Fifty-seven percent of enterprises now have AI embedded in core business processes, up from 35% a year ago, but only 23% of business leaders believe their workforce is fully prepared for AI, a six-point drop from 2025. The Kyndryl 2026 People Readiness Report, based on a survey of 1,100 senior leaders across eight countries, reveals a widening gap between AI deployment and the organizational readiness needed to make it pay off.
Workforce readiness is declining
Only 32% of organizations with broad AI deployment have achieved at least one of their primary AI objectives, and just 11% have hit both. Rapid AI rollout does not automatically produce business results. The skills pipeline is tightening: 52% of respondents said finding employees with the right AI competencies has become more difficult over the past year. Only one-third have fully implemented training programs designed to prepare staff to work alongside AI tools.
Kyndryl CIO Kim Basile said in the report that organizations seeing the strongest outcomes are "investing in their people alongside their technology, rethinking roles, funding upskilling, and actively managing employee transitions through change." For HR teams, building these training programs is a pressing challenge, and resources like AI for Human Resources offer a starting point.
What the 9% Pacesetters do differently
Kyndryl identifies a group it calls Pacesetters, roughly 9% of respondents, who redesign roles around AI capabilities, build structured change management programs, and establish governance guardrails before scaling. These organizations are approximately twice as likely to have fully implemented AI governance and 1.5 times more likely to report AI-driven revenue growth. Their approach shows that technology investment alone is not enough; role redesign and employee transition management are critical. Chief human resources officers can align their strategy with this model through the AI Learning Path for CHROs.
Governance gaps and the trust problem with AI agents
Eighty-one percent of organizations expect AI agents to make impactful business decisions within the next 12 months. Only 25% fully trust AI systems operating without human oversight. On governance, just 33% have established clear policies defining AI decision-making authority, and 27% use registries and monitoring across all AI systems. Kyndryl CHRO Mark Paulek said organizations pulling ahead are "aligning employee skills, role definitions, and decision-making authority to reflect how work is actually changing, not how it used to operate."
Why this matters for HR professionals
- Audit your AI objectives against deployment scope. If your organization has broad AI deployment but isn't hitting key objectives, the gap is likely a people and governance issue, not a technology one.
- Benchmark your governance posture against the Pacesetter model. Policy coverage for AI decision boundaries, system registries, and monitoring are the specific gaps Kyndryl calls out. Check whether your frameworks address all three.
- Treat AI agent autonomy as an urgent governance question. With 81% of enterprises expecting agentic AI to make significant decisions within the year, defining human-oversight thresholds now is a compliance and operational risk issue.
- Tie upskilling investment to role redesign, not just training headcount. The organizations achieving outcomes are restructuring how work gets done, not just adding courses to an LMS.
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