A Literature Review Analysing Public Opinion Data on Public Perspectives of the National AI Plan: Action Item Number 5

Policy Research Program
6 days ago
14 min read

Authors: Phillipa Mills and Rocco Wahhab

INTRODUCTION

The National Artificial Intelligence (AI) Plan, released in December of 2025, is an initiative outlined by the Federal Government in order to highlight the regulatory direction of AI in Australia [12]. AI refers to any software technology that enables computers or machines to perform tasks which once required human intelligence, such as creativity, learning, problem solving, decision making and autonomy [23]. The plan aims to ensure that Australia remains resilient, productive and competitive in the face of innovation [12]. The plan outlines three primary goals, “Capture the opportunity”, “Spread the benefits” and “Keep Australians safe”. Within these goals exists a series of action items which indicate the areas which the Government intends to structure development around [12]. Particularly, action item number 5, entitled “support and train Australians”, focuses on spreading the benefits of AI to the labour force and ensuring that benefits are messaged fairly and inclusively [13]. The plan itself has faced support and scrutiny from the public, with opinions focusing on the economic impact, sustainability impacts and legal impacts and issues arising from the direction of the plan.

Figure 1 of the National AI Plan entitled “Our National AI Plan on a page”

This literature survey reviews public opinion data in order to synthesise the key areas of support and scrutiny. Public opinion data is a useful tool in analysing and framing public policy decisions, which was primarily used during the COVID-19 Pandemic [11]. In analysing the general public opinion is shaped by leading academics, media concerns, public figures such as politicians and legal services within Australia. These voices shape perspectives and can allow the government to continue to refine their policy direction and achieve optimal outcomes which reflect community desires.

This literature survey will highlight the following areas of public opinion concern:

Context, previous direction and current trajectory;
Economic impacts;
Sustainability and safety impacts;
Legal impacts, including legal issues and gaps;
A Case Study of automated warehousing.

CONTEXT, PREVIOUS DIRECTION AND CURRENT TRAJECTORY

As of May 2026, the minister responsible for the oversight of the National AI Plan is Senator The Honourable Tim Ayres (Minister for Industry and Innovation of Australia). Under his oversight, the National AI Plan was published. However, prior to the release of the plan, former Minister for Industry and Innovation The Honourable Ed Husic MP publicly announced a starkly different direction which was later scrapped [4]. In September of 2024, the former Minister flagged ten mandatory guardrails which were under development [4]. The aforementioned guardrails included:

risk management,
data governance,
testing protocols,
human oversight,
transparency,
contestability,
supply chain visibility,
record keeping
conformity assessments [10].

In early of 2025 the Productivity Commission recommended that these guardrails be suspended until an audit of gaps in the law could be completed and a potential $116 billion boost to the economy was not mismanaged [10]. Following the audit and upon the release of the current National AI Plan, Minister Ayres revealed a new direction, shifting away from the guardrail-centric approach [4]. Minister Ayres claimed that current Australian laws, in areas of communication, criminal and financial laws, are still sufficient in addressing AI [9]. Instead of committing to an AI Act, the Federal Government posits that the newly established AI Safety Institute is more suitable than a standalone Act [9]. This direction has received support and criticism from a number of public figures, particularly the former Industry Minister Ed Husic has called for an Act that could be proactive in response to rapid development of AI, rather than a “whack-a-mole” regulatory approach where the Government relies of existing laws, which in turn may disadvantage business and discourage investment [4]. Other bodies and voices have commented on the economic impacts, sustainability and safety impacts as well as the legal implications of a response approach, outlined in the National AI Plan, rather than a proactive approach.

ECONOMIC IMPACT

One of the key areas highlighted under the National AI Plan is the relationship between AI development and its impacts on the economy. The Plan focuses heavily on ensuring that the economic aspect of AI is managed and enhanced, especially in relation to innovation, business and labour. Largely the focus of the plan is positive for economic considerations [6]. In particular, public bodies have emphasised the strength of the Plan in finding a balance between regulation, safe usage and speed of innovation as to not stifle development and support AI investment [1]. Furthermore, it has been noted that there are genuine tangible and practical outcomes that can manifest as a result of the current plan [1]. The plan, in an overall economic capacity, is a positive step in recognising growth fostered by AI development, such as a potential surplus in 200,000 new jobs and a $115 billion dollar a year investment into the economy by 2030 [1].

