There has been much written about AI — mainly good, well-informed articles. It is set to reshape the public service over the next decade. 

So, what skills should a current public servant focus on to get that next promotion? What should universities focus on to meet the needs of the public sector and industry? What should those starting their university studies aim for?

I spent a considerable amount of time as a change manager in developing countries, where change was challenging and scary, as people lost their jobs and new ones were created. In these situations, I always tried to inform the people affected by the change about the day-to-day impacts or the likely impacts on them and their tasks. 

I left the big-picture stuff, which was nice but not informative, to the head office, which is internally focused and has very important committees. My concern, my brief, was about those affected — about their retaining, job creation and communications.

Here is my attempt at qualifying the likely changes in our public sector, down to the grass roots, where some jobs will decline significantly in number and new jobs will emerge. This includes a list of 10 public sector jobs likely to decline and 10 new job opportunities. 

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There is also a department-by-department timeline of how these changes might unfold across the APS. Then, the likely changes in some core functions with an expected AI checklist. 

APS jobs likely to go into decline

Data entry/routine clerical staff

Basic customer service/front-line inquiry operators

Document-processing/mailroom/scanning staff

Simple compliance/regulation checking roles

Routine report writing and template-based communications

Basic legal drafting (standardised contracts, precedents)

Proofreading/editing of standard content

Routine translation/interpretation

Scheduling/low-level administrative assistants

Archival/records management of low complexity

New and growing APS job opportunities 

AI policy & strategy advisors

Data governance officers/data stewardship roles

AI governance/responsible AI specialists

Machine learning/AI engineers & developers

Automation/workflow optimisation experts

AI ethics/risk & compliance officers

User experience (UX) & human — machine interface designers

AI training, education & change management specialists

AI monitoring, audit & assurance officers

Digital inclusion /AI literacy & citizen engagement roles

Projected timeline of AI-driven change 

The following outlines a rough timeline for when jobs might be expected to decline or emerge, and which departments are likely to experience changes first.

Now-2025: Foundation setting, pilot programs, policy frameworks in place. Initial declines in clerical and customer service roles. New AI policy and governance roles are emerging.

2025-2028: Scaling up automation and internal tools. Decline in routine admin and compliance. Growth in AI audit, data stewardship, UX design, and change management.

2028-2032: Broader adoption of AI for citizen-facing services. Routine tasks are mostly automated — rapid growth in oversight and ethics roles.

2030 and beyond: AI deeply embedded in APS operations. Legacy clerical jobs are mostly gone. Workforce focused on ethics, governance, technical literacy, and foresight.

Department-by-department impacts

Services Australia

Decline: Clerical staff processing claims, routine call-centre roles.

Rise: AI case-management support specialists, ethics/compliance officers, digital experience designers.

By 2030: Most routine claims automated, humans focus on complex exceptions.

Home Affairs

Decline: Visa clerks processing straightforward applications, document verification staff.

Rise: AI risk-profiling analysts, biometric AI auditors, legal/ethical reviewers.

By 2030: Automated visa assessments common, human oversight ensures fairness.

Australian Taxation Office (ATO)

Decline: Staff doing low-level auditing, basic call-centre staff.

Rise: AI audit overseers, fraud detection specialists, forensic data analysts.

By 2030: Routine audits automated; humans focus on complex tax avoidance cases.

Health and Aged Care (Admin)

Decline: Records clerks, schedulers, claims support staff.

Rise: AI health policy analysts, ethics advisors, health tech integration officers.

By 2030: Records and billing automated, staff focus on policy and ethics.

Defence

Decline: Clerical logistics roles, some intelligence analysis tasks.

Rise: AI defence strategy advisors, cybersecurity specialists, AI warfare ethics officers.

By 2030: AI embedded in intelligence/logistics, humans oversee ethical decisions.

Education

Decline: Routine assessment/marking support staff, clerical records staff.

Rise: AI curriculum designers, digital inclusion officers, data specialists.

By 2030: AI common in assessments, staff focus on equity and the digital divide.

Finance & Treasury

Decline: Routine economic data compilers, report drafters.

Rise: AI economic modellers, policy foresight specialists, risk analysts.

By 2030: AI drives forecasting; humans manage trade-offs and political context.

Climate Change, Energy, Environment and Water

Decline: Manual data entry, satellite image processing clerks.

Rise: AI climate modelling officers, environmental monitoring auditors.

By 2030: AI predictive models standard; humans manage transparency and communication.

Employment and Workplace Relations

Decline: Clerical staff tracking employment data, routine evaluators.

Rise: AI labour market analysts, workforce transition officers, policy advisors.

By 2030: AI predicts shifts, humans help displaced workers reskill.

Australian Bureau of Statistics (ABS)

Decline: Manual data coders, survey processors.

Rise: AI survey integrity specialists, synthetic data governance officers.

By 2030: Data collection automated, staff focus on bias control and communication.

AI Impacts on core APS functions

Cabinet briefs: AI will accelerate research and produce initial draft briefs, but human officers will remain central to political framing and judgment. Roles will shift toward oversight, verification, and strategic framing. New listed roles include AI briefing, QA officers, and tool stewards.

Senate estimates preparation: AI will automate collation, indexing, and draft responses to predictable questions. Humans will still control disclosure decisions, manage privilege, and craft politically sensitive answers. New roles include disclosure & risk officers and audit/traceability specialists.

Writing legislation: AI tools can draft clauses, check consistency, and search precedents, but final legal drafting and constitutional checks remain human-led. Junior drafters will supervise AI outputs. New roles include legal-veracity auditors and AI integration leads in drafting offices.

And, finally, here is an example of what a new checklist might look like, which is a bit like current checklists with some changes in language but still with the same outcome of accountability, quality and high risk management.

AI-assisted document preparation: Example of a manager checklist

Was the AI tool used an approved, registered model?

Are all sources cited and traceable?

Has a human QA officer reviewed every factual claim?

For cabinet briefs: Has political framing been human-authored?

For Senate estimates: Has a disclosure & risk officer cleared sensitive information?

For legislation: Has legal counsel reviewed all AI-generated clauses?

Are prompts, outputs, and model versions logged for audit?

Have relevant staff received AI safety and verification training?

Final human sign-off completed by the responsible officer?

It is mainly predictable and not as scary as many have proposed.