The biggest productivity gains sit beyond agency boundaries, say APS digital leaders

The opportunity presented by AI is becoming too significant for agencies to remain on the sidelines. At the same time, leaders face growing pressure to improve productivity, modernise services, and maintain public trust.

In a Government Edge panel discussion, Peter O’Halloran, Chief Digital Officer at the Australian Digital Health Agency, Emily Hilder, First Assistant Secretary Digital Capability at the Department of Defence, Justin Keefe, First Assistant Secretary Digital and Security at the Department of the Prime Minister and Cabinet, and ADAPT Principal Research Analyst Peter Hind explored how agencies can pursue productivity gains without losing sight of governance, collaboration, and service outcomes.

Key takeaways

• Measure productivity through citizen and service outcomes rather than agency activity.
• Treat sensitivity and complexity as constraints to manage, not barriers to collaboration.
• Start with the problem to be solved before selecting technology or AI tools.
• Build trust through practical use cases that deliver visible and sustainable value.
• Create guardrails that encourage innovation while maintaining accountability and oversight.

Productivity should be measured where services are delivered

For Peter O’Halloran, productivity starts with the people receiving the service rather than the agency delivering it.

At the Australian Digital Health Agency, the focus is on helping clinicians access information faster, reduce duplication, and make decisions with greater confidence.

Peter pointed to examples such as sharing pathology and diagnostic imaging results across care settings, enabling clinicians to access existing test results rather than repeating them unnecessarily.

The result is faster treatment decisions, reduced costs, and better experiences for both clinicians and patients.

He argued that the biggest productivity gains often sit beyond agency boundaries.

Improving outcomes for frontline workers and citizens creates far greater value than focusing solely on internal efficiency measures.

The risk equation is changing

Emily Hilder challenged traditional assumptions about risk and AI adoption.

As AI capabilities mature, the opportunity presented by the technology is becoming increasingly difficult to ignore.

In some areas of government, the balance has shifted to the point where the risks associated with inaction deserve as much attention as the risks associated with adoption.

Emily highlighted the importance of identifying the problem before selecting a tool.

With hundreds of new AI capabilities entering the market, agencies can easily become distracted by technology choices.

The organisations achieving the greatest gains are those that clearly define the outcome they want to achieve before evaluating potential solutions.

She also highlighted the importance of enterprise guardrails that encourage innovation while preventing uncontrolled proliferation of tools, models, and duplicated effort across large organisations.

Collaboration begins with shared challenges

While agencies often focus on what makes them unique, the panel argued that common challenges create greater opportunities for collaboration.

Justin Keefe encouraged agencies to look beyond their own sectors for ideas, approaches, and lessons that can be adapted to government environments.

He argued that sensitivity, complexity, and risk are realities faced across the public sector and should be treated as constraints to manage rather than reasons to avoid sharing knowledge or working together.

Peter reinforced this point through his experience collaborating with health agencies across Australia and internationally.

While operating environments may differ, many of the underlying challenges around data, governance, service delivery, and technology adoption remain remarkably similar.

Agencies that actively learn from one another can accelerate progress while reducing duplication of effort.

Trust is earned through visible outcomes

The panel concluded that successful transformation depends on demonstrating value early and often.

Peter argued that agencies should prioritise initiatives capable of delivering clear and measurable benefits in the near term.

Early wins build confidence among employees, citizens, executives, and government leaders while creating support for more ambitious transformation programs.

Justin highlighted the role leaders play in maintaining curiosity and building workforce confidence during periods of rapid change.

As AI capabilities continue to evolve, organisations that invest in learning, experimentation, and capability development will be better positioned to realise long term productivity gains.

Across the discussion, a common theme emerged.

Technology may enable transformation, but trust is built when agencies consistently demonstrate that new approaches improve services, strengthen decision making, and deliver meaningful outcomes.