As of December 2025, Australia attracted $10 billion worth of investment in data centres, while forecasts predict that data centres would make up 6% of all electricity demanded by the end of 2030 [4]. This highlights a prime economic opportunity for the government, with a slow and steady approach preventing over-regulation. Public opinion data aligns with AI implementation in the workforce, with 73% believing that the workforce can meet the speed of technological development, while 93% of workers believe that AI will change their work by 2030 [1]. It has also been noted that the Plan is strong in its recognition of AI as a central factor in global competitiveness, industry and economic security, but must be used safely [3].

However, the plan also mentions an attempt to improve public service efficiency, however potential improvements are not explicitly possible [7]. As a result, the plan attempts to capture the economic benefits of AI such as job growth, economic investments and development in Australia. The plan largely focuses on the economic possibilities and opportunities of AI over other key areas [2]. Therefore, this demonstrates the economic impacts which occur as a result of the direction outlined in the national AI plan.

SUSTAINABILITY AND SAFETY IMPACTS

Another key topic for discussion seen within public opinion data is the issue of sustainability and safety issues associated with the use of AI nationally. This area is largely topical, with opinions varying from critique to support. AI has been used not only to aid the labour force and replace workers, but it has also been used to cause harm such as deep fake pornography [9]. Many have recognised that holistically, the Plan is a “promising first step”, including some attempt to mitigate potential risks through funding [2].

Additionally, the National AI Plan does also attempt to promote sustainability both environmentally and employment, such as data centres and AI Hubs increasing employment opportunities in regional locations [7]. It has also been said that this plan could lead to a promising international framework focused on AI risk mitigation [2]. However, the AI plan emphasises economic opportunity over safety and labour sustainability [2]. Additionally, there are still doubts as to whether or not AI can actually boost productivity for private organisations and businesses while balancing sustainable practices [7].

As of current, the National AI Plan relies on existing legislation that addresses older software rather than AI global AI agents [2]. Primarily, the potential risks of emerging AI are not adequately mitigated or addressed in current legislation, and neither are environmental and sustainability concerns adequately addressed in the Plan [2]. Academics have emphasised that while economic opportunity is important, the plan should instead lead with safety leading rather than following [2].

The media has also noted that previous guardrails are “nowhere to be found”, and the AI Safety Institute is too responsive in preventing environmental, sustainability and safety risks [6]. Other sustainability and environmental issues such as fast tracked data centre approvals may mean biodiversity and labour impacts are not sufficiently considered in a shorter duration [7]. There are also concerns about the environmental cost of data centres such as water usage and energy demands [7].

In a holistic capacity, the National AI Plan and the restrained approach to regulation, safeguards and implementation in the workforce does not reflect the desire of the public, where around 75% of Australians want stricter regulation of AI [7]. Academic critique has emphasised this, Sue Keay (director of University of New South Wale’s AI Institute) articulated resentment with the extensive wait for the plan, where AI capability is only just beginning to be considered [10]. She emphasised that while economic opportunity is critical, so too is safety and sustainability of industry and environment [10]. She critiqued the lack of an AI Act and declared a need for guardrails, trustworthiness, and mandatory guidance rather than voluntary compliance [10].

Consequently, this elucidates the various concerns and support arising from public opinion in the face of the release of the National AI Plan in December of 2025.

LEGAL IMPACTS, INCLUDING LEGAL ISSUES AND GAPS

Discussion on the legal implications, as well as the legal gaps observed in the National AI Plan, are at the centre of public debate. Particularly in regards to the approach the plan highlighted; where the Federal Government is relying on existing legislation rather than a contemporary standalone AI Act [9]. Such direction has both positive and negative implications, with a large majority of the public seemingly critiquing the limited approach.

