AI in Talent Acquisition: 2026 Report Findings
Recruiters are further into AI adoption than most talent acquisition strategies give them credit for. But the main headline that "AI is changing hiring." doesn’t tell us much. Here at Solve, we work inside TA functions every day, and the gap we consistently see isn't whether teams are using AI, but whether their hiring strategy, manager readiness, and workforce planning have caught up.
These insights below draw on Talent's 2026 AI in the Workplace report, based on responses from 1,505 business leaders and technology professionals across Australia and New Zealand. Paired with external research, the findings show where AI in talent acquisition is moving, where it’s stuck and what TA leaders should focus on next.
Where Hiring and Workforce Planning Actually Stand on AI
Look beyond individual AI use and the picture gets more interesting. Talent's 2026 survey shows AI workforce planning is moving, but more cautiously than the headline adoption numbers suggest:
- 44% of ANZ organisations are upskilling existing employees, making it the most common response to AI.
- 37% are reducing manual or repetitive work.
- Just 22% are redesigning roles or workflows, while another 22% are hiring AI specialists directly.
- Only 16% are using AI directly in hiring or workforce planning decisions, or changing the skills they hire for.
- 26% haven't changed their workforce planning at all due to AI.
That last figure deserves attention: one in four ANZ organisations are still treating AI as separate from how they plan and hire for talent, even though individual AI use has become routine.
The Upskilling-First Pattern: Why Most Employers Are Reskilling, Not Restructuring
Look at the findings by maturity and the pattern holds. 60% of organisations are building capability and 59% are redesigning work, but only 38% have actually shifted their hiring strategy, and just 14% are using external partners to accelerate the transition.
In other words, employers are choosing to build capability inside their existing workforce before they rethink role design or hiring strategy. That's a reasonable first move, but it also means most TA teams are left absorbing AI-era demands with structures that weren’t built for them.
Struggling to redesign roles fast enough to keep pace with AI-driven demand? Solve's Advisory service tackles specific talent pain points without locking you into a long-term commitment.
What's Actually Slowing Down AI-Driven Hiring Strategy?
Upskilling is the comfortable first move, the tougher hiring decisions are where momentum drops off. Based on Talent's data, the two most direct hiring-strategy actions, changing the skills organisations hire for and using AI in hiring decisions, both sit at just 16%, the lowest of any workforce planning response measured.
That's below both hiring AI specialists (22%) or redesigning roles (22%). So while the future of recruitment and AI is getting plenty of attention, most TA functions are still adding AI to existing hiring processes instead of asking whether those processes, roles and skill profiles need to change.
The Manager Readiness Gap Nobody's Hiring For
Managers are where AI adoption gets real, and Talent's survey found 80% of respondents expect AI to reshape middle-management roles, and while 76% of managers feel at least somewhat prepared to manage AI use in their teams, only 25% feel very prepared.
The hardest parts of the job, according to respondents, are data security and compliance (36%), managing overuse or poor use (29%), and knowing when human judgement is required (29%). Training the team ranks last, at just 13%, even though it's arguably the lever most likely to ease everything above it.
For hiring teams, this is a sourcing problem as much as a training one: candidates and internal promotions are rarely assessed on the judgement it takes to lead AI-enabled teams well.
Hiring managers who can lead through AI change are hard to find and slow to backfill. Solve's Embedded service puts specialist recruiters inside your team to fill critical roles fast, without losing momentum on the rest of your hiring plan.
Is ANZ's AI Skills Gap Bigger Than You Think?
The following data is sourced externally, not from Talent's 2026 ANZ survey, and is included here for benchmarking context.
The Parliamentary Library of Australia's analysis of OECD data found Australia ranked 15th out of 36 OECD countries on AI skills penetration in 2023, up from 19th in 2022. Progress? Absolutely. Job done? Not quite. Australia remained below the OECD average, with the gap most pronounced among women, who ranked 18th of 30 countries measured on AI skills penetration, against a ranking of 20th of 30 for men.
For hiring teams, that ranking is a demand signal: Australia’s AI skills gap makes AI-fluent candidates harder and more expensive to source directly. Building capability internally needs to be part of your Plan A, and not a Plan B.
How Global Employers Are Closing the AI Skills Gap
The following data is sourced externally, not from Talent's 2026 ANZ survey, and is included here for benchmarking context only.
Deloitte's 2026 State of AI in the Enterprise report, surveying 3,235 leaders across 24 countries, and found the top responses to AI-driven skills gaps globally are:
- Educating the broader workforce on AI fluency: 53%
- Structured upskilling and reskilling programs: 48%
- Hiring specialised AI talent directly: 36%
That order matches what Talent's ANZ data shows too: broad AI fluency and reskilling are outpacing direct AI-specialist hiring almost everywhere. The organisations pulling ahead aren't necessarily hiring more AI specialists than their peers, they're better at scaling capability across the workforce they already have.
