Australia's AI Future: Most Jobs Will Change. The Question Is Whether We Change With Them.

I believe the majority of jobs in Australia will be materially changed by artificial intelligence before the end of this decade. Not necessarily eliminated. Changed.

The accountant, engineer, teacher, lawyer, nurse, builder, salesperson and business owner will all still exist in 2030. But the tools they use, the tasks they perform and the skills that make them valuable will be different. Some roles will disappear. New ones will appear. Most will become a combination of human judgement and machine capability.

That shift will create a new divide in the Australian economy, between people and organisations that learn to work with these systems and those that do not. This is why Australia must stop treating artificial intelligence as another technology trend. It is an economic transition, and we are already inside it.

At a glance

• Artificial intelligence changes tasks before it replaces jobs. When 30 to 50 per cent of a role’s repetitive work is automated, the economics of the role change.
• Globally, 86 per cent of major employers expect artificial intelligence and information processing to transform their business by 2030, and expect 39 per cent of workers’ core skills to change.
• Australian business adoption has risen from 1 per cent to 12 per cent in three years, but remains uneven across industries. Most of the transition is still ahead.
• The greatest hidden risk is the loss of entry-level work that trains future experts.
• Small Australian businesses stand to gain the most, but only if they build integrated operating systems rather than collecting disconnected tools.
• National success will depend on capability, not consumption: Australian skills, companies and intellectual property.

Artificial intelligence changes tasks before it replaces jobs

Much of the public conversation revolves around one question: will artificial intelligence take my job? I think that is the wrong question, because a job is not a single activity. It is a bundle of tasks.

Role	Tasks most exposed to automation	Tasks where human value rises
Accountant	Reconciliation, data entry, document preparation	Advising clients, interpreting complex situations, judgement
Salesperson	Prospect research, proposal drafting, follow-up	Negotiation, relationships, understanding client needs
Doctor	Documentation, information gathering, literature review	Diagnosis, communication, clinical decisions
Tradesperson	Quoting, scheduling, ordering, customer administration	Skilled physical work, problem solving on site

Artificial intelligence does not need to perform every one of these tasks to change the economics of a role. If it takes over 30, 40 or 50 per cent of the repetitive work, the role changes, team structures change, the cost of delivering the service changes, and customer expectations change with it.

Jobs and Skills Australia has found that generative artificial intelligence is more likely to augment Australian jobs than replace them, and expects new specialisations, hybrid roles and new combinations of skills to emerge as adoption deepens. Source: Jobs and Skills Australia

That distinction matters. The biggest effect of artificial intelligence may not be millions of jobs disappearing overnight. It may be millions of jobs becoming different.

By 2030, very few industries will be untouched

The World Economic Forum surveyed more than 1,000 major employers representing over 14 million workers. Eighty-six per cent expect artificial intelligence and information processing technologies to transform their business by 2030. They also expect 39 per cent of workers’ core skills to change in that period. Source: World Economic Forum Future of Jobs Report 2025

This change will not stay inside technology companies. Professional services, financial services, retail, healthcare, education, construction, manufacturing, transport, agriculture and government will all be affected. Even in industries built on physical work, where the core task remains human, the surrounding work of planning, scheduling, quoting, procurement, diagnostics and customer communication can be automated or improved. Robotics will extend that reach further.

Industries will move at different speeds. But it is difficult to see any major Australian industry reaching 2030 without artificial intelligence changing at least part of how its people work.

This is not the end of work

Technology removes some types of work and creates others. The World Economic Forum estimates that broader economic and technological change could create 170 million jobs globally by 2030 while displacing 92 million, a net gain of 78 million roles. These are projections, not guarantees, but they illustrate a critical point: economic transformation destroys and creates jobs at the same time.

Many of the new jobs will not carry “artificial intelligence” in the title. They will include people who connect technology with specific industries, specialists who supervise automated processes, governance and assurance roles, data and cybersecurity professionals, automation specialists and new engineering disciplines. Entirely new businesses will emerge.

The challenge is that a new job appearing somewhere in the economy does not automatically help the person whose current job has changed. That is where adaptation becomes decisive.

The real divide: those who adapt and those who do not

Artificial intelligence may not replace an accountant. But an accountant who uses it well may produce high-quality work far faster than one who does not. The same applies to marketers, software developers and business owners. A competitor that automates administration, follow-up, customer support and parts of marketing can run a much leaner, more responsive business.

That changes competition. The risk is broader than direct replacement. A profession can survive while the economic value of its current way of working falls.

This is why the reassurance that “artificial intelligence will not replace you” can create false comfort. The more accurate message is this: artificial intelligence may not replace you, but it is likely to change your job, and your ability to adapt will increasingly shape your opportunities.

Jobs and Skills Australia identifies digital and artificial intelligence capability as increasingly important across the workforce, alongside the continuing value of human skills. Source: Jobs and Skills Australia

The hidden risk: losing the path from beginner to expert

One consequence of this transition deserves far more attention than it receives.

Artificial intelligence is already strong at many tasks traditionally given to junior employees: first drafts, research, basic analysis, reconciliation, document preparation, routine correspondence, data entry and simple coding. These tasks can look inefficient, but they are how people learn. A junior accountant learns by working through records. A graduate engineer learns by checking calculations. A young lawyer learns by researching cases.

Remove too much junior work and a serious question follows: where will the next generation of senior professionals come from? Experience is built through investigation, mistakes, supervision and responsibility. It cannot be created by handing a graduate polished answers.

