AI undermines the manufacturing workforce

As artificial intelligence (AI) reshapes industries across the globe, Australian manufacturing faces a critical crossroads. To remain competitive in increasingly advanced global markets, Australian businesses must urgently adopt smart, high-tech solutions, writes Graeme Sheather.

The emergence of AI as a dominant force is no longer a distant threat—it’s a present-day disruptor altering the foundation of the workforce and production.

A global shift demands national action

A new global order is taking shape, led by nations willing to invest in innovation, adopt disruptive technologies, and upskill their workforces. The question for Australia is clear: Do we have the political will and policy intelligence to stake a claim in this future?

A critical challenge remains: Australia lacks the career pathways, training infrastructure, and cross-industry resources necessary to develop a future-ready manufacturing workforce.

From legacy systems to smart factories

Too many manufacturing enterprises remain wedded to outdated legacy systems. Despite a few standout cases of businesses transitioning successfully to high-value, tech-driven models, most continue to lag. Without significant investment in AI and advanced technologies, these businesses risk obsolescence.

To survive, manufacturers must evolve into agile, scalable, and intelligent factories. This transformation includes adopting AI to streamline operations, enhance productivity, and reduce time-to-market. However, this transition comes with a stark reality: the traditional labour force will shrink as AI replaces hands-on roles once considered indispensable.

AI: The great displacer

AI technologies already replicate core human functions such as:

Comprehension and decision-making
Problem-solving and design
Image analysis and speech recognition
3D robotic movement
Real-time production and assembly

As AI takes over these functions, Manufacturing Resource Planning (MRPII) systems will identify which roles and processes are ripe for automation. Employees themselves often provide digital blueprints of their daily tasks, unknowingly paving the way for their own redundancy.

This raises significant concerns about the future of Australia’s labour force—and poses urgent questions for skill training institutions, TAFE systems, and national employment strategies. Where will displaced workers go, and how will they be supported?

Innovation deficit: A national risk

Australia ranks 23rd out of 132 nations on the Global Innovation Index (2024) though a disappointing 105th on Harvard’s Atlas of Economic Complexity. Australia is an innovation leader, ranking in the top 25 of the GII. This top quartile score in innovation capacity must continue to be addressed to secure a future in AI-driven manufacturing.

Businesses must pivot towards innovation by focusing on:

New markets and customer segments
Emerging technologies and skill sets
Energy, environmental, and regulatory pressures
AI-driven control systems, ERP platforms, and total quality management (TQM)

Importantly, Australia’s future innovation must include:

AI in Internet of Things (IoT) design and control
Human-AI interfaces for robotics
Hyper-scale computing systems for efficiency and scale

The FMIA Policy Directive

Australia’s current Future Made in Australia (FMIA) policy platform assumes the persistence of sub-assembly operations and labour-intensive workforces.

Under the recent release of the Department of Industry, Science and Resources, documentation there is a reference to the establishment of an AI Centre available to all businesses to assist them to plan and guide their establishment of AI control systems. I commend the industry to pursue the advice of this newly established Centre. Under the Net Zero Transformation Stream and the Economic Resilience and Security Stream components there should be a direct reference to the immediate impact of AI control systems upon the operation of manufacturing businesses.

To be relevant, projects must include AI-controlled manufacturing components.

The urgent need for AI toolkits and sovereign capacity (he following data is drawn from DSAi and the Australian Information Industry Association)

What SMEs need now is not just policy—but practical frameworks. Specifically:

AI implementation toolkits
Scalable models for advanced manufacturing
Support systems for retraining and redeploying workers
Innovation funding for R&D and process digitisation

Australia must break its historic pattern of underinvesting in manufacturing innovation. Sovereign capacity requires bold investment in smart processes, adaptive technologies, and globally competitive products.

Responsible AI implementation: Governance and ethics (The following data is drawn from Data Science and Ai Association of Australia)

Any business considering AI must weigh:

Do we fully understand the AI system and its risks?
Is it built with secure-by-design principles?
Have cyber supply chain risks been assessed?
How will it impact data privacy and compliance?
Who is accountable for outcomes and oversight?

A responsible AI strategy also includes proactive redundancy planning.

HRM redundancy plans: A moral and strategic necessity under succession planning

As workers document their roles for AI replication, they risk obsoleting themselves. A humane and forward-looking response is critical. Businesses must implement HRM redundancy plans that include:

Early retirement options
Upskilling or retraining
Reassignment to AI-related functions
Placement with supply chain partners

These actions demonstrate corporate integrity and strategic foresight.

Conclusion: The path forward

Australia’s manufacturing sector must choose either to embrace smart AI transformation now or face inevitable decline. This requires coordinated action across government, industry, and education.

Adopting AI isn’t just a technology upgrade—it’s a workforce revolution. Businesses must lead with vision, prepare with purpose, and act with urgency to build a competitive, resilient, and sovereign manufacturing future.

Picture: credit mikemacmarketing (CC-BY-2.0)

Graeme Sheather has recently retired as a Visiting Professor at the UTS Business School, working with Emeritus Professor Roy Green for 10 years. He has been Principal with Rodin Genoff & Associates since 2007. Together he and Genoff have formulated cutting edge business auditing and cluster and ecosystem mapping tools.