Enterprise AI adoption is accelerating at a rate that far exceeds the ability of organizations to prepare their workforces for the changes ahead. According to new research from Kyndryl, only 23% of business and technology leaders believe their organizations are ready to support AI at scale. The findings, drawn from the 2026 People Readiness Report, underscore a growing gap between AI investment and the human capital needed to realize its full potential.

The report, based on a survey of 1,100 leaders across eight countries, reveals that 57% of organizations have already broadly deployed AI or embedded it into core business processes. Moreover, 77% have scaled generative AI across multiple functions. Yet these aggressive adoption rates have not been matched by corresponding investments in workforce development, role redesign, or change management.

Workforce readiness lags behind AI deployment

The research highlights a stark disconnect between technology readiness and workforce readiness. While 35% of respondents said their IT infrastructure is ready for AI, only 25% reported that their organizational culture is prepared. Even fewer — 23% — indicated that governance and compliance functions are ready. These numbers suggest that the human and organizational dimensions of AI adoption present far greater challenges than the technical ones.

Kyndryl’s CIO Kim Basile emphasized that organizations are realizing that their greatest assets — their people — need more attention. She noted that companies investing in upskilling, role redesign, and formal change-management programs are experiencing positive outcomes at a much higher rate than those that focus solely on technology deployment.

The 'pacesetters' pulling ahead

Among the respondents, Kyndryl identified a small subset — just 9% — that it calls “pacesetters.” These are organizations that have made deliberate investments in workforce readiness while simultaneously redesigning jobs and workflows around AI. The results are striking: pacesetters were 1.5 times more likely to report AI-driven revenue growth and 1.6 times more likely to achieve innovation-related outcomes compared to their peers.

This group represents a model for how enterprises can bridge the readiness gap. They treat AI not merely as a technology implementation but as a transformation of how work gets done. Their approach includes rethinking job descriptions, investing in continuous learning, and embedding change management into every phase of AI deployment.

AI outcomes remain elusive for many

Despite widespread adoption, achieving desired business outcomes from AI remains a challenge. Only 32% of organizations reported achieving even one of their top two desired AI outcomes, and just 11% said they had achieved both. Operational efficiency and productivity was the most commonly reported outcome, cited by 38% of respondents. However, far fewer organizations reported AI-driven revenue growth (14%), IT modernization (13%), or innovation in new products and services (11%).

The survey found that improving operational efficiency and productivity remains the top AI priority for 34% of respondents, followed by IT modernization (27%), risk management and security improvements (25%), business innovation (25%), and AI-driven revenue growth (24%). The gap between ambition and achievement underscores the critical role that workforce readiness plays in converting AI investment into tangible business value.

Skills and talent gap a major obstacle

Nearly half of all respondents (49%) identified skills and talent gaps as a major obstacle to executing their AI strategies, second only to cybersecurity concerns (52%). Additionally, 52% said it has become more difficult over the past year to find employees with the skills needed to support their organization’s AI strategy. This talent scarcity is forcing companies to rethink their approach to workforce development.

Kyndryl’s report indicates that 94% of respondents believe AI will make upskilling current employees more effective than hiring external talent. This sentiment reflects a growing recognition that the pace of technological change makes traditional hiring approaches insufficient. Organizations must instead invest in reskilling their existing workforce to work alongside AI systems.

Change management and role redesign

Nearly 80% of respondents said the pace of AI adoption is likely to outstrip their organization’s ability to adapt its workforce, governance structures, and operating model. Kyndryl notes that most leaders believe addressing these challenges will prove more arduous than those involving code and compute. Role redesign is emerging as a key lever for success. Companies that systematically reimagine jobs around AI, rather than simply adding AI tools to existing workflows, are seeing better outcomes.

Mark Paulek, Kyndryl’s chief human resources officer, observed that AI’s ability to reshape work is challenging organizations to reshape their workforce more rapidly than ever before. The leaders pulling ahead are those that align skills, roles, and decision-making with how work is actually changing.

Infrastructure readiness and governance

Beyond workforce issues, the report also examines organizational readiness across other dimensions. Only 35% of leaders rate their IT infrastructure as ready for AI, and only 23% say governance and compliance functions are prepared. These numbers highlight the need for holistic AI strategies that address not only people but also technology, processes, and policies.

Looking ahead, 36% of respondents expect workforce skills and role structures to be fully AI-ready by the end of 2026, while 33% anticipate the same for organizational culture and change-management capabilities. These projections suggest that while progress is being made, the transformation will take time and sustained investment.

The broader implications for enterprises are clear: AI success is not just about deploying the latest models or expanding computational capacity. It depends on a deliberate, people-focused approach that includes upskilling, role redesign, and structured change management. Organizations that treat workforce readiness as a core component of their AI strategy are far more likely to achieve the revenue growth, innovation, and efficiency gains they seek.

Source:Network World News