From my Live Broadcast with Josh Bersin last week—what to do, not just what to know.

“This isn’t like buying Workday and hoping everyone becomes more productive. This is full business reinvention.”
— Josh Bersin

Let’s stop treating AI like a tech initiative and start treating it like what it actually is:
A total restructuring of how work gets done.

Here are 7 tactical shifts to redesign your workforce model—built from my live session with Josh Bersin.

1. You Need a Critical Infrastructure for Work - Not a Static Org Chart

not just a static job arch; or org struct; something that is dynamic and reflects the work being done

The problem:

Org charts tell you who reports to whom. They tell you nothing about how work actually flows, what’s broken, or where value gets stuck.

Josh shared an example of a company that had 100,000 employees—and 65,000 job titles. After we mapped the work? Just 3,000 unique jobs. The rest was redundant noise, legacy titles, and work no longer done.

You’re managing people by outdated roles, but people don’t do roles—they do work. And that work evolves daily. You need a live operating system that maps tasks, skills, and outputs in real time.

What to do:

• Don’t start from scratch—start with the real data. Automatically receive a live feed of tasks and skills from Reejig.
• Use that data to update your outdated job architecture into what we call a Work Architecture: a dynamic system that reflects how work actually happens.
• This isn’t about removing structure—it’s about redesigning it to manage risk, regulatory requirements, and real-time change.
• Focus on what’s getting done—track how work moves across teams, roles, and platforms, regardless of titles.
• Choose one high-impact function (e.g. customer support, marketing, or claims) to get started.

This is your Work Operating System—a real-time map of how your organization runs, and where you can unlock velocity, automation, and reinvention.

2. Use Tasks as Your Source of Truth

The problem:

You’re trying to automate work based on roles and skills—but AI doesn’t work that way.

AI automates tasks. It needs granularity. “Skills” taxonomies don’t tell you what the person is doing or how often. Roles are too vague. And job descriptions are often pure fiction.

“People have skills. Jobs and work have tasks.” — Siobhan Savage

What to do:

• For each job, list 10–20 repeatable tasks
• Tag each with:
  • Effort level
  • Business impact
  • Cost per task
• This gives you the basis to:
  • Identify automation opportunities
  • Spot task duplication across roles
  • Score AI readiness

Task-level visibility = transformation visibility. 

Don’t worry—you won’t need to do this manually. Reejig automatically gathers this data for you. Your only job is simply to validate what’s already there.

3. Define What AI-Ready Work Actually Looks Like

The problem:

Most “AI pilots” start with vendor demos—not with real use cases grounded in work.

Josh shared the story of a bank that discovered its biggest bottleneck wasn’t in tech or headcount—it was in account opening, a process nobody had flagged.

What to do:

• Start with one problem domain (e.g. “onboarding,” “approvals,” “reporting”)
• Break it into tasks
• Use this filter:
  • Does this cost us money or cause Pain
  • Is this task a very repetitive task 
  • Is AI Mature enough to take this task 
  • What is the ROI for the business when I reinvent this task
    
    

Now you’re not asking, “Can we use AI?”
You’re asking, “Where does AI deliver value today—and what work do we need to redesign to make that happen?”

4. Advance Beyond Tools by Reengineering Design

The problem:

Most orgs are stuck at “AI as Copilot” (Level 1)—and think they’re innovating.

Josh’s AI Maturity Model is clear:

1. Personal Productivity
2. Task Automation
3. Workflow Reengineering
4. Autonomous Agents

The real value—100% to 300% gains—live in Level 4. But you can’t leap there with fragmented processes and siloed tech.

What to do:

• Reejig automatically maps your workflows end-to-end (e.g. sourcing → hiring → onboarding).
• It identifies all handoffs, delays, and duplicated tasks for you.
• Then, instead of asking you to figure out what to fix, Reejig tells you exactly where to eliminate friction—not just speed up parts of the process.

AI maturity isn’t a tech investment. It’s a design discipline.

5. Appoint Someone to Own the Work

The problem:

CHROs own people. CIOs own tools. COOs own throughput.
But no one owns the work itself.

Without a single point of accountability, your AI efforts will stay siloed and tactical.

What to do:

• Appoint a Work Design Lead (title optional—for now)
• Their job:
  • Own task-level design and governance
  • Bridge HR, Ops, and Tech
  • Run the AI-readiness map across the org
• Plug them into your transformation office or report them to your CEO

This is the start of the Chief Work Officer role. The orgs who invent it first will lead the field.

6. Rethink Career Progression: From Fixed Paths to Fluid Pivots

The problem:

Traditional career ladders no longer reflect how work evolves.

Every time AI reshapes or removes a task, the role itself transforms.

Instead of mapping fixed career paths, we now need to look at reskilling or pivoting based on the changes to the role we have just redesigned.

I used the “Jenga metaphor” in our call—remove one task, and the entire structure changes.

What to do:

• Stop mapping roles. Start mapping task adjacencies.
• Example:

Example:

A marketing coordinator might start out doing campaign tracking.

But with AI, that task is quickly automated.

So what’s next?

Instead of climbing a traditional ladder, we pivot—toward adjacent skills like campaign design or customer analytics.

Every redundancy becomes an opportunity to reskill, redeploy, or redesign work in real time.

Just-in-time enablement isn’t just efficient—it’s how we unlock workforce adaptability.

7. Reinvention > Efficiency

The problem:

Too many leaders still treat AI as a way to do the same work faster.

But true transformation happens when you redesign the work itself—and rebuild the system to continuously evolve.

As I said in the broadcast:

“If I were a CEO and you couldn’t help me do this, I’d find someone who could.”

What to do:

• For any AI use case, also ask:
  • What tasks are being removed?
  • What new tasks will emerge?
  • What will this mean for team capacity, structure, and skills?
• Build a reskilling plan that aligns with that evolution—not just generic upskilling
• Reward teams for removing work, not just performing it
  
  

AI doesn’t just change productivity. It changes purpose.

Final Word

Jobs still exist—but they’re no longer enough. We need a new infrastructure built for the AI-powered workforce.

If you can’t see it, map it, and orchestrate it

1. You can’t lead it
2. AI will amplify your problems, not solve them.

But if you can?
You’ll reinvent how your business runs—on a foundation designed for now, not by dinosaurs.

📥 Check out the full webinar recap here.
📅 Join my next session with Josh Bersin + WPP’s Global Head of People Strategy on May 29.

If you’re serious about a total redesign, message me. The team and I will arm you with whatever you need to reinvent work.

Siobhan 💜