Legacy technology isn't just slowing government down—it's costing people their best work. Here's what public sector leaders must do before time runs out.
Eunice Lim
Director, Corporate Affairs, APJ
Workday
In February, the Digital Transformation Agency (DTA) reported a significant shift in Australia’s $5.9 billion digital portfolio: projects reporting a medium-high delivery confidence now account for almost 70% of the total budget.
This is a marked departure from previous years, where large-scale transformation programs were frequently mired in low-confidence projections and delivery delays.
This improvement is the direct result of a strategic pivot toward right-sized governance. By abandoning monolithic delivery models in favor of staged releases and modular tranches, agencies have effectively de-risked their most complex investments.
The timing is critical. With the New Cloud Policy taking effect on 1 July 2026, the transition from legacy systems to innovation-ready architecture is both a compliance and operational necessity.
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The real challenge now lies in execution: will public sector leaders apply these hard-won lessons to embed secure, scalable, and AI-powered infrastructure today, or wait until the burden of legacy tech erodes their ability to serve the Australian public altogether?
When we think about legacy systems, there is a temptation to focus solely on the technical debt: the constraints on integration, scalability and data integrity that undermines modern operating models. But for most public sector organisations, the biggest cost is human.
Workday research found this is particularly true when AI is 'bolted on' to outdated IT systems. For every 10 hours saved through AI, employees are losing nearly four hours to rework, manual verification, and bridging the gaps between disconnected systems.
High performers expect intuitive, modern tools that allow them to focus on meaningful work. When they are forced to spend their day double-checking outputs and creating manual workarounds, engagement drops and frustration rises.
Together, these forces create a compounding effect. Technical debt slows down innovation. Time spent on AI rework diminishes the employee experience. And the New Cloud Policy is driving change in how government agencies architect and govern their digital assets.
The weight of legacy systems isn't unique to the public sector, though the inertia within the APS can make the challenge feel more acute.
By the time emerging technologies are put into play, they are already obsolete.
Regardless of sector, the goal is the same: moving from a maintenance mindset to an operating model that is adaptive, resilient, and capable of supporting AI—and the people that manage it—well into the future.
Here are three critical shifts that we can learn from the DTA's success to move the needle when it comes to improving delivery confidence and avoiding productivity lags.
Traditionally, digital transformation has been delivered through major, multi-year programs—complex, high-risk initiatives to replace or overhaul core systems in one mammoth step.
This model is too slow, too rigid and too disconnected from how value is actually realised. By the time emerging technologies are put into play, they are already obsolete.
Instead, leading organisations are moving away from projects and towards platforms: modular, configurable environments that can be continuously improved, extended and scaled without major change programs.
Rather than waiting years for a single go-live moment, they deliver value incrementally—releasing capabilities in smaller, manageable tranches that reduce risk and demonstrate impact early.
We can see this shift reflected in the direction set by the DTA, which is actively encouraging agencies to move away from large, monolithic programs in favour of right-sized delivery.
Smaller, sequential tranches enable tighter governance, clearer accountability and more active risk management, improving the likelihood of success.
This is not just a public sector response. It reflects a broader realisation across industries: transformation is not an event to be delivered, but a capability that can be built.
As organisations modernise their platforms, attention is turning to how AI is embedded into core business processes.
As 2025's 'proof-of-concept graveyard' showed, value will not come from standalone AI tools, but from AI integrated directly into enterprise systems.
AI agents are now working alongside humans, enabling more adaptive workflows, acting autonomously and reshaping how work is structured.
The opportunity is to move from systems that simply record transactions to environments where AI actively performs and optimises work in real time.
Here, trust is foundational. AI needs to operate within defined processes, supported by enterprise data, security frameworks and compliance guardrails.
This is critical, because AI introduces a fundamentally different mode of reasoning. Its probabilistic nature enables powerful insights, predictions and automation.
Workday research shows that for Gen Z, the decision to stay or go isn't just about pay; it’s about employability.
But it must be anchored to deterministic, trust-critical systems that ensure accuracy, consistency and accountability.
In other words, AI must be tightly integrated with business context, linked to and guarded by organisation-specific rules, data, governance and controls.
This is how AI can be used to build more intelligent and efficient operating models that retain the trust and confidence of employees, customers, shareholders and regulators.
The APS and private sector alike are currently navigating the most diverse multigenerational workforce in history.
Workday research shows that for Gen Z, the decision to stay or go isn't just about pay; it’s about employability. In Australia, 41% of Gen Z employees factor long-term career goals into their daily job satisfaction – significantly higher than previous generations.
When archaic systems force these digital natives into 'shadow work' (manual data entry, reconciling disconnected spreadsheets, or navigating clunky UX), it creates a 'talent tax' that kills their sense of progression.
There are two ways that leaders can manage this:
By removing the constraints of legacy tech, agencies can reimagine how work actually gets done.
Ultimately, reinvesting in people means providing an innovation-ready environment. We must move from an on-premise culture that rewards tenure, to a platform-based culture that rewards impact.
By removing the friction of legacy tech, we are improving productivity today and giving employees permission to do the mission-driven work they signed up for.
The DTA’s latest findings and the new Cloud Policy offers Australian leaders a rare opportunity to exit the 'legacy trap' and strip away the complexity that prevents people across the public sector from doing their best work.
Digital transformation has never been about a fixed destination, but in the public sector the journey has never been more important.
By removing the constraints of legacy tech, agencies can reimagine how work actually gets done. This shift allows the APS to return its focus to its true mission: serving the Australian community with agility, integrity, and purpose.
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