Organizations Combining Organizational Learning and AI-Specific Learning Are up to 80% More Effective at Managing Uncertainty

New MIT SMR and BCG Research Quantitatively and Qualitatively Links Organizational Learning, AI-Specific Learning, and the Ability to Manage Rapidly Changing Business Environments

BOSTON—Addressing uncertainty is a critical challenge for leaders today as geopolitical tensions, shifting consumer preferences, talent disruptions, evolving regulations, and rapid technological advancements increasingly complicate the business landscape. According to a new report by MIT Sloan Management Review (MIT SMR) and Boston Consulting Group (BCG), artificial intelligence, a major source of uncertainty in its own right, is essential for meeting this challenge.

The report, Learning to Manage Uncertainty, With AI, presents findings from the eighth annual global research study on artificial intelligence and business strategy by MIT SMR and BCG. It draws from a global survey of 3,467 respondents across 21 industries and 136 countries, along with interviews with nine executives leading AI initiatives in sectors such as financial services, technology, retail, travel, transportation, and health care.

“AI adoption jumped 20% last year, driven by interest in generative AI, as 91% of organizations now expect GenAI to be core to the strategy in at least parts of their organization,” said report coauthor Sam Ransbotham, professor at Boston College. “This increased AI use isn’t causing workers to panic about their jobs, with respondents far more hopeful (84%) than fearful (20%). Instead, augmenting organizational learning with AI-based learning enhances the knowledge capture, synthesis, and dissemination that organizations depend on to manage the myriad uncertainties they currently face.”

“Our previous research found that organizations with superior learning capabilities are more likely to obtain significant financial benefits from their AI use,” said Shervin Khodabandeh, a BCG managing director, senior partner, and coauthor of the report. “Now we find that the reverse is also true. Using AI can improve organizational learning capabilities, and these learning improvements are tied to not only enhanced financial results but also the ability to manage strategy-related uncertainties.”

Most Organizations Lack Strong Learning Capabilities Despite Facing Widespread Uncertainty

The report defines organizational learning as “an organization’s capability to change its knowledge through experience.” The research finds that organizations that combine organizational learning with AI-specific learning outperform organizations that do neither or employ either alone.

Of the companies surveyed, 59% reported low levels of both organizational and AI-specific learning and only 29% of respondents say their company has strong organizational learning.

Organizations Combining AI and Learning See Greater Success 

According to the report, 15% of organizations integrate AI into their learning capabilities. These organizations — referred to in the report as Augmented Learners — are:

  • 1.6 times more likely than those with limited learning capabilities to manage various environmental and firm-specific uncertainties, including unexpected technological, regulatory, and workforce changes.
  • Twice as likely to be prepared to manage talent-related disruptions compared with organizations that have limited learning capabilities.
  • 60% to 80% more likely to be effective at managing uncertainties in their external environments than Limited Learners—companies with limited learning capabilities.
  • 1.4 times more likely to recognize some revenue benefits from AI compared with Limited Learners.

Augmented Learners Are Prepared to Manage Many Types of Uncertainty

Organizational learning and AI-specific learning (augmented learning) help enterprises manage uncertainty and disruptions from talent mobility, changing technology, and evolving regulatory and legal requirements. The survey results show a clear link between organizational learning and preparedness for talent mobility disruptions. Only 39% of Limited Learners feel ready to manage knowledge loss from departing employees, while this rises to 64% in those with strong learning capabilities. Using AI can further contribute to this readiness: Eighty-three percent of Augmented Learners are prepared to deal with the uncertainty of knowledge disruption from talent mobility—twice as much as Limited Learners.

Compared with Limited Learners, Augmented Learners are significantly more likely to be prepared to deal with uncertainty from technology disruptions (86% versus 49%) and regulatory disruptions (79% versus 48%). On the regulatory front, large organizations with global operations can use AI to navigate complex, uncertain regulatory frameworks that vary from one country to the next. Augmented learning organizations have an advantage here because they have abilities that those unable to learn with AI lack.

“This research demonstrates that human users can use AI to make sense of the business environment in new ways,” said David Kiron, a report coauthor and editorial director, research, at MIT Sloan Management Review. Both organizations and managers can become better learners with AI. That is arguably at least as important as using AI to create efficiencies.”

“Companies can adopt five practical and actionable strategies to enhance their organizational learning through AI,” said Leonid Zhukov, vice president of data science at BCG and a coauthor of the report. “These strategies include fostering growth in both organizational and AI-driven learning, leveraging AI to drive exploration, accelerating learning with AI, selecting initiatives that support continuous learning, and ensuring responsible and ethical AI usage.”

The State of AI in Business

Since 2017, MIT SMR and BCG have tracked AI implementation in business as part of an ongoing research program. The report details evidence of other trends in AI use in business beyond the relationship between AI use and organizational learning:

  • Interest in AI, Especially GenAI, Is Increasing. Since 2017, AI adoption has been relatively stable, but this year, 70% of organizations report piloting or deploying AI solutions, up from 44% to 57% in previous years. More than 54% of organizations are now piloting or deploying GenAI solutions.
  • GenAI Is Drawing Attention. Ninety-one percent of organizations report that their leadership expects generative AI to be a core element of their business strategy in at least some of their business units in the next three years. While 26% of organizations surveyed feel GenAI is diverting funds from traditional AI initiatives, 51% report that it is expanding their overall AI budget. Only 11% find it distracting, and just 13% believe their organization is overly focused on it.
  • Hopes for AI Are Outpacing Fears. In 2024, 84% of respondents are hopeful that AI can assist with some of their tasks, up from 70% in 2017, while only 20% are fearful that AI will assume some of their tasks, down from 31%.
  • Emergence of GenAI Upsets Strategic Plans for AI Use. Since 2020, MIT SMR and BCG have tracked AI’s importance in business strategy. In 2020, 41% of respondents viewed AI as core to their strategy, rising to 61% by 2023. However, in 2024, only 38% consider AI to be core, likely due to the impact of GenAI as executives reassess its role in their strategies.

Download the publication here.

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