As businesses accelerate artificial intelligence (AI) adoption, preparing employees to work alongside the technology remains a major challenge. Only 23% of business leaders believe their workforce is completely ready to leverage AI, down six percentage points from 2025, according to Kyndryl's 2026 People Readiness Report.
The report, which surveyed 1,100 business and technology leaders across eight markets, including India, found that 79% of leaders fear AI will outpace their workforce capabilities, governance and operating models.
The findings highlight a growing gap between organisations' AI ambitions and their ability to prepare employees for changing job requirements.
Skills gaps emerge as a major barrier to AI adoption
Finding employees with the right skills is becoming increasingly difficult for businesses implementing AI strategies.
The report found that 49% of leaders identified skills and talent gaps as a major challenge to AI execution. Cybersecurity concerns ranked higher at 52%, while data quality and availability followed at 47%.
More than half (52%) of respondents also said finding employees with the right skills for their organisation's AI strategy had become more difficult over the past 12 months.
Despite these challenges, employers appear to favour developing existing talent over external recruitment. The report found that 94% of leaders prefer upskilling current employees rather than hiring external talent to meet AI-related skills requirements.
However, only 31% of organisations have implemented a formal budget and proactive upskilling strategy. Just 34% have an accurate inventory of employee skills.
AI is altering job roles and workforce structures
The growing use of AI is also changing how organisations define employee responsibilities.
According to the report, 95% of leaders agree that job roles are evolving to require collaboration with AI rather than the replacement of human labour.
Meanwhile, 22% of organisations are redesigning existing roles to embed AI as a collaborative partner, while 24% are creating new positions focused on managing AI outputs and workflows.
The shift is also reaching entry-level positions. More than half (52%) of respondents said their organisations are redesigning entry-level roles around learning, judgement and AI collaboration. Another 26% reported the emergence of entirely new entry-level pathways and role structures.
However, support for employees whose roles are affected by AI remains limited. Only 25% of organisations have established formal career transition pathways for impacted employees.
Bigger AI implementation challenges than executives
The report also points to a gap between senior leadership and employees responsible for implementing AI strategies.
Non-C-suite respondents were more likely to identify skills shortages as a challenge than their senior counterparts. While 55% of non-C-suite respondents cited skills or talent gaps, the figure stood at 43% among C-suite leaders.
Similarly, 48% of non-C-suite respondents identified redesigning roles and workflows around human-AI collaboration as a challenge, compared with 42% of C-suite leaders.
Employee enthusiasm towards AI is also weakening. The share of leaders who believe employees are enthusiastically embracing AI fell from 37% in 2025 to 32% in 2026.
The gap is particularly visible across organisational levels. Leaders believe 50% of executive leadership teams are enthusiastic about AI, compared with 36% of middle managers, 31% of individual contributors and specialists, and 30% of entry-level employees.
The findings suggest that successful AI adoption will require more than technology investments.
Employers will need to strengthen workforce planning, invest in continuous learning and redesign roles to help employees adapt to an increasingly AI-driven workplace.
For HR leaders, the priority is to translate AI adoption into workforce transformation by strengthening employee capabilities, anticipating future talent needs, creating reskilling opportunities and rethinking roles to support effective human-AI collaboration.