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Annual MIT Sloan Management Review-Boston Consulting Group Study Finds Significant Financial Benefits With AI Are Noticeably Amplified When Organizations Develop Multiple Effective Ways for Humans and AI to Learn Together

A Mere 10% of Organizations Achieve Significant Financial Benefits with AI -- Those That Do, Deploy Multiple Human-Machine Learning Approaches

MIT Sloan Management Review and BCG

News provided by

MIT Sloan Management Review

Oct 20, 2020, 00:01 ET

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CAMBRIDGE, Mass., Oct. 20, 2020 /PRNewswire/ -- According to a major study released today by MIT Sloan Management Review (MIT SMR), BCG GAMMA, and BCG Henderson Institute, despite increased investment and activity, only 10% of organizations are achieving significant financial benefits with artificial intelligence. The study highlights the often-underestimated role of mutual learning between humans and machines in generating value from AI. Those companies that draw on multiple types of interaction and feedback between humans and AI are six times more likely to amplify their success with AI.

The study, as reported in "Expanding AI's Impact With Organizational Learning," is based on a survey of more than 3,000 managers in 29 industries in 112 countries and several in-depth interviews with leading experts. It includes a four-year longitudinal examination of cross-industry AI adoption and a variety of use cases. The authors' analysis found that multiple foundational steps and process improvements enable companies to generate value with AI, but ultimately, companies achieve the most value when mutual learning occurs between humans and machines.  

The study also highlights the investments organizations make to maximize value:

  • Building foundational capabilities — AI infrastructure, talent, and strategy — increases the likelihood of achieving significant benefits by 19%.
  • Scaling AI across different use cases and going beyond automation increases the likelihood by another 18%.
  • Achieving organizational learning with AI (drawing on multiple interaction modes between humans and machines) and building feedback loops between human and AI increases that likelihood by another 34%.

Organizations that learn with AI share three essential characteristics:

  • They facilitate systematic and continuous learning between humans and machines.
  • They develop multiple ways for humans and machines to interact.
  • They change to learn, and learn to change.

Organizations that systematically invest in these activities are 73% more likely to achieve significant impact with AI.

"Isolated AI applications can be powerful. But we find that organizations leading with AI haven't changed processes to use AI. Instead, they've learned with AI how to change processes. The key isn't teaching the machines. Or even learning from the machines. The key is learning with the machines—systematically and continuously," says report coauthor Sam Ransbotham. Organizational learning with AI demands, builds on, and leads to significant organizational change. Additional study data reveals that as of 2020:

  • 70% of global executive respondents understand how AI can generate business value, an increase from 57% in 2017.
  • 59% of global executive respondents have an AI strategy, an increase from 39% in 2017.
  • 57% of global executive respondents affirm that their companies are piloting or deploying AI, an increase from 46% in 2017.
  • A growing number of companies recognize a business imperative to improve their AI competencies and data infrastructures.
  • Despite these trends, just 1 in 10 companies generates significant financial benefits with AI.

"The single most critical driver of value from AI is not algorithms, nor technology — it is the human in the equation," says report coauthor Shervin Khodabandeh. "We continue to see that despite more companies investing in AI technologies and launching AI initiatives, only a small fraction get meaningful value. What this select group do well is that they create integrated AI-Human systems, where AI learns from humans and humans learn from AI. And the more different ways of learning between the two, the more value there is to get."

The report features case studies resulting from interviews with senior leaders from companies ranging from retail to energy, legacy to born-digital, across the world.

"Getting significant financial benefits with AI is not the prerogative of digital native companies only," notes report coauthor François Candelon. "Throughout this research, it clearly appears that success is not bound by legacy, industry, or geography. An incumbent, be it a European energy company like Repsol, an Indian telco like Bharti Airtel, or a U.S. retailer like Walmart, can win by taking the right bold moves and make organizational learning with AI become a reality."

"One big takeaway from this research is that companies need to calibrate their investments in technology, people, and learning processes," adds report coauthor David Kiron. "Financial investments in technology and people are important, but investing social capital in learning is critical to creating significant value with AI."

Along with the report, MIT SMR and Boston Consulting Group have launched an executive-interview podcast series, Me, Myself, and AI, where report coauthors Ransbotham and Khodabandeh talk to leaders successfully leveraging AI in their companies and learn how they did it. The first two episodes, featuring Walmart's vice president of machine learning and Humana's senior vice president of digital health and analytics are available here and on all major podcast platforms.

To read the full report, please visit MIT Sloan Management Review. To read more about the podcast series, please visit Me, Myself, and AI.

MEDIA CONTACTS:
Emily Lavelle, [email protected], +1 212-390-1328
Eric Gregoire, [email protected], +1 617-850-3783

About the Authors
Sam Ransbotham is a professor in the information systems department at the Carroll School of Business at Boston College, as well as guest editor for MIT Sloan Management Review's Artificial Intelligence Big Ideas initiative. Shervin Khodabandeh is a senior partner and managing director at BCG, and the coleader of BCG's AI practice in North America. David Kiron is the executive editor of MIT Sloan Management Review, where he directs the publication's Big Ideas program. François Candelon is a senior partner and managing director at BCG, and the global director of the BCG Henderson Institute. Michael Chu is a partner and associate director at BCG, and a core member of BCG GAMMA. Burt LaFountain is a partner and managing director at BCG and a core member of BCG GAMMA.

About MIT Sloan Management Review
At MIT Sloan Management Review (MIT SMR), we share with our readers an excitement and curiosity about how the practice of management is transforming in the digital age. Our expert contributors help leaders explore the trends that are shaping how organizations operate, compete, and create value in a technology-fueled world. We deliver the kind of evidence-based analysis and practical insight that will inspire leaders to do great work.

About 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 help clients with total transformation — inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact.

To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures — and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.

About BCG GAMMA
BCG GAMMA is BCG's global team dedicated to applying artificial intelligence and advanced analytics to critical business problems at leading companies and organizations. The team includes 900-plus data scientists and engineers who utilize AI and advanced analytics (e.g., machine learning, deep learning, optimization, simulation, natural language, and image analytics, etc.) to build solutions that transform business performance. BCG GAMMA's approach builds value and competitive advantage at the intersection of data science, technology, people, business processes, and ways of working. For more information, please visit our web page.

About BCG Henderson Institute
The BCG Henderson Institute is Boston Consulting Group's strategy think tank, dedicated to exploring and developing valuable new insights from business, technology, and science by embracing the powerful technology of ideas. The Institute engages leaders in provocative discussion and experimentation to expand the boundaries of business theory and practice and to translate innovative ideas from within and beyond business. For more ideas and inspiration from the Institute, please visit http://bcghendersoninstitute.com.

SOURCE MIT Sloan Management Review

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