Select managers are now using artificial intelligence to enhance organizational learning. These astute managers use AI not only to enhance organizations’ ability to learn but also to transform how their organizations operate, making them better—better at integrating AI, better at navigating future technological advancements, and better at managing uncertainty.
AI gives organizations insight into the market and enables them, with more confidence, to swiftly convert it into action, which simultaneously makes the ability to learn quickly more critical to sustaining a competitive edge. To maintain this edge amidst the accelerating tech advances in each new generation of AI models, organizations must also cultivate the agility to integrate these technologies into their operations. In an era marked by technological disruption, regulatory flux, and talent scarcity, those who master learning with AI will have a competitive edge.
Organizational learning is an organization’s capability to change its knowledge through experience. New AI tools, both predictive AI and generative AI (GenAI), can improve organizations by changing the way companies understand, plan for, and react to the ever-increasing speed of change in the market. AI (both generative and predictive) combined with robust organizational learning processes makes organizations better able to benefit from new technologies and more resilient to shocks. In this way, AI-powered organizational learning enhances management’s ability to contend with uncertainty.
What does combining AI and organizational learning look like in the real world? Global cosmetics brand the Estée Lauder Companies (ELC), for example, began deploying predictive AI-powered social media “listening” to better understand and anticipate emerging consumer trends. Previously, trends shifted seasonally, but the social media era shortened the trend life cycle, creating uncertainty for the company. Using AI to identify consumers’ emerging preferences, ELC matches those trends with products already in the company’s supply chain, which it then repackages and redeploys to match real-time consumer demand.
ELC clearly accelerated its market intelligence, but when it synthesized that information as part of its organizational learning process, the company identified emerging compliance uncertainty in its flexible approach; it sees potential for GenAI to support the automation of regulatory requirement checks. For organizations like ELC, integrating AI into their learning systems increases their ability to deploy new technology, setting off a virtuous cycle that further accelerates their organizational learning.
To better understand how companies are coupling traditional organizational learning with cutting-edge AI solutions to manage uncertainty, BCG and MIT Sloan Management Review teamed up to conduct a global survey of more than 3,400 managers in over 120 countries. The results revealed that the vast majority of organizations are not yet using AI as part of their organizational learning practices—but the few who do see significant, tangible benefits.
Organizations that score highly on organizational and AI-specific learning are what we call Augmented Learners. Augmented Learners are 60%-80% more likely to be effective at managing uncertainties in their external environments than Limited Learners. Compared to them, Augmented Learners incorporating AI are also 40% more likely to have created business value over the last three years and benefited from annualized revenue increases.
Despite those potential benefits, only 15% of companies qualify as Augmented Learners, with nearly two-thirds of companies (59%) falling into the Limited Learner category. Here’s what those organizations can learn about how the top performers successfully incorporated AI into their learning systems.
Coupling organizational learning with AI
Managers can effectively integrate AI across three stages of organizational learning: 1) Knowledge capture, building a living repository of knowledge across the organization; 2) knowledge synthesis, refining vast data into digestible information, particularly helping to filter through the noise to identify the crucial signals; and 3) knowledge dissemination, delivering personalised insights to decision makers to guide actions.
Capture critical knowledge: Organizations can now capture new forms of knowledge with AI, including hard-to-express types of knowledge, such as individual expertise within an organization. For companies that use the team communication platform Slack, for instance, AI can synthesize fragments of information entered by employees in disparate Slack channels, encode it, and make those insights accessible to current teams, ensuring the creation and continuity of institutional knowledge. That way, Jackie Rocca, the former vice president of product at Slack told us, “people can actually get context from people who might have left the company months or years ago and still learn from their knowledge.”
Refine the data: Augmented Learners harness AI to make sense of what’s often an overwhelming flow of information. Slack is creating a feature that provides a daily recap of what’s transpired in a given channel, allowing managers to get up to speed without sifting through every message. That means a sales manager juggling multiple conversations with their team and prospective clients could receive a summary of the most essential information upfront, enabling faster, more informed decision-making.
Deliver personalised insights: One key advantage of AI is its ability to personalize content. Augmented Learners embrace this such that organizational learning experiences and insights are tailored to each employee’s learning style, language preference, role-specific needs, and even in recognition of their diverse backgrounds. Slack’s AI-generated recaps, for instance, can be fine-tuned to an individual’s specific preferences.
Becoming an augmented learner
Our research shows that Augmented Learners are not limited to a particular size of company—the proportion of companies that are Augmented Learners remains about the same irrespective of company revenue. This suggests that the ability to integrate AI into organizational learning is not limited by a company’s financial resources but rather by its strategic commitment.
To prepare for this evolution, here are three steps companies can take:
Start early to tap into the virtuous cycle: While each company’s starting point will differ based on their existing organizational learning and AI-enabled learning capabilities, they should start integrating AI into their learning processes now to tap into the virtuous cycle that could lead to competitive advantage. “As the technology matures, these continuous feedback loops will compound, creating a common collective intelligence across the organization," the head of AI at the Danish pharmaceutical company Novo Nordisk told us. "This will enable the utilization of knowledge in ways that were completely impossible before.”
Incorporate learning ROI in project selection: Our research shows that companies that take on high-risk, longer-term AI projects become better learners in the process. Companies can factor in this learning potential in calculating return on investment when selecting a project. Prem Natarajan, Capital One’s chief scientist and head of enterprise AI, says that he considers the ROI to include traditional financial returns, as well as use cases that “allow you to test and learn, because without test-and-learn you cannot slope up into the other, more complex use cases.”
Keep pace with latest innovations: Becoming an Augmented Learner requires ongoing refinement to adapt to new AI advancements, ensuring the organization remains competitive. Expedia, for example, manages 1.2 quadrillion possible travel booking combinations that can be upended by mass cancellations due to weather events, like hurricanes and snowstorms. “Weather forecasting improves every year with the power of AI, so we constantly have to keep refining our approach,” said Rajesh Naidu, chief architect of data platform and data management at Expedia. With improved AI forecasting, Expedia learned to proactively anticipate weather events and can now identify their likely impact, track customers currently traveling or planning trips, and effectively communicate with them in advance to minimize the disruption.
Given the speed at which AI technologies are evolving, momentum from continuously adopting and adapting to new technologies is critical to gaining a competitive edge. Companies incorporating AI into their organizational learning not only get better information to make decisions, which, in turn, improves the existing AI’s ability to impact learning, organizations’ use of AI also increases their ability to adopt what’s coming next and extract maximum value from the latest technology. It is this momentum that creates an acceleration in organizational learning that will likely be hard for late-comers to catch up with.
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Read other Fortune columns by François Candelon.
François Candelon is a partner at private equity firm Seven2 and the former global director of the BCG Henderson Institute.
Michael Chu is a vice president of AI & data science at BCG.X.
Shervin Khodabandeh is a managing director and senior partner at BCG.
David Kiron is the editorial director, research, of MIT Sloan Management Review and program lead for its Big Ideas research initiatives.
Namrata Rajagopal is a project leader at Boston Consulting Group and a former ambassador at the BCG Henderson Institute.
Sam Ransbotham is professor of analytics at Boston College’s Carroll School of Management.
Leonid Zhukov is the director of the BCG Global A.I. Institute and vice president of AI & Data Science at BCG.X.
Some of the companies mentioned in this column are past or present clients of the authors’ employers.
