The Governance Challenge of AI Expertise

Automation is not replacing expertise. It is relocating it.

As the University of Sydney’s 2026 Skills Horizon report argues, organisations are gaining speed through AI and automation. Yet as more thinking shifts into systems, there is less opportunity for people to develop the depth those systems depend on. That is not a technology flaw. It is a design challenge.

The efficiency trap

Across fund operations and decision workflows, AI now assists with tasks that once required human interpretation. It flags anomalies, drafts documents, runs controls and even summarises decisions. These tools make work faster, but not necessarily smarter.

The Australian Financial Review recently described a growing group of Vibers: people who appear expert because AI fills the gaps in their knowledge. This “cognitive offloading” increases throughput but risks hollowing out capability. Teams perform efficiently when conditions are predictable, but struggle when questioned more deeply or when faced with the unexpected.

For organisations, this changes what capability means. It is not only about efficiency or oversight. It is about ensuring knowledge is retained, context is shared and reasoning remains visible. That requires structures that balance automation with deliberate learning and review; processes that test understanding, not just speed.

Expertise as infrastructure

At Wicklow, we view this as a design opportunity. Our operating model blends intelligent automation with human interpretation and context. Systems manage routine and repeatable functions such as registry, onboarding and AML/CTF processing. Human insight drives the rest: assessing exceptions, interpreting results and translating data into decisions.

This goes beyond control. It is about building an operational architecture that keeps knowledge live, where each process reinforces understanding rather than replacing it. It reflects the depth of expertise within Wicklow’s principals, shaped by decades of work in governance, fund operations and regulatory compliance.

Judgement as governance

When expertise moves into systems, governance becomes the safeguard that keeps it accountable. Automation does not remove responsibility. It redistributes it. The task for leaders is to ensure human judgement stays active: questioning patterns, testing logic and validating what automation produces.

Governance in this context is not a barrier to progress. It is how organisations keep thinking visible and capability growing alongside technology.