Over the past year, I have lost count of how many times I have heard the same question:

“Will AI take my job?”

It is an honest fear. AI tools are moving fast. They are drafting grant reports, writing meeting notes, checking compliance, and scanning whole fields of literature in minutes. Tasks that used to fill our days are suddenly shrinking or disappearing altogether.

At first, I felt the same unease. If AI can do so much, where does that leave us?

But here is the real truth: AI isn’t the real threat. Old workflows are. If our roles remain defined only by repetitive tasks, then yes AI will replace them. But if we use AI as a catalyst to redesign workflows, we can actually create better, more meaningful jobs in research management.

Seeing AI as More Than a Task-Doer

Right now, most of us are experiencing AI as a kind of task assistant. Need to polish a report? A Copilot can help. Need a compliance summary? An automated system can generate one.

That feels helpful in the moment. But here is the risk: if our jobs are defined only by those tasks, and AI can do them, then the whole role could eventually disappear.

I think of colleagues whose weeks are filled with chasing approvals or compiling reports. Those are exactly the kinds of workflows AI will fully automate.

This is why focusing only on task-level AI feels shortsighted. Jobs are not just lists of things we do—they are systems of work. And when the system changes, the nature of the job changes too.

Where the Real Shift Begins

This is where I see the real opportunity: when AI doesn’t just speed up old tasks but actually reshapes the workflows themselves.

Picture this:

• Instead of ten administrators managing different pieces of the grant process, one AI-powered system runs the pipeline—while people focus on quality of applications.
• Instead of compliance being checked at the end, AI ensures compliance is built into the workflow from the start—while professionals step into governance and policy roles.
• Instead of endless meeting follow-ups, AI automates the admin—freeing staff to focus on stakeholder engagement and relationship building.

When workflows are redesigned, new jobs emerge. And these jobs look very different from the ones we know today.

The New Roles Emerging

I can see outlines of new kinds of roles:

• Workflow Architects – colleagues who design how AI fits into our offices, creating systems that are efficient, ethical, and aligned with strategy.
• Governance Leads – people who make sure AI adoption is transparent, responsible, and trusted.
• Innovation Catalysts – those who test tools, share lessons, and help teams experiment with confidence.

Notice what ties these roles together: they are not about processing forms or ticking boxes. They are about shaping systems, guiding colleagues, and making sense of change.

Why Workflow Redesign Creates Jobs

What reassures me is this: if we stop at task-level AI, yes—jobs will disappear. But if we lean into workflow redesign, AI becomes a catalyst for creating better jobs.

The research office of the future may not need as many roles defined by repetitive tasks. But it will need more people who can:

• Align systems with institutional strategy.
• Lead others through uncertainty.
• Ensure AI adoption is ethical and fair.
• Connect researchers, funders, and technology partners.

These are the roles where human judgement, empathy, and creativity matter most. And they are roles AI cannot replicate.

A Personal Reflection

The future is not about clinging to the task lists of the past. It is about stepping into the new spaces AI opens up: spaces of strategy, ethics, leadership, and imagination.

So perhaps the question isn’t really “Will AI replace us?” but “Am I ready to step into the new roles it creates?”

Because AI doesn’t just change how work gets done. It gives us permission to reimagine what meaningful work in research management can be.

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