To Be a Responsible AI Leader, Focus on Being Responsible

Findings from the 2022 Responsible AI Global Executive Study and Research Project

by: Elizabeth M. Renieris, David Kiron, and Steven Mills


As AI’s adoption grows more widespread and companies see increasing returns on their AI investments, the technology’s risks also become more apparent.1 Our recent global survey of more than 1,000 managers suggests that AI systems across industries are susceptible to failures, with nearly a quarter of respondents reporting that their organization has experienced an AI failure, ranging from mere lapses in technical performance to outcomes that put individuals and communities at risk. It is these latter harms that responsible AI (RAI) initiatives seek to address.

Meanwhile, lawmakers are developing the first generation of meaningful AI-specific legislation.2 For example, the European Union’s proposed AI Act would create a comprehensive scheme to govern the technology. And in the U.S., lawmakers in New York, California, and other states are working on AI-specific regulations to govern its use in employment and other high-risk contexts.3 In response to the heightened stakes around AI adoption and impending regulations, organizations worldwide are affirming the need for RAI, but many are falling short when it comes to operationalizing RAI in practice.

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There are, however, exceptions. A number of organizations are bridging the gap between aspirations and reality by making a philosophical and material commitment to RAI, including investing the time and resources needed to create a comprehensive RAI program. We refer to them as RAI Leaders or Leaders. They appear to enjoy clear business benefits from RAI. Our research indicates that Leaders take a more strategic approach to RAI, led by corporate values and an expansive view of their responsibility toward a wide array of stakeholders, including society as a whole. For Leaders, prioritizing RAI is inherently aligned with their broader interest in leading responsible organizations.

This MIT Sloan Management Review and Boston Consulting Group report is based on our global survey, interviews with several C-level executives, and insights gathered from an international panel of more than 25 AI experts.

About the Authors

Elizabeth M. Renieris is a senior research associate at Oxford’s Institute for Ethics in AI and the founder and CEO of Hackylawyer, a law and policy consultancy. A former fellow at Stanford’s Digital Civil Society Lab, Harvard’s Carr Center for Human Rights Policy, and the Berkman Klein Center for Internet & Society, Renieris is the author of Beyond Data: Reclaiming Human Rights at the Dawn of the Metaverse (MIT Press, 2023).

David Kiron is the editorial director for research at MIT Sloan Management Review and program lead for its Big Ideas research initiatives. Previously, he was a senior researcher at Harvard Business School and a researcher at the Global Development and Environment Institute at Tufts University. He is coauthor of the forthcoming book Workforce Ecosystems: Reaching Strategic Goals With People, Partners, and Technology (MIT Press, 2023).

Steven Mills is a managing director and partner at Boston Consulting Group (BCG), where he serves as the chief AI ethics officer. He is responsible for developing BCG’s internal responsible AI program as well as guiding clients as they design and implement their own RAI programs. Mills has been recognized by DataIQ as one of the 100 most influential people in data (2022) and by Forbes as one of 15 AI ethics leaders shaping the future (2021).

Contributors

François Candelon, Maxime Courtaux, Michele Lee DeFilippo, Todd Fitz, Carolyn Ann Geason-Beissel, Franz Gravenhorst, Abhishek Gupta, Sarah Johnson, Tom Porter, Lauren Rosano, Allison Ryder, Max Santinelli, Sean Singer, Barbara Spindel, Peter Strutt, and Yunke Xiang

To cite this report, please use:

Elizabeth M. Renieris, David Kiron, and Steven Mills, “To Be a Responsible AI Leader, Focus on Being Responsible,” MIT Sloan Management Review and Boston Consulting Group, September 2022.

Acknowledgments

We thank each of the following individuals, who were interviewed for this report:

Kathy Baxter, principal architect, ethical AI practice, Salesforce

Linda Leopold, head of responsible AI and data, H&M Group

Katia Walsh, chief global strategy and AI officer, Levi Strauss & Co.

Brian Yutko, vice president and chief engineer, sustainability and future mobility, Boeing

MIT Sloan Management Review

At MIT Sloan Management Review (MIT SMR) we explore how leadership and management are transforming in a disruptive world. We help thoughtful leaders capture the exciting opportunities — and face down the challenges — created as technological, societal, and environmental forces reshape how organizations operate, compete, and create value.

