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.
Future AI Leaders Program panelists at The AI Summit Australia 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.
