I wanted to share a few reflections after an open, at times blunt, but deeply important conversation with Amy Wilson and Josh Gosliner from SAP SuccessFactors.
We called the session Beyond Skills: Reengineering Work because that’s exactly what’s at stake.
For years, I’ve worked in workforce strategy, trying to help organizations see that people have skills but jobs have tasks. And that distinction matters more than ever in this AI era.
Here’s what stood out for me in our conversation.
Not long ago, every boardroom was focused on retention. Employee experience was the metric. Internal mobility was the buzzword. It was all about making people feel valued and building opportunities internally.
But the reality changed—abruptly. Economic pressures flipped the switch. Suddenly, productivity, efficiency, and cost-cutting dominated the conversation.
We talked about this shift on the call. It’s not that organizations don’t care about people anymore. But the priority has changed to survival, velocity, and getting leaner.
That shift means a lot of companies are back at square one. Even those that invested in skills-based strategies are now asking:
Who are our people? What are they actually doing? How can we be more efficient?
The old focus on "skills-based org design" isn't enough on its own.
One thing I keep repeating (and did on the call): People have skills. Jobs have tasks.
AI doesn’t automate skills. It automates tasks.
When I see companies investing millions in static skills taxonomies, it worries me. Because the second you save that file, it’s outdated. Every time you introduce AI, you remove certain tasks—and you introduce new ones.
We need a live, dynamic view of work.
That’s why we built Reejig’s Work Ontology. Not to replace job architecture, but to transform it into work architecture.
We map tasks, tie them back to skills, and keep that data live and connected. So companies don’t just know their people’s resumes—they know what work actually gets done.
Josh made a great point about customers buying tools without having the data to make them work.
I see this everywhere.
Companies are planning massive transformations, but their learning strategies are still guesswork. They’re picking “future capabilities” out of thin air.
I said it bluntly on the call—and I’ll say it here:
We can’t waste people’s time making them learn things that don’t matter.
If you want to reskill people for an AI-powered workforce, you need to know:
That’s the only way to target reskilling in a way that actually works.
We also talked about the fear that this shift will be driven purely by "bean counters" slashing headcount with AI.
That’s real.
We all have a responsibility to make sure workforce transformation doesn’t just mean cutting costs. It has to mean reinventing work and reinventing careers.
When 64% of a role’s tasks are automated, the answer shouldn’t just be layoffs. It should be:
How do we pivot these people into new roles with their adjacent skills?
This is the work.
This is why I'm excited about our partnership with SAP SuccessFactors.
Their Talent Intelligence Hub gives organizations the governance and structure for skills data. Reejig’s Work Intelligence connects that to the reality of tasks and work design.
Together, it’s not just a software integration—it’s a way for organizations to see and manage the full picture:
If you’re a CHRO, CLO, transformation leader, or workforce strategist reading this:
Go make best friends with whoever owns AI strategy in your company.
These conversations cannot be happening in silos. If AI teams are roadmapping automation without talking to HR, you're going to waste money, lose people you could have kept, and fail at transformation.
We have to build this together.
AI workforce transformation isn’t optional. It’s here. The train has left the station.
Our job is to make sure it happens responsibly, without leaving people behind.
If you want to talk about this more—about what it means for your company—my inbox is always open.
Let’s do this the right way.
Siobhan 💜
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