AI is reshaping work at speed. Australia’s competitiveness, productivity and prosperity depend on getting adoption right: confidently, responsibly and with employees at the centre.
How adoption succeeds
The adoption of AI is among the most consequential shifts in a generation for Australia’s businesses and their employees.
Implemented well, it has the potential to unlock significant gains in productivity, innovation and service delivery, while improving employee safety, supporting better customer outcomes, and advancing sectors such as health and care.
Realising these opportunities will require thoughtful implementation, organisational transformation, careful analysis, and strong partnerships between employers, employees and government. It will also involve deploying AI in ways that employees, regulators and policymakers can trust.
The opportunity is real, but so is the urgency
The global race to adopt AI is accelerating. The BCA Global Investment Competitiveness Index ranks Australia 21st out of 42 similar countries for business investment fundamentals, underscoring the need to use AI to strengthen competitiveness, attract investment and support high-quality jobs.
The benefits of AI will only be realised if businesses bring their workforces with them in its implementation and use. As AI adoption reshapes jobs and tasks, organisations will need to build workforce capability, redesign roles and workflows, support workforce-led adoption and provide confidence that AI is being used responsibly. Productivity gains will depend on employees having the skills, tools, operating environments and trust required to use AI effectively.
The foundations are there – but we must keep moving
Australia has a strong foundation for responsible AI adoption. As recognised in the Australian Government’s December 2025 National AI Plan, existing technology‑neutral frameworks already regulate many relevant risks. Workplace relations, health and safety, privacy and anti-discrimination laws are anchored in enduring principles: fair treatment, safe systems of work, lawful handling of personal information and genuine consultation about workplace change. These frameworks give businesses the flexibility to innovate while allowing targeted responses to risks.
But we cannot sit still. We have a responsibility to continually ensure that protections are effective, that people are equipped with the skills, capability and support needed to adapt to changing ways of working, and that we are transparent about what we do so we can all secure the benefits that this technology can deliver.
Getting it right:
Best practice AI adoption in the workplace
Best practice isn’t accidental. It demands executive leadership, deliberate deployment, human oversight and a workforce that is skilled, consulted and shares in the gains.
Implementation
Embed AI into enterprise-wide transformation and performance through clear Board accountability and C-suite ownership.
Empower workforce-led adoption and experimentation to embed practical integration into day-to-day work.
Define the business problems first and deploy AI where it can clearly improve outcomes.
Continuously monitor, review and refine AI systems to maintain performance and address emerging risks.
Skills & Capability
Build deep AI capability across the organisation, recognising that productivity gains depend on workforce adoption and effective use.
Treat AI capability and workforce design as continuously evolving, with skills, roles and talent models regularly updated to keep pace with changing tools, workflows and business needs.
Combine foundational AI learning (governance, risk and ethical use) with practical, on-the‑job application to embed AI into everyday workflows.
Provide AI tools for bottom-up experimentation and on-the-job learning.
Governance
Build on existing governance frameworks to adapt them for AI, with clear ownership, risk assessment and board-level accountability.
Treat data quality and security as foundational, ensuring representative data, lawful use and security controls are built in from the outset.
Keep humans in control, ensuring AI outputs are understood, reviewed and can be challenged or overridden where needed.
Implement safeguards and ongoing oversight so that AI systems operate reliably, consistently and lawfully, strengthening trust and reducing risk.
Workplace Relations
Engage employees collaboratively and with positive intent, focusing on improving implementation, understanding risk and supporting informed management decisions, while complying with applicable legal consultation obligations.
Provide focused transparency to help employees understand when AI significantly affects their work or employment outcomes, while protecting confidential business information, cybersecurity and legal privilege.
Keep human decision-makers accountable for significant employment decisions informed by AI, including recruitment, performance management, disciplinary action, redundancy selection and termination.
Support shared opportunity, recognising that AI-enabled productivity gains can flow through wages, bonuses, training, job creation, lower prices, better services, reinvestment and improved competitiveness.
Workplace relations and AI
Workplace relations principles
Australia’s workplace laws already apply to AI. Meaningful engagement, human accountability and shared opportunity are the standard; the task is applying them with judgment.
The principles set out below are intended to guide the workplace relations dimension of responsible AI adoption. They are designed to be applied flexibly across different tools, levels of impact and business contexts, rather than as a checklist for every tool or a static compliance framework. They are practical guidance, not uniform or mandatory workplace rules, and should be adapted to each organisation’s size, sector, workforce, risk profile, technology maturity and legal obligations.
The principles are framed affirmatively to define a clear standard for responsible workplace AI adoption, while recognising that organisations will be at different stages of maturity and may build capability over time. Innovation is often non-linear: it requires testing, learning, iteration and adjustment as technology, work practices and organisational needs evolve. Workplace relations settings should be understood in that context, supporting responsible adoption while preserving the flexibility needed for businesses and employees to adapt.
