AI as Rocket Fuel for Human Potential: Julia Anas on the future of work in ANZ

Artificial intelligence (AI) has swiftly evolved from a distant buzzword to an essential driver underpinning the operations, collaboration, and competitiveness of organisations across Australia and New Zealand (ANZ). Julia Anas, Chief People Officer at Qualtrics, provides a nuanced perspective on AI’s transformative role—not as a substitute for human ingenuity, but as a catalyst that elevates creativity, productivity, and a deeper sense of purpose in the workplace.

At the heart of Qualtrics’ approach to employee experience is a commitment to listening and acting on feedback. “When I joined Qualtrics in early 2021, I spent 90 days on what I called my ‘listening and learning journey,’ meeting with culture carriers, long-tenure employees, and people across regions and functions,” Anas recalls. She emphasises that employee experience is the differentiator between good and great companies—a philosophy that is embedded in Qualtrics’ own practices, from frequent pulse surveys to analysing specific moments in the employee lifecycle.

Yet, Anas is clear that listening is only valuable if it leads to action. “We use the same sentiment analysis and predictive insights we sell to customers to understand our own people’s intent to stay, what’s working, and where we need to invest. It keeps us honest. And when employees see that their feedback leads to real change… that builds the trust that makes everything else possible.”

For Anas, the impact of AI on the workplace is profound. “AI is fundamentally shifting the work teams do, not just how they do it. The single greatest impact will be an exponential increase in the velocity of collaboration and innovation.”

She is quick to clarify that the goal is not to replace human intelligence, but to augment it. By automating manual tasks and reducing organisational drag, AI frees up people to focus on judgment, creativity, and deep problem-solving. “This creates a powerful partnership where AI handles speed and data, and humans focus on insight and impact.”

But technology alone is not enough. “AI is rocket fuel, but it won’t fix a broken engine,” Anas warns. If communication or psychological safety are lacking, AI will simply accelerate dysfunction. The real transformation, she argues, requires leadership that prioritises trust, clarity, and culture, ensuring that people feel supported through change.

The opportunities AI brings for workforce development and upskilling are immense. “The primary opportunity is intelligent personalisation at scale… AI is the rocket fuel that allows us to finally deliver bespoke development pathways that are adaptive, real-time programs based on an employee’s current role, skills gaps, career aspirations, and unique learning style.”

HR leaders, Anas says, must prepare employees through radical transparency about the realities of AI, aggressive investment in the uniquely human skills—critical thinking, judgement, collaboration, empathy—and by making development continuous, not episodic. “The half-life of skills is shrinking rapidly,” she notes, highlighting the need for ongoing learning.

AI’s rapid adoption brings uncertainty and anxiety—something Anas believes leaders must address directly. “HR leaders must model comfort with uncertainty. If we’re anxious about AI, our teams will be too. We must show our people we are learning alongside them, building a culture of trust where vulnerability and continuous reskilling are seen as strengths, not weaknesses.”

As organisations accelerate AI adoption, the question of balance becomes critical. “Instead of asking ‘what can AI do?’ we must lead with ‘what should only humans do?’” Anas suggests. She advocates for a model of ‘intelligent augmentation,’ where AI delivers speed and efficiency, but humans provide the essential gyroscope for trust, quality, and direction. Over-automation risks eroding the human touch; under-automation risks missing out on efficiency gains. The answer, Anas argues, lies in being “ruthlessly clear about where humans add irreplaceable value.”

“If automating something makes your employees’ work more meaningful and less tedious, do it. If it erodes trust, relationships, or the quality of outcomes that matter to customers, don’t. Be willing to course-correct when you get it wrong, because we all get it wrong sometimes.”

As AI becomes more deeply embedded in HR processes, ethical considerations must be front and centre. “Transparency isn’t optional,” Anas stresses. Employees have a right to know how AI influences decisions about their careers and compensation. Black-box algorithms are fundamentally unethical, and lack of clarity erodes trust.

Data privacy is another non-negotiable. “The data employees generate through their work is incredibly revealing… That data can improve experiences or it can enable surveillance, and the line is thinner than people think.” Clear policies around data collection, use, access, and retention are essential.

