from AI depend on employees working with and trusting AI. Y et our survey respondents described numerous reasons why end users may mistrust AI solutions. (SEE FIGURE 3.)Close to half the respondents believed that mistrust of AI stemmed from a lack of understanding (49%) or training (46%). Paul Pallath, global technology head of data, analytics, and AI at Levi Strauss & Co., said that the company invested widely to improve understanding; it selected employees “from various different domains, from the retail store to people in IT to people in business, and called them into an eight-week, highly immersive AI/ML boot camp. ” The first cohort, which graduated in May 2021, consisted
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