Australian firms scale AI as trust becomes the gate

By Elena Vasquez

Fewer than half of the 25 Australian organisations Cisco studied were very or extremely confident their foundations could support the next stage of AI adoption.

Cisco published the report on November 10, 2026. Separate University of Melbourne and KPMG research cited by Cisco found that 50% of Australians use AI regularly, while only 30% believe its benefits outweigh its risks.

The gap between regular use and confidence sets the context. Cisco argues that trust determines how far Australian businesses will let AI operate. Its research draws on consultations with 25 organisations, including AustralianSuper, Flight Centre Travel Group, Culture Amp and Funlab.

The most intensive users were not waiting for another technical advance. They focused on proving reliability, protecting data and keeping people responsible for final decisions, Cisco found.

What builds trust before AI scales?

Cisco’s evidence-first account puts measurable results ahead of management direction alone. Respondents said trust and AI adoption strengthen each other over time. Successful use encourages wider acceptance, which then supports broader deployment.

Chris Locke, Chief Technology Officer, Flight Centre Travel Group, said:

“Training, usage, and successful outcomes start to build a flywheel of trust. By training your people, getting them to use AI, and seeing good outcomes, you create the confidence for them to keep going.”

At Culture Amp, managers tracked both productivity and accuracy when staff used AI tools. Their measurements showed people using the tools were three times faster, while error rates stayed exactly the same.

Paul Keen, Vice President of Engineering, Culture Amp, said:

“We could see that the people using the tools were three times faster, while error rates were exactly the same. That gave us statistical evidence to back up the benefits, and that built trust around the adoption of AI.”

Culture Amp did not treat the speed gain as a standalone claim. It used the unchanged error rate to supply statistical evidence for broader adoption, according to Cisco.

Funlab added a peer network. Its “AI Super Squad” brings together representatives from across the business. They meet every four weeks to compare experiences, discuss concerns and share lessons with colleagues, Cisco said. Cisco highlights the arrangement as part of the trust-building process.

What does calibrated trust mean?

Cisco found that the most advanced users were not seeking unrestricted faith in AI. The report describes “calibrated trust,” where the level of reliance matches the risk attached to each task.

That approach changes daily behaviour. Staff need to know when an AI-generated answer is sufficient, when it needs checking and when a person should take over. Cisco says this shifts attention away from simple adoption metrics such as log-ins and towards signs that users are applying judgement.

Sarah Carney, Head of Artificial Intelligence, AustralianSuper, said:

“Blindly trusting these systems and their outputs is a huge risk. Trust has to include knowing when to challenge, when to check and when judgement still needs to sit with a person.”

Cisco identifies two practical measures for that judgement. The first is whether employees override or challenge AI outputs when necessary. The second is whether staff use approved tools instead of unsanctioned alternatives. Cisco says those alternatives can introduce governance and data risks.

Cisco’s framework treats a login count as an incomplete signal. An override can show that a worker knows when the system has reached its limit. The study treats both behaviours as evidence about whether deployment remains governable.

Can autonomy outrun readiness?

Cisco found that ambition for more autonomous AI is moving faster than organisational readiness. Fewer than half of respondents were very or extremely confident their foundations could support the next stage of adoption.

The control problem changes as AI moves from producing drafts and recommendations to taking actions on behalf of users. Cisco says the test is no longer only whether an output is correct. Businesses also need to know whether a system will remain within defined limits.

Respondents identified privacy and security breaches as the biggest threats to trust in AI. Legacy infrastructure ranked among the top five risks. More than half said they needed to upgrade infrastructure to support newer forms of AI.

Devesh Maheshwari, Chief Technology Officer, Lendi Group, put the relationship directly:

“Trust determines the autonomy you are prepared to give AI. The aim is bounded autonomy, where the agent can act on your behalf but cannot go beyond the boundaries you have established.”

Cisco’s findings link infrastructure work to trust, not merely technical capacity. The study pairs that work with defined boundaries and a route for human intervention before systems gain more independence.

Why are controls lagging?

Cisco connected the autonomy gap to a broader control shortfall in Australian organisations. Its separate Relentless Defence Report found that only 36% of Australian respondents apply consistent controls to AI agents and non-human identities.

The 36% figure comes from the separate defence report, not the 25-organisation study. Cisco uses it to frame a specific problem: businesses are preparing to delegate more work before they have consistent controls over the systems doing that work.

Cisco says organisations need stronger technical controls before granting AI systems more independence. It recommends monitoring and governance arrangements that can operate at machine speed as AI agents take on more tasks.

Stefan Leitl, Vice President and General Manager, Cisco Australia and New Zealand, said:

“Trust isn't a hurdle that the organisations in the Cisco study clear once. What we've learned from Australia's AI leaders in the study is that trust is an essential foundation for the change AI will bring.”

“They start where AI's value can be proven, make their safeguards visible and expand as the evidence builds. That's how they're turning AI investment into real returns. It's a playbook that travels well beyond Australia, for any business looking to build new services and business models on AI.”

Leitl’s sequence starts with a use case that can prove value. It then makes safeguards visible and allows evidence from early use to support wider deployment. Cisco presents that pattern as a route from investment to returns.

Carl Solder, Chief Technology Officer, Cisco Australia and New Zealand, said:

“The leaders in our research aren't scaling AI first. They're scaling trust. That means data they can stand behind, clear boundaries for every agent and people who know when to step in. Built into the network and security underneath, control stops being the brake and becomes the permission to move faster.”

The next threshold is operational. Before granting wider autonomy, companies will need monitoring at machine speed and a clear path for human intervention. Cisco’s research says expansion follows where value stays measurable, safeguards remain visible and infrastructure can support newer AI systems.