Nearly all Australian employers now expect AI proficiency in new hires but 88% say finding that talent is a genuine challenge.
What’s happening: Research published today by specialised recruiter Robert Half found that 97% of Australian hiring managers now expect new hires to have some level of AI and automation proficiency, while 88% report difficulty finding candidates with the right capabilities.
The skills a new hire is expected to bring to the job have shifted. According to research published today by Robert Half, 97% of Australian hiring managers now expect new hires to demonstrate some level of AI and automation proficiency. The expectation is not limited to technical roles. It reflects a broader shift in how organisations view day-to-day work across finance, HR, operations and administration.
The demand is matched on the worker side. More than four in five workers, 83%, believe generative AI skills are necessary for career success, according to the same research, which surveyed 500 hiring managers and 1,000 workers across Australia in 2025.
Nicole Gorton, Director at Robert Half, described the shift as a change in baseline rather than a premium. “AI skills are becoming part of the baseline, but they are only one piece of the puzzle,” she said. “Employers are looking for people who can apply AI tools productively and responsibly, and in ways that create business value.”
The gap between expectation and supply
The problem is that supply is not keeping pace with expectation. Eighty-eight per cent of hiring managers report difficulty finding candidates with the right AI and automation capabilities, a significant gap given how broadly the expectation now applies.
The research found that 89% of businesses are already using AI in at least one finance, HR or technology process, and more than nine in ten technology leaders say AI is influencing workforce planning beyond experimental use. The tools are already embedded in how work gets done. The candidates who can use them well are harder to find than the job descriptions suggest.
For small business owners, this creates a practical tension. The instinct when hiring is to look for someone who already has the skills the business needs. But in a market where 88% of employers are struggling to find AI-capable candidates, competing solely on that basis is difficult, particularly without the salary bandwidth of larger organisations.
Gorton’s recommendation addresses this directly. “Organisations cannot rely on hiring alone to close capability gaps,” she said. “Upskilling existing staff and taking a skills-based approach to recruitment are critical.” For small businesses with existing team members who are willing to develop, investing in structured AI training may be more practical and more cost-effective than searching for a candidate who already has every capability required.
When the CV can’t be trusted
The second challenge the research identifies is less about finding candidates and more about evaluating them once they apply. Thirty-seven per cent of hiring managers say AI-generated applications are making it harder to accurately assess candidate quality.
The problem is structural. Generative AI tools allow candidates to produce polished, well-structured applications that may not reflect their actual skills or experience. For a small business owner without a structured assessment process, distinguishing between a genuinely strong candidate and a well-prompted application is increasingly difficult.
Gorton noted that the industry response is moving toward process rather than instinct. “While generative AI can help candidates present themselves more effectively, it can also make it harder to distinguish between overly polished applications and genuine capability,” she said. “Many organisations are strengthening their hiring processes with skills testing, deeper interviews and more rigorous checks to ensure candidates can deliver what their applications suggest.”
What small business hirers can do
For SME owners running their own hiring process, the practical response to both challenges is straightforward even if it requires some additional effort upfront.
On the skills gap, consider whether the role genuinely requires demonstrated AI experience or whether a candidate with strong foundational skills and a clear willingness to learn is a viable alternative. Given the shortage of experienced candidates, being rigid on AI proficiency as a prerequisite may unnecessarily narrow the field.
On the assessment challenge, move away from relying on application quality as a proxy for candidate capability. A short practical task relevant to the role, a structured interview with specific scenario-based questions, or a working interview are all more reliable signals of real ability than a well-written cover letter. For roles involving content, communication or data, asking candidates to complete a brief task without AI assistance, or transparently with it, can reveal more about their actual thinking than any application document.
The broader shift the research reflects is that hiring in 2026 requires more process than it did two years ago, not because candidates are less capable but because the tools available to them have changed what a first impression looks like. For small businesses doing their own hiring, building even a basic assessment step into the process is now worth the time.
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