MIT Sloan Management Review Big Ideas

MIT Sloan Management Review’s Big Ideas Initiatives develop innovative, original research on the issues transforming our fast-changing business environment. We conduct global surveys and in-depth interviews with frontline leaders working at a range of companies, from Silicon Valley startups to multinational organizations, to deepen our understanding of changing paradigms and their influence on how people work and lead.

Boston Consulting Group

Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we work closely with clients to embrace a transformational approach aimed at benefiting all stakeholders — empowering organizations to grow, build sustainable competitive advantage, and drive positive societal impact. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives that question the status quo and spark change. BCG delivers solutions through leading-edge management consulting, technology and design, and corporate and digital ventures. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, fueled by the goal of helping our clients thrive and enabling them to make the world a better place.

GAMMA, part of BCG X

BCG X is Boston Consulting Group’s home for tech-build and design talent. The multidisciplinary unit develops cutting-edge AI, visionary business ventures, and unique software and products powered by the combined expertise of BCG Digital Ventures, BCG GAMMA, and BCG Platinion. Together as BCG X, this team collaborates at all levels with the world’s leading organizations to solve their biggest strategy and technology challenges. BCG X is at the forefront of thought leadership, with a breadth of industry-recognized experts and deep engagement in industry thought leadership.

References

1. T.H. Davenport and R. Bean, “Companies Are Making Serious Money With AI,” MIT Sloan Management Review, Feb. 17, 2022, https://sloanreview.mit.edu.

2. For a summary of legislative action taken in the U.S., see C. Kraczon, “The State of State AI Policy (2021-22 Legislative Session),” Electronic Privacy Information Center, Aug. 8, 2022, https://epic.org.

3. See, for example, N.E. Price, “New York City’s New Law Regulating the Use of Artificial Intelligence in Employment Decisions,” JD Supra, April 11, 2022, http://www.jdsupra.com; and J.J. Lazzarotti and R. Yang, “Draft Regulations in California Would Curb Use of AI, Automated Decision Systems in Employment,” Jackson Lewis, April 11, 2022, http://www.californiaworkplacelawblog.com.

4. S. Ransbotham, S. Khodabandeh, R. Fehling, et al., “Winning With AI,” MIT Sloan Management Review and Boston Consulting Group, Oct. 15, 2019, https://sloanreview.mit.edu.

5. D. Kiron, E. Renieris, and S. Mills, “Why Top Management Should Focus on Responsible AI,” Sloan Management Review, April 19, 2022, https://sloanreview.mit.edu.

6. Leaders are the most mature of the three maturity clusters identified by analyzing the survey results. An unsupervised machine learning algorithm (K-mean clustering) was used to identify naturally occurring clusters based on the scale and scope of the organization’s RAI implementation. Scale is defined as the degree to which RAI efforts are deployed across the enterprise (e.g., ad hoc, partial, enterprisewide). Scope includes the elements that are part of the RAI program (e.g., principles, policies, governance) and the dimensions covered by the RAI program (e.g., fairness, safety, environmental impact). Leaders were the most mature in terms of both scale and scope.

7. We offer a deeper analysis of the connection between RAI and CSR here: E.M. Renieris, D. Kiron, and S. Mills, “Should Organizations Link Responsible AI and Corporate Social Responsibility? It’s Complicated,” MIT Sloan Management Review, May 24, 2022, https://sloanreview.mit.edu.

8. To assess whether an organization’s AI use was mature or immature, we asked respondents, “What is the level of adoption of AI in your organization?” Those who selected “AI at scale with applications in most business and functional areas” or “Large number of applications in select business and functional areas” were classified as mature, and those who answered, “Only prototypes and/or pilots, without full-scale implementations” or “Some applications deployed and implemented” were classified as immature.

9. E.M. Renieris, D. Kiron, and S.D. Mills, “RAI Enables the Kind of Innovation That Matters,” MIT Sloan Management Review, May 24, 2022, https://sloanreview.mit.edu.

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