What Happened?
At Charter’s New Employer Brand Summit in New York City on June 9, Canva Chief People Officer Jennie Rogerson shared two attributes she looks for in candidates across roles and departments: curiosity and the ability to contribute beyond one’s core remit.
Her clearest message was that curiosity is no longer optional in the age of AI. As she said during the session:
“Curiosity is a baseline.”
For Rogerson, curiosity means more than being interested in new tools. It includes curiosity about emerging technologies such as AI, but also curiosity about why previous decisions were made. She told CNBC Make It that strong employees should understand “what came before,” respect the thinking behind it, and then “build stronger on top of it.”
This gives recruiters a practical evaluation signal. Instead of simply asking whether a candidate is curious, Rogerson suggested asking:
“What have you learned outside of your core discipline that you then put into practice for impact?”
The second trait Rogerson looks for is contribution beyond the candidate’s direct responsibilities.
She said Canva wants to build a culture of “givers” — people who feel responsible for the culture, not just people who benefit from it. These are candidates who notice a broken process, pitch an idea, start an internal community, help ship better work, or improve team culture without waiting to be asked.
To assess this, she might ask:
“What did you do outside of your core remit that added to either product development or shipping some great things to your users or that you added to team culture?”
The article also connects Rogerson’s view with a broader leadership pattern: in an AI-shaped labor market, durable human skills such as curiosity, initiative, adaptability, and cross-functional contribution are becoming stronger signals of long-term candidate value.
What This Means for Recruiters and Companies
The key hiring question is shifting.
Recruiters are no longer only asking, “Can this person do the job as it exists today?”
They also need to ask, “Can this person keep learning, apply new tools, and expand the value of the role as work changes?”
For recruiting teams, the main takeaway is that curiosity must become observable.
Many candidates can say they are curious, but fewer can prove it. A better interview structure should look for four signals: what triggered the learning, what the candidate did to learn, how they applied it, and what impact it created. This turns curiosity from a vague culture-fit trait into an evidence-based competency.
Recruiters can adapt Rogerson’s question into a practical interview prompt:
“Tell me about something you learned outside your main role in the past year. How did you apply it, and what changed because of it?”
The second insight is that “beyond remit” should be evaluated as an ownership signal, not as a request for overwork.
In an AI-enabled workplace, role boundaries are becoming more fluid. Recruiters can automate candidate communication, marketers can build AI-assisted prototypes, HR teams can analyze workforce data, and operators can improve workflows without waiting for another function. Companies need people who can identify friction, collaborate across teams, and improve the system around them.
This should be reflected in hiring scorecards.
Two useful dimensions are:
- Applied curiosity: the candidate learns beyond their core domain and applies that learning to improve speed, quality, decision-making, collaboration, or user outcomes.
- Ownership beyond scope: the candidate notices gaps and contributes to product, process, team, or culture beyond assigned tasks.
For companies, the lesson is equally important: do not hire for curiosity and ownership unless the organization is ready to support them.
Employees need time to learn, access to AI tools, permission to experiment, clear guardrails, and recognition for cross-functional contribution.
The recruiter’s role therefore becomes more strategic. AI can help screen resumes and summarize interviews, but recruiters still need to define what matters, design better evaluation criteria, and identify the human traits that remain valuable as work changes.