Employees are supported to use AI effectively and responsibly through training, guidance and clear direction on approved tools, data, privacy, confidentiality, accuracy, cybersecurity and human review.
The introduction of new technology, redesign of work, changes to workflows and operational decisions can benefit from employees’ expertise and ideas. Where practicable, those insights should be actively sought, genuinely considered, and
used to support effective implementation.
Engagement is collaborative and undertaken with positive intent, focused on improving implementation, understanding risk and supporting informed management decisions.
Employers comply with applicable legal consultation obligations. Beyond those
obligations, the timing and form of best practice engagement will vary by context.
In some cases, pilots and testing can provide useful opportunities for employee feedback and co-design, to improve the usability, effectiveness and adoption of AI tools and systems. In other cases, limited exploratory testing by appropriate internal teams may be needed to understand the use case, risks and likely workplace impacts before broader employee engagement can be meaningfully undertaken. Subject to applicable legal consultation requirements, the nature and extent of engagement should reflect the risk and impact of the AI use case.
AI may inform decisions, but employers, through human decision-makers, remain
accountable for significant employment outcomes, including recruitment, performance management, disciplinary action, redundancy selection and termination.
AI is used to improve work quality, remove unnecessary tasks, support safer work and help people focus on higher-value activity. It should not be implemented in a way that simply increases pace, pressure or workload without regard to safety,
capability and sustainability.
Where employees, health and safety or other representatives as applicable identify that an AI tool is increasing pace, pressure or workload in ways that affect safety or wellbeing, employers will review the implementation and respond to concerns within a reasonable timeframe and in accordance with applicable safety requirements and legal obligations.
High-impact uses of AI require stronger safeguards than low-risk productivity tools or ordinary software changes. AI used for purposes such as workplace surveillance, performance management, disciplinary processes or redundancy planning will require greater testing, human oversight and review than AI used for drafting, summarising or administrative support. Similarly, AI systems that are substantively AI-driven (self-iterative, with limited human review) may require greater controls and assurance than systems that merely have an AI component (e.g. AI in a secondary function, with human review in the loop).
Surveillance and monitoring should be limited to collecting and reviewing only the
data necessary for a legitimate business purpose, e.g. identifying physical safety risks, unsafe interactions with plant or equipment, fatigue indicators or security
issues before harm occurs. Best practice is to maintain clear workplace surveillance policies and update them where AI significantly changes the nature, purpose or intrusiveness of monitoring.
Employees are informed when AI significantly affects their work or employment outcomes, including the broad purpose for which it is used and, where relevant, how concerns about AI-informed decisions can be raised or reviewed through applicable processes. Transparency focuses on information people can act on, while protecting
commercial confidentiality, cybersecurity and legal privilege.
Employers treat AI as part of skills, leadership and workforce planning. Where
AI changes tasks or roles, employers should treat capability building as part of
implementation, supporting employees to build relevant skills and adapt to new ways of working where reasonable and practicable. The objective is adaptability, rather than static job preservation, with employers supporting employees to build skills that are portable and recognised beyond a single workplace where practicable.
AI-enabled productivity should benefit employees, customers, businesses and the broader economy. Where AI-enabled productivity gains are identifiable and relevant, employers should consider them when making remuneration, workforce capability
and investment decisions. Those gains may be reflected in wages, bonuses, training,
skills development, progression opportunities, access to higher value work, job creation, or reinvestment rather than through an automatic formula for distributing benefits.
Learn more about applying the principles in practice – visit our AI Hub to read more member business stories, and other reports, submissions and insights.
For us, successful AI adoption isn’t about the technology alone. It’s about aligning innovation with our mission using empathy, trust and long-term thinking to develop new ways of delivering high-quality care at scale. We’re not using AI to replace the human touch that defines our organisation, but as a powerful enabler to enhance it.
We view AI as a tool to enhance human expertise in hearing care, not replace it. Through better technology and clinical practice, AI supports improved hearing outcomes and helps us scale and grow our business.
Business is going to play a large role in the applications of AI that will enable both Australians and the global competitiveness of the Australian economy.
I firmly believe that our people are central to this journey. By investing in everyone’s capability, we can ensure each person has the opportunity to build a rich, rewarding, and sustainable career.
From improving reliability to supporting faster, better-informed decisions, these are just some of the ways AI‑supported tools are helping our teams get more value from our assets.
From evidence to action
Australia’s AI moment is here. The technology is delivering commercial value. The business community has enough evidence to move beyond experimentation.
The regulatory environment provides strong foundations for safe and responsible AI adoption and implementation, and whilst it may continue to evolve, its direction is clear enough to enable long-term planning and investment.