Building AI-fluent teams at scale needs the right delivery model, not just the right training content. See how Solve's RPO service connects workforce planning directly into your hiring pipeline, from role design through to onboarding.
Confidential Data, Unapproved Tools: The Hiring Risk Most TA Teams Miss
Talent's survey found 57% of respondents name entering confidential or client data as a top AI risk behaviour, and just 16% are confident their staff know what data is safe to input into AI tools. For hiring teams specifically, this risk shows up in a place most TA functions haven't accounted for: candidate data, assessment records, and internal hiring notes are exactly the kind of sensitive information that can end up in an unapproved AI tool without anyone flagging it.
Almost 1 in 4 organisations (23%) shared in Talent's survey they've never been provided AI training or a policy refresh at all. If that gap exists broadly, it almost certainly exists inside recruitment workflows too, where teams handle sensitive personal data all day, every day.
What Good AI Governance Looks Like in a Hiring Context
The external data in this section is sourced from Melbourne Business School, not from Talent's 2026 ANZ survey, and is included here for benchmarking context only.
Melbourne Business School's 47-country Trust and AI study found almost half of employees globally admit to using AI in ways that breach their organisation's own policies, including uploading sensitive information into public AI tools, and 66% report using AI output without evaluating it first.
Put that into a hiring context, that means candidate screening, reference checks, and interview notes run through an ungoverned AI tool carries real exposure to data breaches and biased or unchecked decisions about real candidates. Good governance means making safe use clear and practical at every stage of the candidate journey, backed by training that helps people apply the policy when the pressure is on.
Contingent and Contract Talent: The Fastest Way to Plug an AI Capability Gap
Not every AI capability gap needs a permanent hire. Talent's data shows 22% of ANZ organisations are hiring AI specialists directly, but only 14% are using external partners to accelerate their AI transition, the lowest-used lever of the workforce planning responses measured.
That's a missed opportunity for many teams. Contract and contingent talent can close a specific AI capability gap, whether that’s a data governance specialist for a quarter or an AI-fluent analyst for a project, without the lead time or long-term cost of a permanent role, and without committing to a structure before you know exactly what the business needs.
Need flexible AI capability without a permanent hire? Solve's MSP solutions give you full visibility and control over contingent AI talent spend, all in one place.
What This Means for Talent Acquisition Leaders
- For TA and hiring leaders: the workforce planning data suggests most organisations are still one step behind, upskilling before redesigning, and redesigning before changing hiring strategy. Treat that sequence as a roadmap, not a stopping point.
- For hiring managers: AI judgement, knowing when to trust an output and when to intervene, is becoming a real hiring criterion, not just a nice-to-have. Start assessing for it directly.
- For HR and People leaders: the same policy and training gaps Talent's survey found across the workforce apply just as much to recruitment. Candidate data deserves the same AI governance attention as any other sensitive information.
- For teams managing contingent and contract workforces: external partners remain the least-used lever for closing an AI skills gap. That's an opportunity, not a limitation, for teams that need capability fast without a permanent commitment.
[Get the Full 2026 Findings →]
Frequently Asked Questions
What skills should recruiters look for when hiring for AI-era roles?
Based on Talent's 2026 survey, judgement and data awareness matter as much as tool familiarity. Only 25% of managers feel very prepared to manage AI use, so look for candidates who can explain when to trust an AI output when to check it and when a human needs to step in.
Should we hire AI specialists or upskill our existing team?
Both, but the sequence is important. Talent's data shows 44% of organisations are upskilling first, and Deloitte's 2026 global research shows the same pattern internationally, with workforce-wide AI fluency programs outpacing direct specialist hiring by a wide margin. Build what makes sense to own. Hire what you need to access quickly.
How is AI changing recruitment and talent acquisition workflows?
Based on Talent's survey, individual AI use is well ahead of workflow change: only 16% of ANZ organisations are using AI directly in hiring decisions or changing the skills they hire for, the lowest of all workforce planning responses measured. The next shift will be from adding tools to rethinking the work around them.
What's the risk of hiring managers who aren't ready to lead AI adoption?
Real and measurable. Talent's survey found 80% of respondents expect AI to reshape middle-management roles, but only 25% of managers feel very prepared, and data security and compliance is the single hardest part of the role, so leaving managers to work it out as they go isn’t much of a strategy.
Is contract or contingent talent a faster way to close an AI skills gap?
Often, yes. Talent's data shows only 14% of organisations currently use external partners to accelerate AI transition, the least-used option measured, which suggests it's an underused lever for teams that need capability without a permanent hire. For teams that need specialist capability now but aren’t ready for a permanent hire, contingent talent can be the faster, more flexible move.
Ready to Build an AI-Ready Hiring Function?
The gap between using AI and hiring for it won’t close itself. Whether you need to redesign a role, backfill a critical manager, scale AI fluency across your workforce, or bring in flexible capability without a permanent commitment, Solve's Advisory, Embedded, RPO, and MSP services help turn a workforce plan into action.