Economic benefits of open foundation models
RESEARCH

Economic benefits of open foundation models

clock

02.08.2024 - 02:55

AITechnology

This study estimates the core economic benefits of open foundation models for businesses in the US economy. This considers profit uplift, operational efficiencies and cost savings in rent reductions for US businesses having access to open foundation models versus closed foundation models.

Estimating the benefits of open foundation models in AI

To inform the US National Telecommunications and Information Administration consultation on “Dual Use Foundation Artificial Intelligence Models With Widely Available Model Weights”, this study estimates the benefits of a ‘diverse’ generative AI ecosystem, where both open and closed foundation models exist and are available to access, against the counterfactual of a ‘restricted’ ecosystem where only closed foundation models are available.

Open foundation models could support faster adoption of generative AI amongst US businesses and provide an additional $1.5 trillion in benefits for them in 2035

The transparency, competition and innovation supported by open foundation models could accelerate the adoption of generative AI by US businesses in 2035

portableText image

Open models allow developers to access, deploy, and modify the model… which has played a key role in growing developer activity in generative AI

Open foundation models support transparency, competition and innovation, and are likely to drive higher adoption of generative AI across the US economy.

Open model weights allows researchers and authorities to inspect, test, modify and deploy models independently. US IT professionals recognize the security benefits of open source - 90% of US IT executives believe enterprise open source is as secure or more secure than proprietary software.

As seen with other technologies, open sourcing puts downward pressure on costs and gives businesses greater flexibility and choice. The top reason businesses use open source software is its cost competitiveness.

Publishing model weights enables developers to collaborate on fine tuning and crowdsource better, safer models. The number of third-party variant models publicly released to date is over 70,000.

portableText image

We modeled likely adoption curves for generative AI across the two scenarios: diverse and restricted.

In a diverse future generative AI ecosystem, there are highly-capable open and closed foundation models (similar to the current state). In this scenario, 88% of US businesses adopt foundation models.

In a restricted future generative AI ecosystem, government regulation or other competitive dynamics results in predominantly closed foundation models. In this scenario, 55% of US businesses adopt Generative AI foundation models.

portableText image

Read the report here.

Read our latest posts

Unlocking a Virtuous Cycle: Overcoming Barriers to AI in Australian Energy Systems
AIEnergy transitionElectricNet zeroTechnology

Unlocking a Virtuous Cycle: Overcoming Barriers to AI in Australian Energy Systems

Mandala's latest research, developed in partnership with Microsoft, examines the barriers to transformative AI adoption in Australia's electricity system. The research finds that AI is one of the few tools able to unlock capacity and efficiency from the existing grid without waiting on new transmission and generation capacity, yet adoption today remains incremental. Three soft barriers, a lack of shared strategy, weak investment incentives and siloed data, are constraining Australia's ability to capture this potential. Overcoming them will require joint action from government, the technology industry and energy utilities to prove AI's value, align policy settings and fund pilots through to deployment.

8 Jul, 2026

Demonstrating the local benefits of AI infrastructure in Wisconsin
AIEconomicsInternationalIndustry

Demonstrating the local benefits of AI infrastructure in Wisconsin

Mandala's latest research, prepared for Microsoft, examines the economic impact of hyperscale data center investment on Wisconsin's communities, businesses, and workforce. The research finds that committed data center projects will channel $16.5 billion to local suppliers, support more than 9,000 jobs during construction, and generate lasting economic activity across every county in the state, thereby extending Wisconsin's long tradition of industrial leadership into the AI era.

1 Jul, 2026

The essential infrastructure: How Australian banks power the economy
HousingSuperannuationFinancial servicesEconomics

The essential infrastructure: How Australian banks power the economy

Mandala's latest research, prepared for the Australian Banking Association, examines the often-hidden role Australian banks play in supporting households, businesses and the broader economy. The research finds that banks are deeply embedded in the financial lives of Australians - as lenders, as community investors, through the jobs they generate and increasingly as assets owned by Australians themselves through shares and superannuation. From financing homes and small businesses to supporting regional communities through hardship and disaster, the report builds a picture of a sector whose success is broadly shared across the Australian population.

17 Jun, 2026

The threat of climate change to the US insurance industry
ClimateHousing

The threat of climate change to the US insurance industry

This joint report by the Coalition for an Insurable Future and Mandala Partners examines how climate change is undermining the stability of the US home insurance market. Homeowners insurance premiums have risen 38% since 2021, outpacing both inflation and wage growth, while 1 in 7 owner-occupied homes are now uninsured. Climate risk could push national premiums 35–107% higher by 2050, leave an additional 1.5–2.5 million households without cover by 2035, and cost the broader economy $1 trillion. The aggregate cost could rise to over $3 trillion by 2050. A preliminary assessment of state-level policy responses across California, Florida, Louisiana, New York and Colorado finds that effectiveness is mixed, and that the burden of costs falls primarily on homeowners, insurers and taxpayers, rather than on the sources of the underlying climate risk.

10 Jun, 2026

Loading...