On one side, political reporter Jake Evans has noted that “while the government has opted for a lighter-touch response in its AI plan, it has also left the door open to a stronger response in the future” [4]. Lawyers from the firm White and Case have noted that the objectives are “commendable”, and the “incremental and evolutionary approach” would be positive in ensuring AI is implemented on a large scale, including the workforce [5]. Academics have also commented that preferring incremental development over large industry regulations and changes is logical in regards to the key purpose of The Plan [7].

However on the global scale, other approaches such as the European Union AI Act and the Māori AI Governance Framework have been effective measures in both regulating AI in industry and employment, as well as ensuring opportunities are maximised [8]. Greens Senator David Shoebridge commented on another aspect that the plan does not address, mental health issues caused by AI algorithms [4]. Mental health issues could stem from a sense of impending doom, anxiety or restlessness, fear of job insecurity, validation of delusional thoughts, emotional dysregulation, and social withdrawal [15]. Further, the legal directions within the Plan lack specificity, detail and performance indicators for progress measurement [5]. While the plan is attempting to focusing on bridging skills gaps, ensuring, the fair sharing of productivity benefits, and protecting worker rights, rather than focusing solely on automation-driven job displacement [16], the plan does not provide concrete commitments or specificity as to what commitments will ‘look like’ long term [7] other than the following in Action Item number 5:

Voices have argued that these actions, while positive in recognition, are limited in application, practicality and efficacy. Additional legal uncertainty stems from legislative and regulatory provisions of up-and-coming software systems and their handling of data in capacities such as consumer relations, industry and employment [5]. Due to this, there are still refinements necessary in order to address regulatory gaps, infrastructure restraints, and overcoming challenges which would allow for Australia to become a global leader in safe implementation of AI in work, education and other areas of life [5]. Though, this means that reform will be significantly backlogged and slow given the ‘incremental approach’ taken by the Plan [7]. This would result in further delays and waiting periods which have already been previously emphasised as a public concern [10].

Other areas of concern have also been noted with the legislative provisions within the Plan, both generally and in relation to Action item Number 5:

AI Safety Institute is at the centre of the Plan rather than a legislation itself
The Plan outlines voluntary codes of conduct rather than mandatory guidelines
The AI Safety Institute is advisory rather than direct reform or administerial power
Technology companies and social media companies are not adequately held liable under current laws, with consistent exploitation of loopholes
While there is some improvement in AI training for staff, the use of falsified information, hallucinations and artificial data can prevent genuine training or create mis-skilled workers
Limited regulation or commitment to uphold cultural and voluntary codes of conduct [8]

Summarily, the legal provisions and actions outlined under the National AI Plan (especially in Action Item Number 5), while a positive step forward in recognition and development are currently facing criticism in regard to specificity, reliance on current legislation and limited progress benchmarking. Of which, may impact the overall efficiency and efficacy of the National AI Plan when ensuring the Australian workforce and education sectors are adequately trained and equipped with skills necessary to navigate AI implementation.

CASE STUDY: AI-AUTOMATED WAREHOUSING

WHAT IS AI-AUTOMATED WAREHOUSING?

Automated AI warehousing is the integration of AI, machine learning and robotics to manage picking, packing, and inventory management within warehouse operations [19]. It optimises speed, accuracy, and uses data analytics to predict demand and streamline workflows [20].

KEY STATISTICS (2026, GLOBALLY):

In 2026, around 4.7 million warehouse robots were installed in over 50,000 warehouses globally,
AI Warehouse Automation has generally resulted in 25-30% reductions in labor costs, 300% increase in completion rates, and accuracy close to 99%,
AI inventory tools cut ‘pick paths’ by 60%,
60% of warehouses plan to increase automation budgets by 20% in 2026, focusing on AI-driven software solutions [17].

KEY USES OF AI IN AUTOMATED WAREHOUSING:

Machine Learning for Predictive Optimisation
Computer Vision for Real-Time Warehouse Visibility
Natural Language Processing for Voice-Enabled Operations
Reinforcement Learning for Autonomous Robotics and Routing
Predictive Demand Forecasting and Inventory Optimization
Automated Order Picking and Dynamic Route Optimization
Computer Vision for Real-Time Quality Control and Hazard Detection [14].

