Why adaptive performance is your secret weapon

In the race to integrate AI, organizations are finding that traditional performance metrics tell only part of the story. Basic task completion and collaborative teamwork—the cornerstones of industrial-era success—are not enough. Companies that thrive in the age of AI have mastered what researchers call adaptive performance.

The problem is that at this crucial moment when AI is requiring workers to adapt quickly, workplace performance is falling fast—costing U.S. companies $2.2 trillion in lost productivity over the past 5 years, according to new research from BetterUp Labs. And adaptive performance is declining faster than any other type of performance. Understanding why this matters and how to reverse the trend could determine the success or failure of AI transformation at your organization.

Beyond the assembly line

Why do some employees excel in unpredictable, rapidly-changing environments when others flounder? Adaptive performance emerged as a concept in the 1990s when organizational psychologists sought to answer this question. It turns out there are three types of performance: basic performance focuses on executing known tasks efficiently, collaborative performance emphasizes working well with others, and adaptive performance addresses the ability to thrive as things keep changing.

As markets became more volatile, tech cycles accelerated, and global competition intensified, organizations found that their most valuable employees weren't necessarily the fastest task-completers or the most collaborative team players. The most valuable were those who could pivot quickly, generate creative solutions, and maintain effectiveness amid constant change. 

A high-stakes performance gap

Organizations with high adaptive performance see more than a 33% increase in organizational innovation and show strong correlation with shareholder returns. Boston Consulting Group found that the 50 most adaptive companies outperformed the market by 68%. When manufacturing firms demonstrate high adaptive performance, profitability doubles.

Despite its impact, adaptive performance is declining the fastest of all performance types. Our research, encompassing over 200 million data points from 410,000 employees, reveals that adaptive performance has experienced the steepest decline since 2019, threatening organizations' ability to evolve and compete in fast-changing environments.

This decline manifests in several ways. Organizations report slower responses to market changes, failed transformation initiatives, and employees who default to safe, routine work rather than taking calculated risks. Innovation cycles lengthen, competitive advantages erode more quickly, and teams struggle to reconfigure themselves as business needs shift.

The AI adoption paradox

The irony is that organizations are being asked to execute one of the most disruptive transformations in business history—AI integration—precisely when their workforce's capacity for adaptation is at its lowest.  Success depends on employees who can learn new systems quickly, integrate AI tools creatively into their work, and pivot when initial approaches don't work.

Research from UC Berkeley's Haas School of Business and Harvard Business School confirms this paradox. AI has the potential to dramatically increase adaptive performance in jobs requiring creativity, but only if workers' skills in this area are already high. AI doesn't replace imagination, it amplifies it. 

The pilot advantage

BetterUp’s partnership with Stanford's Social Media Lab revealed two distinct mindsets around AI adoption that directly correlate with adaptive performance levels. We call them Pilots and Passengers.

Pilots represent the minority who are thriving with AI. They embrace AI as a creative partner, navigate change with confidence, and proactively adapt to new technology. Their defining characteristics—optimism and agency—are core components of adaptive performance. Pilots collaborate with AI, experiment with it, and push its boundaries.

Passengers, representing the majority of workers, struggle with AI adoption. They're pessimistic, fearful, and reluctant to engage with AI tools meaningfully. When they do use it, they treat it as a task-completion device, failing to think critically about its outputs or explore innovative applications.

The gap between these groups is about fundamental differences in adaptive performance. Pilots possess the creativity to envision new possibilities, the connectivity to collaborate effectively with both humans and AI systems, and the agility to shift approaches when needed. Passengers lack these adaptive capabilities, making them resistant to the experimentation and iteration that AI adoption requires.

Why adaptive performance is crashing

The decline in adaptive performance stems from a perfect storm of organizational and psychological factors that have been building for years.

Innovation fatigue: Constant organizational changes, strategic pivots, and abandoned initiatives have created a workforce that's exhausted by change. When employees see new strategies launched and discarded repeatedly, they lose faith in their ability to adapt successfully, leading them to avoid risk-taking and retreat to familiar routines.

Psychological fuel depletion: Adaptive performance requires significant psychological energy. We call it fuel. The three components of this fuel (motivation, optimism, and agency) have all declined significantly. Without adequate fuel, people avoid the experimentation and creative problem-solving that adaptive performance demands.

Skills vs. mindset confusion: Many organizations have focused on teaching discrete AI skills rather than developing adaptive mindsets. They train employees on specific tools or processes but fail to cultivate the underlying psychological capabilities that enable adaptation. This creates brittle learning that breaks down when circumstances change.

Structural barriers: Traditional organizational structures, reward systems, and performance metrics often penalize the very behaviors that adaptive performance requires. Risk-taking, experimentation, and failure-based learning are discouraged, while efficiency and predictability are rewarded.

The switching gear 

In an AI-enabled workplace, adaptive performance is the critical switching gear that allows organizations to move fluidly between different operational modes. During periods of stability, teams can focus on basic task execution. When collaboration challenges arise, they can shift to alignment and coordination mode. But when disruption hits—whether from new AI capabilities, market changes, or competition—adaptive performance is required.

This switching capability proves especially crucial because AI adoption is an ongoing evolution. As AI capabilities expand, organizations must continuously reconfigure teams, rethink workflows, and respond to shifting technological landscapes. Teams with high adaptive performance can make these transitions smoothly.

Building the adaptive advantage

The good news is that adaptive performance can be developed, but it requires a different approach than traditional training. Instead of focusing solely on skills transfer, organizations need to cultivate the psychological fuel that powers adaptation.

This means creating environments where employees feel their work matters, where growth opportunities are abundant, and where calculated risk-taking is rewarded rather than punished. It requires leaders to communicate about AI using supportive, encouraging language that builds agency rather than fear.

Most importantly, it demands recognition that adaptive performance isn't just another metric to track—it's the foundation that makes all other performance improvements possible.  Organizations that master adaptive performance will define the AI revolution. 

Download the full report, Winning in the age of AI:Transforming workforce performance, for more about how adaptive performance can help set your workforce up for success in the AI transformation.