Global EVP, Kyndryl: To embrace AI, your workforce needs 'organizational readiness'

On the journey to a productive workplace relationship between AI and employees, it can often feel like there are far more questions than answers.

What operating models must be re-evaluated? Should training and development programs focus on technical or human skills? How can leadership build trust when there is so much fear?

One leader with a blueprint for successful adaptation and adoption is Victoria Pelletier, Global EVP of Enterprise Transformation at Kyndryl, and a People, Process, Value & Change Practice Leader.

She speaks to HR Grapevine about the concept of organizational readiness for AI, shifting employees from fear to partnership, including the vital roles of holistic reskilling, change management, and leadership role modelling.

What does organizational readiness for AI look like at the business level?

AI readiness at the organizational level is a fundamental shift in how the business works, rather than just a checklist of tools and governance. Yes, governance, risk, and ethics frameworks must be in place, and yes, organizations must close critical skills gaps. But without rethinking operating models and ways of working, AI remains an unrealized promise.

The real measure of readiness is whether employees adopt AI into the flow of daily work, with trust and fluency. Until AI is embedded in processes, decision-making, and culture, organizations won’t capture the value. In other words, readiness is less about “installing AI” and more about designing a system where people, skills, and technology evolve together.

How about at the employee level?

At the employee level, readiness is about more than just technical fluency. It’s about feeling seen, supported, and trusted. Whole Human Leadership plays a pivotal role in this regard.

Employees need transparency in communications, so they understand not only what AI means for the business, but also what it means for their careers. They need a clear commitment to career development, with reskilling and upskilling programs that demonstrate the organization’s investment in them, not in replacing them.

Most importantly, they need leaders who balance accountability with empathy – leaders who coach resilience, model curiosity, and create safe spaces for employees to experiment with AI. When employees feel their growth and humanity are prioritized, adoption becomes less about compliance and more about empowerment.

How can organizations embed change management across the business to drive employee adoption?

Too often, organizational change management (OCM) is treated like a sidecar on the vehicle of transformation. A nice to have, but not essential. It should be the engine.

Without a deliberate, enterprise-wide approach to change, the value of AI will remain largely theoretical. Embedding change management involves establishing the structures, rituals, and communication channels that enable employees to shift their mindset, from fear of replacement to confidence in augmentation, seeing AI as a trusted co-pilot in their work.