KEY BENEFITS OF AI-AUTOMATED WAREHOUSING:

Efficiency Improvements
Cost reduction
Enhanced Decision-Making Capabilities
Competitive Advantage
Proactive Risk Mitigation and Workplace Safety [14].

KEY CHALLENGES OF AI-AUTOMATED WAREHOUSING:

Data Privacy and Security Concerns
Skill Gaps and Workforce Readiness
High Implementation Costs
Integration Complexity and Data Silos
Ethical Considerations and Change Management [14].

BENEFITS IN ACTION:

Amazon is an exemplar model of successfully integrated AI Automation within warehouses, which is used to foster and aid manual labour. Amazon has integrated 750,000 AI-powered robots and generative AI mapping systems across global centers. This has allowed Amazon to achieve an estimated $4 billion in annual savings on fulfillment costs, reducing picking and packing times by 75% [14].

IMPACT IN AUSTRALIA:

AI automation in Australian warehousing evaluates operational constraints to assist managerial decision making, acting as a tool rather than a replacement. AI automation in Australian warehousing does this by:

Detecting anomalies early
Suggesting resolution pathways
Routing issues with contextual information [18].

Warehouse managers are relying on AI Automation to assist in combatting the following:

Rising input and operating costs
Labour shortages in metropolitan and regional markets
Increasing service expectations
Pressure for predictable performance under demand variability [18].

AI automation in Australian warehousing simultaneously:

Reduces cost to serve
Minimises errors and rework
Stabilises output during volatility [18].

SUMMARY

The use of AI to optimise supply chain inventory management, as seen in Amazon’s operations, highlights the significant potential of robotic technology to transform traditional supply chain processes [23]. Through integration of AI Automated warehouse technology, warehouse operations have become more efficient, allowing for faster order fulfilment and efficient use of resources [23]. There are however still challenges to address, the future development of AI in supply chain management will allow businesses to match technological advancements and maintain a productive relationship between AI systems and human workers [23]. Overall, the integration of AI technologies into supply chain management presents substantial opportunities to streamline inventory processes and improve operational efficiency [23]. By adopting AI-driven innovations, companies can also enhance customer satisfaction by delivering better products and services more efficiently [23].

CONCLUSION

In conclusion, the National AI Plan released by the Federal Government in December of 2025 posits a variety of actions in order to address national concerns, maximise opportunity and navigate potential risks of AI implementation into industry. Particularly, Action Item Number 5 as a component of the holistic plan has faced the test of public debate. By analysing public opinion data, many conclusions can be made with respect to the change from mandatory guardrails to an ‘incremental’ approach, economic impacts, sustainability and safety impacts, as well as legal impacts and gaps in regulatory direction. The incremental approach adopted by the government in particular sits at the centre of discussion; with some figures praising an evolutionary approach, while others claim that safety and precaution should be regarded on the first instance rather than slow reform. Furthermore, the Plan places a strong emphasis on capturing economic opportunity, many of which have been seen as positive, however others fear that the economic emphasis is outweighing the safe direction.

Additionally, concerns have been raised in regards to sustainability of the labour force and education sector with the implementation of new AI software which current legislation does not capture or regulate effectively. In regard to environmental concerns, community voices desire further consideration of the impacts of AI investments (such as infrastructure like data centres) on the environment, particularly in regards to energy consumption and water usage. Finally, the legal aspect of the Plan is the most scrutinised area in the public debate. With concerns ranging from limited power and regulatory guidelines in new bodies, to issues of ineffective current legislation, reform backlog and speed to even mental health concerns for employees and the broader community. These areas serve as the key spheres of public life by which the National AI Plan, including Action item Number 5, directly impacts and raises concern of figures in the Australian community.

The implementation of AI can be seen through the use of automated AI warehousing equipment, particularly demonstrating the balance between technology and the work force. It is recommended that the Federal Government audit and review the public desire and concerns surrounding AI implementation in order to adequately capture, regulate and maximise outcomes from AI technologies within Australia. By doing so, Australia will be a model nation, competing globally with leading nations on safety, innovation and investment into the economy, work force, education sector and many more.

