A Mere 10% of Organizations Achieve Significant Financial Benefits With AI — Those That Do Deploy Multiple Human-Machine Learning Approaches
CAMBRIDGE, MA—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 6X 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 following investments organizations make to maximize value:
Organizations that learn with AI share three essential characteristics:
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:
“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 human and human learns 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 Airtel Bharti 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, & 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.
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.
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.
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 webpage.
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