Australia’s race to adopt artificial intelligence is no longer about awareness. It’s about capability – and closing the widening gap between those experimenting at speed and those struggling to get started.
That gap is exactly what Future Skills Organisation set out to address when it launched its FSO Skills Accelerator-AI in August 2025. At the time, AI adoption appeared to be booming on the surface, but underneath, organisations were hesitant and unsure how to move forward.
“Individual adoption was skyrocketing on the surface, but underneath that, organisations were lagging,” Tiffany McHugh, who leads the FSO Skills Accelerator-AI, says.
“A small number of organisations were moving fast, but the majority were nervous, not organised in their attempts to implement AI, and not satisfied with generic advice that didn’t suit their context.”
Rather than adding more theory to an already crowded market, FSO focused on practical, hands-on capability building within the education and training sector. The logic is clear: confident educators build capable learners entering the workforce.
A system under pressure
The challenge is structural as much as it is technical. Australia’s education and training system is highly fragmented, with national regulation, mixed funding models and significant autonomy at the provider level.
At the same time, educators are under pressure to prepare a workforce for an AI-enabled economy, often without the tools, confidence or safe environments to experiment.
FSO’s response has been to position the skills accelerator not as a training provider, but as a national orchestrator.
“We saw ourselves as connecting people, surfacing what’s working, and turning experiments into scalable, repeatable practice,” Ms McHugh says.
The model is simple and effective: connect, learn, do.
Scaling at speed
In just eight months, the skills accelerator has grown from 12 partners to more than 900 across 300 organisations, a level of uptake that points to both timing and unmet demand.
“Growth is driven by relevance and timing. We provide a place where people can engage without needing all the answers. You can arrive highly advanced or with no skills at all – we welcome both,” Ms McHugh says.
The Skills Accelerator centres on real-world problems – assessment design, curriculum development, teaching practice – and creates opportunities for participants to test industry-aligned solutions in context.
“Capability building isn’t about pushing information out,” McHugh says. “It’s built through participation including peer-to-peer learning, shared and relevant examples and a common language.”
Learning by doing
This philosophy comes to life through the skills accelerator’s action learning sprints, which connect knowledge to practice.
In one recent example, the program flipped its traditional model. Instead of organisations pitching problems, technology providers pitched solutions in a ‘reverse sprint’ format, demonstrating practical tools that could be immediately trialled.
Twelve vendors, including organisations like Deloitte, Turnitin, Supahuman and Red Velvet AI, presented solutions spanning assessment integrity, curriculum design, learner support and compliance, backed by more than $1.2 million in technology access and support.
The result was a surge in engagement: 65 pilot opportunities were generated, creating a pipeline of real-world case studies and shared learning.
“These were practical, tangible examples of how workflows could change,” Ms McHugh says. “We saw a clear shift – from interest to excitement and willingness to adopt.”
Across the program, this shift is emerging as the clearest early signal of impact.
From experimentation to scale
While the first phase of the Skills Accelerator has focused on experimentation and community building, the next phase is about consolidation and scale.
The ambition is to embed what works across the system – building on early trials to repeatable, industry-aligned approaches that ultimately lift AI capability across the workforce.
“Success isn’t about doing more,” Ms McHugh says. “It’s about being more intentional – taking what works in one organisation and scaling it across the sector.”
This includes aligning activity to a common skills framework, ensuring consistency and portability of learning, and tracking clear signals of impact like increased adoption of shared tools and improved learner outcomes.
The goal is for AI capability to become embedded in everyday practice.
“We want AI to be part of how teaching and operations happen, not the exception,” Ms McHugh says.
A coordinated path forward
In a system where duplication, fragmentation and isolated experimentation are common, the ability to connect people, share evidence and build confidence is emerging as a critical lever.
Connections and coordination matter beyond the education system itself: a workforce confident with AI depends on training providers and industry moving together.
“We want to avoid organisations experimenting in isolation,” Ms McHugh says. “Instead, we encourage experimentation in public, where learnings can be shared – even when things don’t work perfectly.”
That shift may ultimately prove as important as any individual technology.
Because in the AI era, the organisations that move fastest won’t necessarily be those with the most tools. They will be those with the confidence and capability to use them.
This article was produced by InnovationAus.com in partnership with Future Skills Organisation.
Do you know more? Contact James Riley via Email.