Why AI is top of mind for HR leaders

While artificial intelligence (AI) was the second most common priority raised in our survey, it generated by far the most detailed feedback. Which is unsurprising, given how AI talk seems to be everywhere in every industry. HR is no exception.

That level of engagement reflects a shift in mindset. HR leaders are moving from asking if AI has a place in their work to asking how to make it deliver real value.

The context is important. Let’s be honest — our to-do lists haven’t got shorter in the last five years, and budgets aren’t getting bigger. HR teams are being asked to achieve more with fewer resources, while expectations for speed, personalisation, and insight continue to grow.

AI is one of the few levers that can help meet those demands, whether by automating repetitive work, surfacing workforce trends earlier, or enabling faster decision-making.

Industry surveys, such as the 2024 State of AI in Australian Human Resources report by the Australian HR Institute (AHRI) and QUT, show that more than half of HR leaders are actively seeking AI education, yet a significant capability gap remains. The organisations leaning in early are already seeing benefits, ranging from faster recruitment cycles and improved employee engagement to richer workforce insights and more accurate payroll.

The greater risk is not in moving too quickly, but hesitating while others define the standards, expectations, and competitive advantages of AI in the workplace.

The three-phase adoption model

AI can feel overwhelming because the possibilities are endless. For many HR leaders, their biggest challenge is not whether to adopt AI, but how they can do so in a way that delivers value without risks. The prospect of actually implementing and launching new AI software can be daunting, too.

Based on TechnologyOne’s own experience and the discussions from Origin Energy’s recent webinar, in which we took part, a phased approach offers the most effective path forward.

The key is to start small, learn quickly, and scale what works, all while maintaining governance and oversight.

Phase 1: Readiness

The starting point is building knowledge, curiosity, and confidence within the People and Culture team. This means demystifying AI — making it clear what it can and cannot do — and creating safe spaces for experimentation.

Giving teams access to AI tools in a low-pressure setting and identifying early champions helps drive adoption. Leaders must also decide whether to hire for AI skills, borrow expertise from other areas, or build capability internally.

Phase 2: Pilot

Pilots are designed to prove value without introducing significant risk.

A common example is implementing a chatbot to manage ‘tier-0’ HR queries, such as “How many annual leave days do I get?” or “where can I find the parental leave policy?”. This can free up staff for more strategic work while still generating insights on recurring questions.

Another is using AI to draft job ads, giving recruiters a head start while maintaining human oversight. At TechnologyOne, we developed a talent assessment and calibration tool in just a few hours using Replit and Claude, before ensuring it met IT and security requirements.

Phase 3: Rollout

Once pilots have proven value, AI can be embedded into core HR processes. This might include AI-powered workforce planning to identify skills gaps early or AI-assisted career planning tools that map future pathways.

Balancing opportunity with responsibility

AI has the potential to transform how HR operates. But with that potential - whether it’s automating repetitive tasks or analysing data for better insights – comes responsibility.

Adoption will reshape roles across entire business and industries. New positions such as AI specialists and ethics advisors are already emerging, while existing roles are evolving to become more strategic and data driven.

Indeed, in the weeks prior to writing this, many companies announced they had hired or were actively hiring for ‘Head of AI’ roles, something that used to be limited purely to tech companies. Skills like digital fluency, systems thinking, and ethical decision-making are fast becoming essential for non-AI specific roles too.

While that all sounds great, the risks are equally significant. Poor quality work from an over-reliance on AI is an ever-present issue to be aware of. So too are privacy breaches and biases in algorithms: we only recently saw the first major class-action lawsuit a few months ago, brought against Workday for alleged discrimination as a result of an AI-screening process for recruitment.

Poor AI use can erode trust, which is why it’s best to consider a “human-in-the-loop” approach. By that, we mean that while AI can support decisions, critical calls on hiring, performance, or promotions must always remain with people.

Every tool undergoes a privacy and ethics review and is supported by strong governance to ensure its use is fair, transparent, and aligned to organisational values.

Handled in this way, AI can strengthen HR’s credibility and create a foundation for safe, sustained innovation.

Turning insight into action: What does all this mean for HR leaders?

AI is no longer a distant prospect for HR leaders. In fact, it’s already embedded in a lot of the workplace tools and processes we use daily and has been for years. We just don’t think of it in the same way we do things like ChatGPT.

The challenge now is to move from passive exposure to active, strategic use, without falling into the hype trap.

Global research shows that 60% of AI projects never make it from prototype to production, and only 36% of organisations achieve the benefits they expected. Too often, AI initiatives are driven by hype rather than clear business needs, built in isolation from existing systems, or developed without considering industry-specific requirements like data residency or security standards.

For HR leaders, this is a cautionary reminder: success depends on being deliberate and aligned to organisational priorities.

That means building capability and confidence within your team. It means starting small with low-risk pilots that prove value before scaling.

And it means maintaining strong governance and human oversight to ensure AI tools enhance, not compromise, the employee experience.

The HR leaders who approach AI in this way will not only realise efficiency and insight gains but also help shape how the technology is used in their workplace.