BIBLIOGRAPHY

Kassabgi, D (2025) TCA statement in response to the release of the Albanese Government’s National AI Plan, Tech Council of Australia. 2 December 2025, available at [https://techcouncil.com.au/newsroom/tca-statement-in-response-to-the-release-of-the-albanese-governments-national-ai-plan/](https://techcouncil.com.au/newsroom/tca-statement-in-response-to-the-release-of-the-albanese-governments-national-ai-plan/] [accessed 26 March 2026].
Johnson, R, Chitizadeh, A and Davis, J (2025) Australia’s National AI Plan released: experts respond, The University of Sydney. 2 December 2025, available at [https://www.sydney.edu.au/news-opinion/news/2025/12/02/australias-national-ai-plan-released-experts-respond.html](https://www.sydney.edu.au/news-opinion/news/2025/12/02/australias-national-ai-plan-released-experts-respond.html ] [accessed 26 March 2026].
Sheehy, L (2025) National AI Plan a sensible step forward for productivity and prosperity, Universities Australia. 2 December 2025, available at [https://universitiesaustralia.edu.au/media-item/national-ai-plan-a-sensible-step-forward-for-productivity-and-prosperity/](https://universitiesaustralia.edu.au/media-item/national-ai-plan-a-sensible-step-forward-for-productivity-and-prosperity ] [accessed 26 March 2026].
Evans, J (2025) Artificial intelligence to be managed through existing laws under National AI Plan, ABC News. 2 December 2025, available at [https://www.abc.net.au/news/2025-12-02/national-artificial-intelligence-plan-growth-existing-laws/106086474](https://www.abc.net.au/news/2025-12-02/national-artificial-intelligence-plan-growth-existing-laws/106086474?utm_source=chatgpt.com ] [accessed 26 March 2026].
Boyle, N, Moore, A and Kermond, C (2025) Australia’s National AI Plan: big ambitions, but light on details, White & Case. 8 December 2025, available at [https://www.whitecase.com/insight-alert/australias-national-ai-plan-big-ambitions-light-details](https://www.whitecase.com/insight-alert/australias-national-ai-plan-big-ambitions-light-details?utm_source=chatgpt.com ] [accessed 26 March 2026].
Australian Broadcasting Corporation (2025) Tuesday, December 02: The government has just dropped its National AI Plan, BTN. 2 December 2025, available at [https://search-informit-org.wwwproxy1.library.unsw.edu.au/doi/full/10.3316/TVNEWS.TSM202512020086](https://search-informit-org.wwwproxy1.library.unsw.edu.au/doi/full/10.3316/TVNEWS.TSM202512020086 ] [accessed 26 March 2026].
Goldenfein, J, Parker, C and Weatherall, K (2025) Australia’s National AI Plan has just been released. Who exactly will benefit?, The Conversation. 2 December 2025, available at [https://theconversation.com/australias-national-ai-plan-has-just-been-released-who-exactly-will-benefit-270981](https://theconversation.com/australias-national-ai-plan-has-just-been-released-who-exactly-will-benefit-270981 ] [accessed 26 March 2026].
Russ-Smith, J, Motsi-Omoijiade, I and Lazarus, M D (2025) Australia’s national plan says existing laws are enough to regulate AI. This is false hope, The Conversation. 16 December 2025, available at [https://theconversation.com/australias-national-plan-says-existing-laws-are-enough-to-regulate-ai-this-is-false-hope-271725](https://theconversation.com/australias-national-plan-says-existing-laws-are-enough-to-regulate-ai-this-is-false-hope-271725 ] [accessed 26 March 2026].
Australian Broadcasting Corporation (2025) Government reveals National AI Plan to ‘serve’ Australians, ABC TV. 2 December 2025, available at ABC television broadcast [accessed 26 March 2026].
Ramesh, R (2025) Australia abandons proposed mandatory AI rules in new plan, GovInfoSecurity. 2 December 2025, available at [https://www.govinfosecurity.com/blogs/australia-abandons-proposed-mandatory-ai-rules-in-new-plan-p-3986] (https://www.govinfosecurity.com/blogs/australia-abandons-proposed-mandatory-ai-rules-in-new-plan-p-3986] [accessed 26 March 2026].
