How should governments engage with innovation ecosystems? Research by the Acton Institute, examining over 90 innovation districts globally, finds no governance model that reliably outperforms others. What matters is whether arrangements align with local institutional foundations and address each ecosystem's binding constraint, the weakest capability that limits returns from all other investment. This Insight catalogues twelve governance categories from Silicon Valley to Singa

Minister Ayres's National Press Club address draws selectively on the SERD's Ambitious Australia report to support a broader industrial policy agenda. The report's proposed SRI architecture is largely absent. R&D is positioned as one of the instruments in a reindustrialisation. The broader innovation system, including management capability, absorptive capacity, and place-based ecosystems, is unaddressed at this stage. No doubt, more is coming on actions and initiatives.

Australia's SERD report, Ambitious Australia, strengthens the research system but treats it as though it were the innovation system. This Innovation Insight argues for two shifts: defining innovation as the successful application of new ideas rather than production of research outputs, and widening the frame beyond science and technology to include creative practice, social innovation and place-based ecosystems. Firms, users and places, not universities alone, should be at th

The centrepiece proposals in Ambitious Australia would redefine what counts as R&D, leave the fiscal cost unexamined, and concentrate benefits on a very small proportion of Australian innovative businesses. The expanded startup stream converts the RDTI from an R&D incentive into an early-stage business subsidy. No OECD country subsidises deployment and commercialisation through its R&D tax incentive. Without forward estimates, it is impossible to judge whether proposed benefi

The SERD report's proposed National Innovation Council cannot direct Ministers across thirteen portfolios. Section 64 of the Constitution vests that authority in individual Ministers. This Insight proposes an alternative: a Cabinet-level coordination mechanism paired with a statutory Innovation Commission for independent research on innovation and industry economics, complementing the Productivity Commission's efficiency analysis and IISA's continuing R&D Tax Incentive admini

Australia performs strongly in research, yet struggles to translate this into innovation outcomes. This Insight argues that the SERD report reinforces this divide by treating the research system as a proxy for the innovation system. While funding, governance and capital reforms are well developed, the report underweights management capability, industry structure, demand-side dynamics and place-based ecosystems that ultimately determine whether research delivers economic and s

The Denholm Review presents Australia’s innovation system as a reinforcing flywheel coordinating research, firms, and growth. This Insight challenges that framing. It argues that the central constraint is the absence of strong market formation, capital depth, and global integration. Without these, policies risk improving internal coherence while failing to generate globally competitive outcomes. The question is whether Australia is building a system it can manage, or one that

Australia has revisited the idea of a National Innovation Council many times, often in response to concerns about fragmentation and weak coordination. The latest proposal in the SERD report again raises expectations. This Insight argues that the issue is not the absence of a coordinating body alone, but a deeper policy problem shaped by competing ideologies, institutional resistance, and unresolved tensions between science-led and system-based views of innovation.

The Strategic Examination of Research and Development, released 17 March 2026, is the latest review diagnosing Australia's innovation system and proposing reform. The panel's 20 recommendations are analytically sound and deliberately integrated. But the real test is implementation. Systemic reform must navigate sequential budgets, entrenched institutional resistance, and competing fiscal priorities, including defence, health, and cost-of-living measures.

Innovation ecosystems often contain the same institutions but produce very different outcomes. This Insight argues that the difference lies in “rate-limiting complements” such as trust, talent density, patient capital, governance capability, and access to markets. Identifying which complement is binding at a given stage may explain why many innovation policies underperform.

Artificial intelligence is generating unprecedented investment and uncertainty. This book argues that AI outcomes depend less on the technology itself and more on what it combines with: data quality, management capability, workforce skills, governance capacity and institutional design. A structured framework for policymakers and executives making decisions before the evidence is complete.

Why does the same technology lift productivity in some places and disappoint in others? The complementarity thesis explains the gap: returns depend on what technology is combined with. Applied to innovation districts, value comes from complements across placemaking, economics, business, and governance, underpinned by infrastructure. Leadership, collaboration, and learning mindsets become practical policy levers, not soft extras.

People regularly ask whether innovation districts can be deliberately created or whether they emerge beyond policy control. This Insight argues that districts arise through a small number of recurring pathways rather than a single replicable model. Drawing on international experience, it shows why policy outcomes depend less on ambition than on correctly diagnosing which pathway is plausible in a given context. Replicating the Silicon Valley or China approaches is fraught.

Innovation policy increasingly targets precincts and districts. But the evidence used to guide investment is often metropolitan in scale. This Insight argues that innovation outcomes emerge from the interaction of metropolitan enabling conditions and district-level mechanisms. It explains why single-scale analysis misleads policy, contrasts Australian governance with North American and European cities.It outlines a nested framework better suited to AI, productivity, and place

Innovation precinct strategies routinely promise "chance encounters" and "spontaneous collaboration" as if bringing talented people together in well-designed spaces automatically produces productive connections. The evidence is weak. Many precincts deliver proximity without interaction. Tenants occupy adjacent floors for years without substantive engagement. Shared amenities become places where people check phones rather than start conversations. My latest Innovation Insight

In research policy, the "Valley of Death" is a familiar lament. We assume that with enough tax credits or grant schemes, the bridge from discovery to market will build itself. Yet beneath the surface lies a more fundamental disconnect: the tension between what we can see as the "sociology of the academy" and the "epistemology of the engineer".

The real AI race is shifting from algorithms to infrastructure. Multi‑gigawatt data centres, reliable power and secure subsea cables now shape who captures value and who carries risk. Australia is an attractive Asia‑Pacific data‑centre market, but grid constraints and fragmented governance threaten its ambition to be a trusted Indo‑Pacific AI hub rather than a peripheral server‑farm landlord.

Australia’s National AI Plan makes strong commitments to infrastructure and adoption, but leaves governance and liability unresolved. This uncertainty exposes SMEs to risk, complicates investment decisions, and weakens public trust. History shows that technologies such as electricity became dependable only when standards, liability, and oversight aligned. AI now requires the same institutional attention if it is to move from experimentation to reliable national infrastructure

Australia’s next wave of innovation will depend on how clearly policy separates generic data centres from high‑performance computing (HPC). Bundling them into one “digital infrastructure” bucket directs capital to cloud‑style capacity while underinvesting in leadership‑class HPC needed for frontier AI, climate modelling, defence and advanced industry. The piece argues for explicit “AI‑ready HPC” and “AI‑capable cloud” tracks in national strategy, funding and governance.

Research and development is moving from laboratory-based models to digital platforms that integrate data, software, and AI. This Insight examines how many global firms now operate as de facto research environments, the implications for Australia’s capability and sovereignty, and the changes required in policy, measurement, and national strategy.