Lightning
Beyond Self-Reported Skills: A Verified Standard for AI Fluency
Australia needs a 500% increase in its AI-capable workforce by 2030, yet 73% of workers do not know what AI skills they actually need, and 75% of employers say they cannot find the AI talent they are looking for. This gap is most visible, and most damaging, at the point of entering the workforce, where students move from structured learning into a fast paced and changing labour market with no consistent way to measure AI capability at all. This session introduces the Graduate AI Fluency Index (GAFI™), a framework built to close that gap. GAFI™ measures AI fluency across five levels, moving graduates from self-reported confidence to a verified, benchmarked signal that employers can trust and students can act on. Drawing on work building capability-led hiring tools for Australia's early-career workforce, this talk shows how measurement itself builds agency: when students can see exactly where they stand on AI fluency, they gain the confidence to close their own gaps rather than guess at what employers want in an AI driven workforce. Attendees will leave with a practical model for embedding AI fluency measurement into curriculum, work-integrated learning, and employability strategies, plus a framework for talking to industry partners about what verified AI capability actually looks like at graduation. Key Takeaways How the Graduate AI Fluency Index (GAFI) works, and what the fluency framework measures in practice Why self-reported AI skills are unreliable A practical approach for embedding AI fluency benchmarking into curriculum, work-integrated learning, and employability strategy
