Views in the creative industries about the impact of artificial intelligence (AI) and automation tend to fall into one of two camps – unbridled optimism or existential panic. Neither is helpful for decision-makers at media companies. Rather, they need hard, evidence-based answers to key questions: How are automation and AI changing jobs in the media industry? Which tasks are being eliminated, and which new ones are emerging? And what does this mean for the skills required?
Australia's AI journey: From broad adoption to real value
Australia’s next AI challenge is converting adoption into sustained returns.
Australia has moved beyond early-stage AI adoption. Investment is substantial, deployment is broad and governance is comparatively mature. Yet outcomes remain uneven: 27% of Australian companies surveyed are classified as Industrialisers, while 37% remain stalled. For senior decision-makers, the central question is no longer whether to adopt AI. It is how to convert strong activity, investment and executive engagement into sustained business value.
Fast facts:
37% of Australian companies remain stalled on generative AI, despite significant investment.
43% of Australian SMEs are already embracing AI, with adoption continuing to rise across key sectors.
AUD 155 billion in total FDI was invested in the manufacturing and processing sector in 2025.
"Australia’s challenge is no longer simply getting AI into production but proving its value. Despite strong governance and substantial investment, many companies still measure AI activity rather than financial impact. Australian executives must introduce continuous ROI measurement to ensure that AI initiatives deliver measurable business outcomes."
Australia has built strong foundations, but value remains uneven
Australia’s services-led economy creates a distinctive AI opportunity. Banking, insurance, healthcare, education and professional services all involve high volumes of data, documents and judgement-intensive work.
Generative AI and agentic AI can help improve productivity across these established organisations without requiring a broad transformation of the physical economy.
The ageing population makes this opportunity more urgent. Demand for healthcare, insurance, government and other essential services is expected to rise while workforce growth becomes more constrained.
We see AI as part of the answer: helping organisations increase the productivity and capacity of the workforce already in place, preserve institutional knowledge and reduce repetitive work.
Australian companies have already put important foundations in place. Executive involvement is close to universal, formal AI governance is comparatively strong and investment is scaling.
The divide is between AI activity and measurable impact
Strong foundations, however, do not guarantee results. Australia has one of the highest shares of Industrialisers in the Asia-Pacific sample, but also the highest share of Stalled companies.
Stalled companies
Companies that are investing in or deploying AI but are struggling to convert that activity into meaningful business outcomes.
This contrast suggests that access to technology, capital and executive support is not the main differentiator. The difference lies more in how companies select, manage and scale AI initiatives.
The journey from proof of concept to production provides one indication of this divide. Only around a third of Australian companies convert at least half of their proof-of-concept initiatives into production.
The most advanced companies appear to be more selective about which projects they take forward and more deliberate about preparing them for scale.
"Australia is caught in somewhat of an AI paradox, holding the highest share of stalled companies in the region at 37%. So, to unlock the next frontier of growth, business leaders must move past treating AI as merely a shiny add-on and really start completely redesigning core workflows around autonomy."
Measurement is an even clearer point of difference. Australia records a high level of informal measurement and the lowest use of continuous ROI modelling in the regional sample.
Many companies are still tracking activity, such as pilots, users or systems deployed, rather than financial impact. We believe leaders need to connect operational improvements, such as faster processing or greater productivity, directly to measurable business outcomes.
Scaling autonomy requires redesigned workflows
Most Australian companies use AI to augment existing processes rather than redesign work around autonomy. While concerns about accuracy, security and compliance are justified, excessive caution can limit the value of agentic AI.
Australia’s Industrialisers take a different approach: they connect AI to proprietary data, redesign workflows and reduce inefficient handoffs.
Physical AI also offers targeted opportunities in sectors such as mining and agriculture, where autonomy addresses clear operational challenges.
Leaders should make value a prerequisite for scale by defining clear ownership, outcomes, costs and guardrails. Australia does not have an AI adoption problem, but it does have a value conversion problem.
The next phase will depend on connecting AI to core workflows and scaling autonomy where the financial case is clear.
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