Published on the 03/09/2026 | Written by Heather Wright
Open-weight models, AI program reshape procurement choices….
Australia’s latest bid to strengthen its domestic AI sector with the Buy Australian Partnership Program, comes as enterprises increasingly look beyond proprietary AI platforms and explore open-weight models.
The federal-government backed Buy Australia AI Partnership, launched last week by Stone & Chalk with the National AI Centre as principal sponsor, aims to connect Australian AI providers with major enterprise buyers, initially in the financial sector. Financial institutions ANZ, Commonwealth Bank, NAB, Westpac and payments provider Cuscal.
“It gives Australian AI companies direct exposure to enterprise expectations, while helping organisations better understand the capability available locally.”
The program is designed to help local providers build a deeper understanding of how organisations evaluate, procure, govern and deploy AI, in order to hlep them meet enterprise requirements, and connecting them with potential customers.
It’s a program designed to build Australia’s AI economy, or in the words of Lee Hickin, executive director of the National AI Centre, to ensure Australia is ‘the makers, not takers’.
“It gives Australian AI companies direct exposure to enterprise expectations, while helping organisations better understand the capability available locally,” Hickin says.
Organisations including the Australian Banking Association, Customer Owned Banking Association, Insurance Council of Australia, Australian Information Industry Association, Committee for Economic Development of Australia, MYOB and blockchain provider Solana have thrown their weight behind the program.
Andrew Charlton, Minister for Science, Technology and the Digital Economy, says there are already over 1500 Australian AI companies building ‘world-class technology’. “The challenge is getting in front of the organisations that can buy their products,” he says.
In a First Take on the initiative, Gartner says government-backed supplier ecosystems are emerging as one way to develop technology capability. Rather than relying only on regulation, subsidies or public procurement, governments can connect private-sector buyers with local technology providers and improve their ability to compete for enterprise opportunities.
Open-weight for enterprise
That trend is playing out as enterprises themselves reassess how they source and deploy AI.
A new Gartner report highlights growing enterprise interest in open-weight models, with the analyst company saying the performance gap between open-weight and proprietary large language models has narrowed dramatically and is now ‘close to disappearing altogether’. Driving that is the ‘runaway spending on AI and enterprise efforts to contain those costs’.
Unlike proprietary AI services accessed through vendor APIs, open-weight models allow organisations to download, inspect and modify a model’s core numerical parameters. Gartner says they are becoming an increasingly attractive option for IT-forward organisations and their token-hungry applications.
“Beyond potential cost savings, these models provide flexibility, control and independence from API-driven large language model hyperscalers and lock-in to their platforms,” Should You Ban or Embrace Open-Weight AI Models, by Gartner’s Darin Stewart, says.
“Open-source AI and weights offer substantial benefits over their closed, proprietary cousins,” the report says. “Open LLMs can lower switching costs, both financial and technical, reducing the risk of platform and vendor lock-in. Local or private cloud deployment, deeper customisation, resilience from provider dependence, and greater freedom to test, audit and optimise models for specialised work all indicate the unique appeal of open-source AI.”
The shift is also attracting attention in New Zealand.
Earlier this year, Amanda Williamson, director of Deloitte’s New Zealand Artificial Intelligence Institute told iStart Kiwi companies were beginning to recognise the strategic importance of the technology underpinning AI deployments. She highlighted open-weight models as one option for companies to consider.
“Until now, an approach that most organisations have been using is just switching on the model that’s provided in whatever technology stack they have access to, but there are other things that can be done, such as using open weight models,” Williamson said.
Greater control, greater responsibility
For enterprises, however, greater control comes with greater responsibility.
Gartner says organisations adopting open-weight models assume responsibility for ongoing management, including patching, monitoring, access controls, compliance and governance. The report also highlights concerns around data provenance, training bias, data handling practices and the removal of safety controls. “However, most commercial AI and LLM providers involve similar risks, just abstracted away from the customer and absorbed by the vendor,” Stewart notes.
The issue becomes more complex when foreign-developed AI models enter the mix.
Australia is among several countries which have placed formal restrictions on DeepSeek and other Chinese AI offerings. While Gartner says many of the concerns about Chinese technology are ‘overblown’, it acknowledges there are legitimate dangers than need to be taken into account and addressed.
It argues enterprises should evaluate models on their architecture, training data, capabilities and governance characteristics, rather than relying solely on country-of-origin considerations, saying organisations should adopt policies that are ‘nationality-aware, but nationality-neutral’.
For procurement leaders, the message on both fronts is similar: Expanding choice does not remove the need for due diligence.
While the Buy Australian AI program will enable proactive supplier discovery, and earlier visibility of emerging local providers, Gartner warns participation in Australia’s Buy Australian AI program should not be treated as proof of enterprise readiness, while the growing availability of open-weight models should not be viewed as a shortcut to lower-cost AI. In both cases, organisations still need to assess cybersecurity, governance, scalability and commercial risk.
But, it says, expect government-backed supplier development programs to become more common. It’s predicting that by 2028 at least five major technology markets will operate ecosystems linking domestic AI providers with large enterprise buyers.