Australia and New Zealand School of Government (2024) Public opinion data and policymaking during COVID-19 and beyond: insights from interviews across policy and politics, ANZSOG. 7 October 2024, available at [https://anzsog.edu.au/insights/public-opinion-data-and-policymaking-during-covid-19-and-beyond-insights-from-interviews-across-policy-and-politics](https://anzsog.edu.au/insights/public-opinion-data-and-policymaking-during-covid-19-and-beyond-insights-from-interviews-across-policy-and-politics ] [accessed 11 May 2026].
Department of Industry, Science and Resources (2025) National AI Plan, Australian Government. 2 December 2025, available at [https://www.industry.gov.au/publications/national-ai-plan](https://www.industry.gov.au/publications/national-ai-plan ] [accessed 11 May 2026].
Department of Industry, Science and Resources (2025) National AI Plan, Australian Government. December 2025, available at [https://www.industry.gov.au/sites/default/files/2025-12/national-ai-plan.pdf](https://www.industry.gov.au/sites/default/files/2025-12/national-ai-plan.pdf ] [accessed 11 May 2026].
Nguyen, D A (2026) AI in warehouse management: top use cases you need to know, SmartDev. 31 March 2026, available at [https://smartdev.com/ai-use-case-in-warehouse-management/#Future_Trends_of_AI_in_Warehouse_Management](https://smartdev.com/ai-use-case-in-warehouse-management/#Future_Trends_of_AI_in_Warehouse_Management ] [accessed 11 May 2026].
Head, K R (2025) Minds in crisis: how the AI revolution is impacting mental health, Journal of Mental Health & Clinical Psychology. 5 September 2025, available at [https://www.mentalhealthjournal.org/articles/minds-in-crisis-how-the-ai-revolution-is-impacting-mental-health.html](https://www.mentalhealthjournal.org/articles/minds-in-crisis-how-the-ai-revolution-is-impacting-mental-health.html ] [accessed 11 May 2026].
Butler, J (2025) Labor rejects standalone AI legislation with plan that offers to help unlock public and private data, The Guardian. 1 December 2025, available at [https://www.theguardian.com/australia-news/2025/dec/01/labor-rejects-standalone-ai-legislation-with-plan-that-offers-to-help-unlock-public-and-private-data](https://www.theguardian.com/australia-news/2025/dec/01/labor-rejects-standalone-ai-legislation-with-plan-that-offers-to-help-unlock-public-and-private-data ] [accessed 11 May 2026].
SellersCommerce (2026) Warehouse automation statistics (2026), SellersCommerce. 12 March 2026, available at [https://www.sellerscommerce.com/blog/warehouse-automation-statistics/](https://www.sellerscommerce.com/blog/warehouse-automation-statistics/] [accessed 12 May 2026].
Adamek, D (2026) AI automation in Australian warehousing: driving productivity and flow, [Ramco Systems](https://www.ramco.com?utm_source=chatgpt.com). 13 February 2026, available at [https://www.ramco.com/blog/logistics/ai-automation-australian-warehousing](https://www.ramco.com/blog/logistics/ai-automation-australian-warehousing ] [accessed 12 May 2026].
Körber (n.d.) AI and warehouse automation: the future of fulfillment centers, Körber Supply Chain. available at [https://www.koerber.com/en/insights-and-events/supply-chain-insights/ai-warehouse-automation](https://www.koerber.com/en/insights-and-events/supply-chain-insights/ai-warehouse-automation ] [accessed 12 May 2026].
SAP (2026) What is warehouse automation? [SAP] 26 January 2026, available at [https://www.sap.com/resources/warehouse-automation](https://www.sap.com/resources/warehouse-automation ] [accessed 12 May 2026].
Li, Z (2024) Review of application of AI in Amazon warehouse management, Advances in Economics, Management and Political Sciences, 144, pp. 1–8. doi: 10.54254/2754-1169/2024.GA18980. Available at [https://www.researchgate.net/publication/387711589_Review_of_Application_of_AI_in_Amazon_Warehouse_Management](https://www.researchgate.net/publication/387711589_Review_of_Application_of_AI_in_Amazon_Warehouse_Management ] [accessed 12 May 2026].