Building Australia's AI-ready workforce: key insights from The AI Summit Australia

Fostering human capability alongside technology will be critical to Australia becoming an AI-ready nation.

That was the clear message from RMIT University's panel session at The AI Summit Australia, where academic, industry and student voices came together to unpack what's required for people and organisations to thrive in an AI-enabled future.

Moderated by Professor Rahil Garnavi, Director of RMIT's Artificial Intelligence Advanced Innovation Experience (RAIsE) Hub, the panel brought together Professor Sherman Young, RMIT's Deputy Vice-Chancellor Education; Yasminka Nemet, Future Skills Lead for Microsoft Australia and New Zealand; Peita Davis, Director of Skills, Education and Research at the Business Council of Australia; and Alexander McIntosh, an RMIT Mechatronics, Robotics and Automation Engineering student.

Bridging the capability gap

Davis outlined how Australia's major employers define an "AI-ready workforce" as capability across three levels: foundational AI skills (understanding how AI is built, its limitations, and how to use it safely and securely); applied AI knowledge (embedded in teams and individual workflows); and specialised AI skills (held by a smaller, technical cohort).

Citing Deloitte's recent State of Generative AI in the Enterprise report, Davis noted that while 85% of workers already use AI, only half report having basic skills, and just 7% describe themselves as advanced users.

She also referenced PwC's AI jobs barometer data, which shows a widening gap of employer demand outpacing workforce capability.

Nemet framed this as a "chicken-and-egg" problem, distinguishing between AI embedded in day-to-day work and AI adopted at an organisational level.

Too often, she said, "AI is being bolted onto existing processes and structures rather than prompting organisations to rethink how work gets done."

The real opportunity, she argued, lies in organisations approaching AI holistically, freeing people to focus on what they do best and enhancing outcomes over output.

Preparing graduates for a moving target

For Young, the challenge for RMIT is to prepare graduates for a bar that keeps rising.

"A 2026 graduate is expected to bring far more capability and experience to an entry-level role than a graduate did just five years ago, at a time when entry-level jobs are shrinking," he commented.

Davis agreed, suggesting small and medium-sized businesses are increasingly looking to their younger hires to lead the way on AI adoption, and larger employers expecting "AI natives" to help drive rollout across their organisations.

RMIT's solution is to balance discerning adoption of technical AI skills with enduring human capabilities, including curiosity, imagination and leadership, to produce "T-shaped" graduates who pair depth with breadth.

"Technology changes, but the ability to think critically alongside it endures. Resilience, agility, and curiosity allow graduates to keep learning as the tools around them evolve," Young said.

The student experience: trial, error and momentum

RMIT student Alexander McIntosh offered a candid account of his own AI learning curve, which was limited to basic chatbot support for assignments until last Summer.

He began experimenting with cutting-edge AI tools in his field of mechatronics, devoting 30 hours of trial and error before finding real momentum.

That early investment now allows him to move from problem identification to full-system solutions much faster, using AI to break down complex challenges and accelerate learning.

He applied this approach to his capstone project: building an autonomous tractor for Knuckeys with five fellow students.

McIntosh now leads an AI student community at RMIT, helping bring his peers along on the same journey.

"AI has effectively meant that I can learn more. It's like having a genius tutor who will curate answers to my desires," he said.

From experimentation to adoption

The discussion turned to what organisations need to move from scattered experimentation to meaningful widespread AI adoption, with Davis suggesting the greatest productivity gains come from full-scale implementation.

Nemet pointed to work already underway among educators to scaffold AI skills explicitly into curricula, citing United Arab Emirates, India and Singapore as exemplars in building AI literacy from K-12, rather than leaving it to universities and TAFEs alone.

Young pointed to RMIT's existing work training educators to embed AI capability into the Bachelor of Education curriculum, as well as the University's short courses supporting corporate upskilling.

"The task ahead is translating student agency and self-directed learning into properly scaffolded educational structures," he said.

AI in action: three demonstrations from lab to industry

RMIT brought its AI capability to life with three live demonstrations, each tracing a different path from student learning to real-world application.

• Dr Tim Wiley demonstrated autonomous AI and robotics through RMIT's RoboCup program, highlighting applications in computer vision, decision-making and intelligent systems.

• Alexander McIntosh showcased his Autonomous AgTech capstone project.
• Farahan Wazer, founder of Occivar, presented a privacy-first edge AI platform developed through RMIT Activator and now progressing towards commercial deployment.

A shared challenge and responsibility

Learn more about how RAIsE Hub is connecting education, research, industry and emerging talent to help build Australia's capability to thrive in an AI-enabled future.