Even as AI investment rises, many organizations don’t see the returns they expected. They might see small improvements by deploying AI tools into existing structures. But true success means thinking beyond the technology alone, reinventing tomorrow’s workflows, and putting AI to work for people. Our research shows only 5% of organizations are redesigning work, while others are optimizing what already exists.
When my role evolved to blend people leadership with AI enablement, it sent a clear message from our CEO: AI requires a strong people strategy at the core. I’ve seen real transformation when organizations bet on people, not just AI.
The companies unlocking results are asking the right questions about how work should change. What those leaders are learning comes down to a few key steps.
BUILD THE FOUNDATION ON DATA AND GOVERNANCE
When we rebuilt our AI HR operating model at ServiceNow, we considered how we would design it if we were starting from scratch. That helped us move from scattered pilots to a structured process with clear governance, accountability, and a way to scale without chaos.
PepsiCo’s executive vice president and chief people officer, Becky Schmitt, took a similar, structured approach. In a webinar we hosted, Schmitt a client of ours shared how she focused on data hygiene and prioritized all employees, including frontline and factory employees where safety and wellbeing are nonnegotiable.
With clean data and transparent definitions, employees can better trust and verify what AI tells them. When trust grows, adoption accelerates.
“As we’ve thought about what it means to adopt AI and harness the full power of this technology, we have five principles. Everything is human-centered. We’re fair, transparent, we have accountability, and we’re safe from the start,” she said.
When roles are clear and processes are simple, people move faster and smarter. Governance builds confidence.
ENABLE YOUR PEOPLE WITH SKILLS THAT MATTER
By 2031, the fastest-growing technical skills will be linked to data quality, software development, analytics, and AI, according to our research. But demand for distinctly human capabilities is also accelerating.
This dual reality changes how we should think about enablement. Our client, Omar Abbosh, chief executive officer at Pearson, studies these dynamics closely. In another webinar we hosted, he said key skills that matter now are agency, learning velocity, and emotional intelligence.
Add adaptability and design thinking, and people can evolve faster than the environment shifts.
“We need to rewire occupations. We need to understand where you apply agents to specific tasks, how agents work with people, and how people can supervise and orchestrate. That level of rewiring results in a new operating model. It’s process, it’s systems, and it’s the motivation required to change the culture,” he said in the webinar.
But you can’t teach these skills in a classroom. Real-time learning embedded in daily work beats traditional reskilling programs. We give our employees personalized learning recommendations tailored to how AI will be used in their roles, which allows them to understand the why behind its use and the value of human judgment in their work. We have seen that when you coach people through the work they’re doing, learning is faster, stickier, and more scalable.
TRANSFORM THE WORKFORCE WITH CHANGE READINESS
AI adoption is increasing, yet many people aren’t aware of their organization’s AI strategy. This is a disconnect that leaders need to address with continuous, adaptive, and decentralized change readiness.
This is often the hardest part of a transformation because it’s complex and abstract. It’s about changing the way we work at a fundamental level, which requires a strong understanding of your organization’s structure and capabilities. And it requires keeping employees informed about the skills the organization is prioritizing, how roles are evolving, and the path forward.
Another client of ours, Nickle LaMoreaux, senior vice president and chief human resources officer at IBM, used an “X-Ray” framework as a foundation to rethink her organization with an AI-native mindset. As she explained in a different webinar we hosted, “We were really clear from the beginning that we were going to put employees at the center of this.”
By recognizing the importance of redesigning jobs and helping employees feel comfortable with the technology, Nickle built a powerful model to map current skills against future needs.
Her team also identified where redesign was most urgent. Then, IBM shared that analysis with employees.
“You have to redesign jobs. If you wait too long, you can quickly fall behind, especially at the pace things are moving today. When we talk about redesigning jobs, we need to shift our thinking from the job as a whole to the tasks and skills underneath it,” she said.
That kind of analysis can help leaders think about future skills as AI changes work. The end goal is a workforce that can pivot at the speed of innovation. It’s about shifting the mindset to “let’s try this” instead of “don’t break this.”
THE FLYWHEEL
We’ve been through big technology shifts before. AI transformation feels different because of the pace, but those examples should give us confidence.
Each step creates the conditions for the next. They can help us shift from talking about change to showing people what it feels like when their roles evolve to expand their potential.
For leaders, this is the moment to put people at the center, powered by technology and a clear plan. In my experience, that has always been the right combination.
Jacqui Canney is the chief people and AI enablement officer at ServiceNow.
