“Skills Are a Symptom”: Amy Wilson on Rebuilding the Way We Work

We’ve talked about skills. We’ve talked about jobs. But what if the very foundation we’ve built the workforce on—needs to be reimagined?

In this episode of Skills Connect, Reejig CEO Siobhan Savage sits down with Amy Wilson—former Product Strategy leader at SAP SuccessFactors and Workday, now Product Strategy Advisor at Reejig—to explore the messy, urgent, and exciting business of reinventing how work works.

With decades shaping the biggest platforms in HR tech, Amy brings a rare vantage point: she’s seen where enterprise gets stuck, why tech often misses the mark, and how we can redesign from the inside out. What follows is a brutally honest, insight-rich conversation about the real roadblocks to workforce transformation—and what to do next.

1. Skills Are the Symptom. The Real Challenge Is Work.

Skills aren’t predictive. They reflect the past—not the future.

“The fact that we won’t have the skills we need in the future? That’s just a symptom. The root problem is understanding the work.”

Job postings and resumes tell us what was trending years ago. To make better decisions, we need a real-time view of what work is being done—and what’s changing.

Takeaway: Map the work, not just the worker.

2. Job Architecture Doesn’t Match Reality

Org charts and job descriptions no longer reflect how work gets done. Internal gigs, AI agents, and agile teams exist outside formal structures—and the old frameworks can’t keep up.

“Our rigid structures don’t work in the midst of change… The org chart no longer reflects what’s actually happening.”

The problem isn’t just inefficiency. It’s invisibility. Work is happening—but leaders can’t see it, shape it, or scale it.

Takeaway: It’s time to move from job architecture to work architecture.

3. AI Replaces Tasks, Not Roles

Most models predict job disruption based on skills. But AI doesn’t automate skills—it automates tasks.

“AI doesn’t automate skills. It automates the task. And that changes everything.”

Looking at work only through a skills lens misses the real impact of automation. If you want to design for the future, start with the atomic unit of work: tasks.

Takeaway: Stop planning around roles. Start planning around tasks.

4. Structure Is the Bottleneck

Data alone won’t drive change. Most systems weren’t designed to support dynamic, fast-moving work—and that limits how far transformation can go.

“We’re pumping good ideas into rigid structures. That’s not transformation. That’s translation.”

Even when orgs reimagine work, they’re still constrained by the tools, workflows, and platforms built for another era.

Takeaway: Modern work needs modern infrastructure.

5. This Isn’t a Phase. It’s the New Operating Model.

The shift to AI-native work isn’t a trend. It’s the beginning of a permanently different way of running businesses.

“It’s not about a one-time AI project. This is an ongoing change. And your structure needs to flex with it.”

The future of work isn’t something to prepare for later—it’s already happening. Every task reallocated. Every workflow redesigned. This is it.

Takeaway: Progress depends on elasticity, not certainty.

Final Thought: Stop Describing Work. Start Orchestrating It.

Skills are only one piece of the puzzle. To lead in an AI-native world, we need to stop labeling jobs—and start understanding work as a living system.

“You don’t need to be perfect. But you do need to be moving.”

Design for stretch, not stress. Rebuild the systems. And reimagine what’s possible when we stop waiting for the future—and start building it.

Love bold conversations like these? Tune in live to Skills Connect every Wednesday at 11am EST.