Organisations should not simply automate junior work away. They need to redesign the path from beginner to expert, through supervised projects, structured practical experience and new forms of mentoring. Otherwise, today’s productivity gain becomes tomorrow’s capability shortage.

Australian businesses are early in the transition

The Australian Bureau of Statistics reported that 12 per cent of Australian businesses used artificial intelligence in 2024 to 2025, up from 1 per cent in 2021 to 2022. Source: Australian Bureau of Statistics

Industry	Businesses using artificial intelligence, 2024 to 2025
Information, media and telecommunications	38 per cent
Professional, scientific and technical services	24 per cent
Financial and insurance services	24 per cent
Construction	6 per cent
Agriculture, forestry and fishing	3 per cent
Transport, postal and warehousing	1 per cent

Two conclusions follow. The transition is real, and most of it is still ahead. Businesses that build capability now have time to learn before artificial intelligence becomes part of the normal competitive baseline in their industry.

Small businesses stand to gain the most

For decades, scale gave large companies a decisive advantage. They could employ analysts, marketers, administrators, customer support teams and software specialists. A small business owner often performed several of those roles personally.

Artificial intelligence can change that equation. A five-person business may gain capabilities that once required fifteen or twenty people. A trades business can automate enquiries, quoting and follow-up. An accounting practice can reduce repetitive processing and spend more time advising clients. A healthcare or disability provider can streamline administration and keep people focused on care. A regional company can serve customers well beyond its traditional area.

That is real economic leverage, but only if the technology is implemented well.

Build an operating system, not a tool collection

One of the most common mistakes I see is businesses buying disconnected applications: a chatbot, another customer relationship management system, a marketing platform, an automation tool, a customer service product. Staff then spend their day moving information between systems. That is not transformation. It is digital clutter.

The objective should be an integrated operating environment in which information moves through the organisation with minimal manual handling, automation removes friction, and human judgement is concentrated where it creates the most value.

A practical sequence works for most organisations:

1. Start with the business problem, not the software.
2. Measure the current cost of the process in time, errors and lost revenue.
3. Redesign the process before automating it.
4. Integrate new tools into a single operating environment.
5. Measure the full result, including quality and customer outcomes.
6. Scale what works and stop what does not.

The measure of success is not how much artificial intelligence a company uses. It is whether the company works better.

Australia must build capability, not dependency

There is also a national question. Australia could become a sophisticated consumer of foreign technology while losing the ability to understand the systems it depends on. That is not good enough.

Sovereignty in artificial intelligence does not mean Australia must build everything itself. It means Australia must retain meaningful choices. That requires engineers who understand these systems, cybersecurity and data expertise, Australian technology companies creating intellectual property, and leaders capable of challenging technology suppliers. It also requires the ability to change providers, protect sensitive information and maintain essential services when circumstances change.

A server located in Australia does not create sovereignty on its own. Capability does. Knowledge does. People do.

National policy must reach the workplace

Australia’s National AI Plan is built around three goals: capturing the opportunity, spreading the benefits and keeping Australians safe. Source: Department of Industry, Science and Resources

The test is whether those goals become everyday reality. A national strategy succeeds when a small business can find affordable, practical help; when a worker can access training linked to a real career; when an Australian startup can commercialise its intellectual property; when companies can find the technical talent they need; and when public institutions can use advanced systems without losing accountability.

Infrastructure, skills, commercialisation, education and business adoption cannot be managed as separate policy areas. They are one system and must be designed as one.

A note on responsibility

I lead Sharktech Global, and I have a commercial interest in technology adoption. That makes clarity more important, not less. The objective should never be to insert artificial intelligence into every possible process. The objective is measurable improvement. Sometimes the answer is artificial intelligence. Sometimes it is better data, better integration or a redesigned process.

Through Sharktech Global and our consultancy arm, Divine Lab Worx, this is how we approach the problem: technology, business process, commercial viability, people and governance designed together. Deploying software is easy. Building an organisation capable of using it well is much harder, and that is where the real value is created.

What leaders should do next

• Workers should build practical fluency with the tools changing their field, and deepen the industry knowledge and judgement that machines cannot supply.
• Business owners should map their processes, measure where time is lost and build an integrated operating environment before buying more tools.
• Employers and educators should redesign entry-level pathways so young Australians still gain supervised, real-world experience.
• Government should measure the National AI Plan by workplace outcomes, such as small business adoption, career transitions and Australian intellectual property created, rather than by announcements.

An Australia strengthened by artificial intelligence

When I talk about rebuilding the soul of Australia, I am not arguing that we should slow technological progress. I believe Australia should move faster, with purpose. The measure of success should be whether Australians become more capable because of these systems: whether a small business can compete with a larger one, whether a young person can still build a meaningful career, and whether Australian companies create intellectual property rather than simply consuming it.

We can wait for this transition to happen to us, or we can build the skills, companies, infrastructure and institutions required to shape it. My vision is not an Australia protected from artificial intelligence. It is an Australia strengthened by it.

More from this series

• What Norway’s sovereign wealth fund teaches Australia
• Australia already has a sovereign wealth fund. It needs a clearer job
• Turning Australia’s mineral wealth into national wealth
• Preparing Australians for the artificial intelligence transition
• Governance is what makes a sovereign wealth fund last

About the author

Dainu Devis is an Australian emerging technology CEO, technologist and business and economic strategist. As Chief Executive Officer of Sharktech Global and Divine Lab Worx, he brings a decade of international business consulting and political strategy advisory experience to building technology businesses. His strength is concurrent product and process design, bringing the product, delivery processes and route to market together from the start.