remote AI workforce development Is Key to Unlocking AI’s Full Value
Despite widespread AI adoption, organizations are capturing less than 60% of its potential productivity gains. The missing piece? remote AI workforce development. According to EY's 2025 Work Reimagined Survey, while 93% of workers in Latin America use AI—above the global average of 88%—only 5% operate at an advanced level. This gap leaves up to 40% of AI’s productivity value unrealized, not due to technology limits, but to shortcomings in talent, culture, and leadership.
AI Is Everywhere, But Not Deeply Understood
AI has become a standard workplace tool across Latin America. Employees save an average of nine hours per week using AI for tasks like email drafting, document summarization, and information searches. However, advanced applications—such as deep research, decision modeling, and AI-assisted mentoring—remain rare. Only a small cohort of users, just 5%, combine multiple AI tools and agents to unlock productivity gains of up to 14 hours per week.
This disparity reveals a critical insight: adoption does not equal impact. The technology is available. The workforce is using it. But without structured remote AI workforce development, most employees remain in the shallow end of AI capability.
Leadership and Culture Are the Real Bottlenecks
Organizations are investing in AI tools but not in the organizational changes needed to scale their use. As Carolina González, People Consulting Leader at EY Latin America, states:
"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."
AI productivity leadership gaps are now a top constraint. Managers’ confidence in using AI, organizational mindset, and role-specific enablement are among the six key factors influencing whether AI use translates into measurable outcomes. In the United States, similar patterns are emerging: high adoption rates but limited advanced use, especially in remote tech teams where oversight and training are decentralized.
The Learning Paradox: Training Increases Retention Risk
Training is one of the strongest drivers of AI adoption. Employees with more AI learning hours are more likely to integrate AI into daily workflows. Yet, a troubling trend emerges: those receiving over 80 hours of AI training are more likely to leave their organizations. This "learning paradox" highlights a flaw in many tech talent retention strategies.
Organizations that invest in upskilling without reinforcing retention risk losing their most capable workers. The solution lies in pairing remote AI workforce development with career pathing, recognition, and leadership opportunities—especially for distributed teams.
Remote AI workforce development in Latin America illustrates this paradox sharply: while 93% of workers use AI—surpassing the global average—most apply it for basic tasks like email drafting and document summarization. Only 5% are advanced users, despite average time savings of nine hours per week, with top performers gaining up to 14. This gap between broad adoption and deep skill development underscores how training without structured career growth can accelerate turnover, especially in distributed teams where recognition and advancement opportunities are less visible. Without aligning learning with clear pathways, companies risk cultivating talent only to see it leave for more rewarding environments.
Regional Gaps Reflect Global Inequities
AI readiness varies across regions. Brazil leads Latin America in AI preparedness, while Mexico, Colombia, and Japan fall below the global average. Meanwhile, Asia-Pacific outperforms the Americas by as much as 19 points in AI readiness, signaling growing competitive pressure.
For global tech firms, this means remote teams in lower-readiness regions may lag in AI integration unless targeted development programs are implemented. This is not just a Latin American issue—it reflects broader challenges in scaling AI across diverse, distributed workforces.
AI Governance Must Evolve Beyond Technology
As employees bring personal AI tools into the workplace, governance challenges grow. Cybersecurity, data protection, and the erosion of human expertise are top concerns for both employers and employees. AI governance can no longer focus solely on deployment. It must now include workforce planning, leadership development, and cultural monitoring.
Executive teams must treat AI not as an IT project, but as an organizational transformation. As González notes:
"The true competitive advantage will not come from adopting AI, but from intentionally integrating it into the way organizations work"
The gap between technology adoption and organizational readiness is stark, especially in regions like Latin America where remote AI workforce development has surged ahead of supporting infrastructure. With 93% of workers using AI—above the global average—yet only 5% classified as advanced users, the bulk of potential gains remain untapped. Most employees apply AI to basic tasks such as email drafting and document summarization, missing deeper productivity opportunities. While AI saves Latin American workers about nine hours per week on average, advanced users nearly double those savings, gaining up to 14 hours weekly—highlighting how leadership and cultural gaps limit broader impact. Without parallel investment in skills, culture, and management practices, remote AI workforce development risks becoming a story of missed opportunity rather than transformation.
How to Close the AI Productivity Gap
To realize the full 40% of untapped productivity, organizations must:
- Invest in continuous, role-specific AI learning programs
- Align incentives with AI adoption and innovation
- Develop leaders who model and support AI use
- Embed AI into daily workflows, not just pilot projects
- Monitor cultural readiness and psychological safety for experimentation
The future of remote tech careers depends on this shift. Workers who master AI integration will outperform peers, but only if their organizations support sustained growth.