Leadership Gaps Leave 40% of AI Productivity Unexploited: EY

Organizations are capturing only a fraction of AI's productivity potential because technology investments are not being matched by talent development, culture and leadership. EY's 2025 Work Reimagined Survey finds that while 93% of workers in Latin America already use AI and save about nine hours per week, but only 5% use it at an advanced level, leaving up to 40% of AI's productivity gains unrealized.

AI has become a standard workplace tool across Latin America, but widespread adoption is not translating into proportional business value. According to EY's 2025 Work Reimagined Survey, companies are leaving as much as 40% of AI's productivity potential unrealized because investments in technology are not accompanied by the organizational changes required to support them.

The findings suggest that the challenge facing business leaders is no longer whether employees are willing to use AI. Instead, organizations must determine how to integrate the technology into daily operations through leadership, workforce development, and cultural transformation.

"The leadership team must recognize that technology alone does not correct organizational gaps. The value of innovation materializes only when talent, culture and leadership are aligned with strategy,” says Carolina González, People Consulting Leader, EY Latin America. “The true competitive advantage will not come from adopting AI, but from intentionally integrating it into the way organizations work".

AI Adoption is Widespread, but Advanced Use Remains Limited

EY's research shows that AI has already become part of everyday work across the region. About 93% of employees in Latin America report using AI in their jobs, above the global average of 88%, generating average time savings of approximately nine hours per week.

However, most workers rely on AI for relatively simple tasks such as information searches, email drafting, and document summarization. More advanced applications, including deep research, decision evaluation and AI-assisted mentoring, remain significantly less common. Only 5% of AI users qualify as advanced users capable of combining multiple AI tools, assistants and agents to unlock productivity gains of up to 14 hours per week.

This gap illustrates that AI adoption alone does not guarantee measurable business outcomes. According to the study, organizations need to move beyond deploying AI tools and focus on embedding them into business processes through structured learning, role-specific enablement, and management support.

The survey identifies six factors that most strongly influence AI-enabled productivity, including the availability of appropriate tools, employee skills, organizational mindset, and managers' confidence in using AI effectively. These elements collectively determine whether employees convert AI access into measurable operational improvements.

Skills, Culture and Leadership Determine AI Returns

The report argues that organizations frequently undermine AI investments when they deploy new technologies without strengthening workforce capabilities or adapting workplace culture. Weak learning programs, misaligned incentives, and insufficient leadership support reduce the likelihood that AI will generate sustainable productivity improvements.

Training emerges as one of the strongest drivers of adoption. Employees who complete more AI learning hours are substantially more likely to integrate AI into their daily work, and increased usage correlates directly with higher productivity. At the same time, EY highlights a "learning paradox": employees receiving more than 80 hours of AI training are also more likely to leave their organizations, underscoring the importance of pairing workforce development with effective talent retention strategies.

The study also identifies several organizational capabilities that companies should strengthen to convert AI adoption into long-term value. These include continuous learning and AI skills development, organizational cultures that encourage experimentation, reward systems aligned with technology adoption, strategic talent management, and leadership supported by consistent communication.

Beyond productivity, AI adoption is creating new governance challenges. More employees are bringing personal AI tools into the workplace, creating opportunities for innovation while increasing concerns around security, governance and data protection. Both employers and employees identify AI oversight, cybersecurity, workforce displacement, and the erosion of human expertise among their leading concerns.

Regional differences also remain evident. Brazil records the highest AI readiness score in Latin America, while Mexico, Colombia and Japan score below the global average. Asia-Pacific markets continue to outperform the Americas by as much as 19 points, highlighting the competitive pressure facing organizations across the region.

For boards and executive teams, the report positions AI less as a technology initiative than as an organizational transformation effort. Governance priorities increasingly extend beyond AI deployment to include workforce planning, leadership development, cultural monitoring, and continuous succession planning.

EY concludes that sustainable competitive advantage will depend less on access to AI than on an organization's ability to align technology investments with people strategies.