Australia is facing a sustained productivity slowdown that is constraining its economic potential. Over recent years, limited technological innovation, underutilisation of the workforce, regulatory complexity and reduced competitive pressures have combined to erode productivity growth.
This has direct consequences for real wages, living standards and the capacity of governments to invest in essential public services. Addressing this trend requires not only the adoption of new technologies such as artificial intelligence (AI) but also a re-examination of how work is organised through a coherent ‘‘System of Work.’
Historically, major gains in productivity have coincided with significant innovations, such as those that began the agricultural and industrial revolutions. These developments not only improved efficiency but also changed the nature of work, expanded participation in the economy and required new systems to manage greater complexity across labour, capital and governance.
AI represents the next major frontier. Unlike earlier revolutions that were driven by physical tools or infrastructure, AI affects decision-making, workflows and workforce dynamics in real time, adding new layers of organisational complexity.
Realising productivity gains from new technologies depends on both identification and effective application. The Productivity Commission’s 2025 bulletin highlights that while technologies may be available, their impact is often limited by slow or partial adoption. For example, sectors such as mining and construction have seen little change in operational technologies, while many professional services continue to rely on outdated software and heavy investment. Enterprise Resource Planning (ERP) systems have stifled innovation by being treated as major investments intended to enhance business capability. Yet in many cases, they have failed to deliver meaningful productivity returns. Instead of driving transformation, ongoing expenditure is absorbed by integration demands, locking organisations into a cycle of technical upkeep. As a result, firms continue to invest in ERP integration rather than in the business capabilities that generate real value.
Organisations frequently attempt to address capacity issues by increasing headcount, often through consultants, rather than addressing underlying productivity constraints. Where equipment, space or supply chains are already at capacity, additional labour provides minimal benefits and often increases costs. Even when innovative technologies are introduced, they are frequently applied on a limited scale or without fully utilising their capabilities.
AI is a clear example: while it is being trialled in professional sectors, its fragmented adoption has so far prevented its full potential from being realised.
Embedding AI within a coherent ‘System of Work’ is essential to support adoption at scale, align it with organisational objectives and ensure that operational and cultural adjustments are managed effectively.
The regulatory environment also presents challenges. With rules expanding in scope and complexity, many firms, particularly in construction, health and finance sectors struggle to navigate regulatory frameworks with confidence.
The Productivity Commission’s 2025 paper Housing construction productivity: can we fix it? noted that the decentralised and disorganised nature of regulation deters innovation because firms risk breaching requirements they do not fully understand. Consolidating standards and improving accessibility would provide greater clarity, lower compliance risks and create stronger incentives for firms to pursue productivity-enhancing innovations.
A further factor is declining business dynamism. Since the early 2000s, entry and exit rates of firms have slowed markedly. Established businesses benefit from scale, networks and regulatory familiarity, making it harder for new entrants to compete. This reduces competitive pressures and dampens incentives for innovation, limiting productivity growth.
A ‘System of Work’ in provides one approach to these challenges. By codifying roles, workflows and decision rights, it enables organisations to adapt to workforce changes such as hybrid models, contingent labour and rapid onboarding. It can also embed compliance within operational processes, reducing the burden of managing regulatory requirements. Importantly, it provides a framework for more effective deployment of capital: rather than fragmented investments in stand-alone tools or reactive measures, resources can be channelled into scalable and integrated systems that deliver measurable improvements.
In this context, AI should be seen not as a stand-alone solution but as a technology that realises its full value when embedded within a coherent ‘System of Work’. By aligning technology adoption with organisational strategy, overcoming legacy constraints and managing complexity at scale, such systems can help shift Australia’s productivity trajectory from stagnation to sustainable renewal.