Finally, Anas insists on the importance of human oversight. “AI should inform decisions, not make them autonomously. There needs to be a human in the loop who understands context, can exercise judgment, and is responsible for outcomes. When AI gets something wrong, and it will, someone needs to own that mistake and fix it.”

AI is already making recruitment faster and, when done well, fairer. “We’re already seeing AI screen resumes more consistently than humans, identify candidates from non-traditional backgrounds who might have been overlooked, and significantly reduce time-to-hire.” Speed is crucial in tight talent markets, but Anas is most excited about AI’s potential to improve the candidate experience. “AI can provide real-time feedback, personalise communication, and ensure candidates aren’t left in the dark about where they stand. How you treat candidates—even the ones you don’t hire—impacts how they feel about you as a company.”

Still, she cautions, hiring is about fit for purpose, culture, and potential—qualities that are genuinely hard to quantify. “AI should handle the screening and logistics, but humans need to leverage their judgement in making the decision. And we need to be vigilant about bias… Regular checks are essential.”

With AI taking over repetitive tasks, the demand for uniquely human skills will only grow. Anas identifies three categories as critical:

Critical thinking and judgement: As AI compiles data and recognises patterns, humans must interpret what matters, make decisions amid uncertainty, and understand the context algorithms miss.

Human synergy and empathy: The ability to build trust, navigate complex stakeholder relationships, and foster collaboration becomes a key differentiator.

Adaptive and agile learners: Those comfortable with constant learning, able to ask probing questions, and who can work alongside AI rather than compete with it will thrive.

Anas is candid about the impact of AI on entry-level roles. “We are not talking about roles disappearing; we are talking about roles being fundamentally upleveled.” Routine tasks like data entry and basic research are already being automated, which means entry-level workers will be expected to contribute to strategic projects and develop professional judgment much earlier in their careers.

“The adverse impact on jobs will only occur if organisations fail to adapt. The real question is whether leaders will embrace the opportunity to redesign entry-level roles differently.” She calls for intentional leadership to create jobs that leverage the native AI fluency of the next generation, focusing on critical thinking, learning, and collaboration.

Supporting employees through transformation

Navigating the uncertainty and change brought by rapid AI adoption requires leaders to model vulnerability and validate concerns. “Leaders must start by acknowledging that rapid AI adoption is disruptive, and we’re all learning this together. Employees want to be closely tied to leadership on this journey. Leaders who pretend to have all the answers or dismiss genuine fears will lose credibility fast.”

Anas champions radical transparency and feedback, constant communication about what is being experimented with, and genuine support for continuous learning—even if it means sacrificing short-term productivity. “The organisation must signal and model that continuous learning is valued over immediate productivity increases during this transition.”

Above all, psychological safety is paramount. “People need to feel comfortable admitting when they’re struggling or asking for help with new AI tools. Leaders set that tone through their own behaviour. For instance, I champion vulnerability with my own team each week in our slack channel, we share AI discoveries, or just as importantly, where AI hasn’t nailed it.”

Anas does not shy away from the risks AI presents. The biggest is creating a workforce that feels monitored rather than supported. “AI’s ability to track productivity and analyse behaviour can feel intrusive if not handled with clarity. Our research shows significant perception gaps between employees and senior leaders regarding AI, signalling a lack of trust. Trust is harder to earn during times of change and disruption. Once trust collapses, engagement does too.”

She highlights the danger of implementing AI faster than people can be upskilled to work with it, creating frustration and wasted potential. “It’s important for leadership to be patient with the learning curve and truly value continuous reskilling, the human curriculum over the immediate productivity increases.”

Finally, there is the risk of perpetuating existing inequities. “If AI systems are built on flawed historical data, they will embed into hiring, promotion, and performance management at scale. We must subject all workforce AI to rigorous ongoing human oversight and auditing.” Cross-functional governance teams must continuously check systems for fairness, explainability, and ethical alignment.

Anas’ vision for the future of work in ANZ is one of partnership. AI is not a threat to be feared, but a tool to be harnessed for greater human impact. The challenge for leaders is to ensure that as AI accelerates the pace of change, they do not lose sight of what makes organisations great: trust, empathy, and a relentless focus on people. “We work to live, we do not live to work,” Anas concludes. “The real question is: does this automation help employees live more fulfilling lives while doing better work? If yes, move forward. If not, rethink it.”