Expanding AI’s Impact With Organizational Learning

by: Sam Ransbotham, Shervin Khodabandeh, David Kiron, François Candelon, Michael Chu, and Burt LaFountain
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Only 10% of companies obtain significant financial benefits from artificial intelligence technologies. Why so few?

Our research shows that these companies intentionally change processes, broadly and deeply, to facilitate organizational learning with AI. Better organizational learning enables them to act precisely when sensing opportunity and to adapt quickly when conditions change. Their strategic focus is organizational learning, not just machine learning.

Organizational learning with AI is demanding. It requires humans and machines to not only work together but also learn from each other — over time, in the right way, and in the appropriate contexts. This cycle of mutual learning makes humans and machines smarter, more relevant, and more effective. Mutual learning between human and machine is essential to success with AI. But it’s difficult to achieve at scale.

Our research — based on a global survey of more than 3,000 managers, as well as interviews with executives and scholars — confirms that a majority of companies are developing AI capabilities but have yet to gain significant financial benefits from their efforts. More than half of all respondents affirm that their companies are piloting or deploying AI (57%), have an AI strategy (59%), and understand how AI can generate business value (70%). These numbers reflect statistically significant increases in adoption, strategy development, and understanding from four years ago. What’s more, a growing number of companies recognize a business imperative to improve their AI competencies. Despite these trends, just 1 in 10 companies generates significant financial benefits with AI.

We analyzed responses to over 100 survey questions to better understand what really enables companies to generate significant financial benefits with AI. We found that getting the basics right — like having the right data, technology, and talent, organized around a corporate strategy — is far from sufficient. Only 20% of companies achieve significant financial benefits with these fundamentals alone. Getting the basics right and building AI solutions that the business wants and can use improve the odds of obtaining significant financial benefits, but to just 39%.

Our key finding: Only when organizations add the ability to learn with AI do significant benefits become likely. With organizational learning, the odds of an organization reporting significant financial benefits increase to 73%.

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References

1. Our interpretation of “significant financial benefits” necessarily varies based on company revenue. See “About the Research” for details.

2. 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.

3. S. Ransbotham, D. Kiron, P. Gerbert, et al., “Reshaping Business With Artificial Intelligence,” MIT Sloan Management Review and Boston Consulting Group, Sept. 6, 2017, https://sloanreview.mit.edu.

4. S. Ransbotham, P. Gerbert, M. Reeves, et al., “Artificial Intelligence in Business Gets Real,” MIT Sloan Management Review and Boston Consulting Group, Sept. 17, 2018, https://sloanreview.mit.edu.

5. Ransbotham et al., “Winning With AI.”

6. Ransbotham et al., “Winning With AI.”

7. Our survey results indicate that smaller businesses — in contrast with larger organizations — capture most of their AI-related benefits from learning with the most autonomous mode (AI decides and implements). One reason may be that smaller companies typically have less organizational complexity, which can make it easier to realize significant financial benefits from automation than at larger companies.

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