Key Takeaways
- 60 % of Australian workers have personally spotted an AI mistake at work, yet only 14 % fully trust AI‑generated outputs.
- More than one in five say employees are discouraged from challenging AI recommendations, eroding a vital safety net.
- Almost half of the most significant AI errors reported led to financial, compliance, or reputational harm—not just minor inconveniences.
- 94 % of respondents believe AI should not make decisions affecting employees or customers without limits or human oversight.
- While 92 % agree AI agents need rules‑based guardrails, less than half (48 %) say their organisation has actually defined them.
- Workers prefer AI to be limited to low‑risk decisions or to always require human review/approval for higher‑impact choices.
Survey Reveals Widespread AI Errors and Low Trust
Sixty percent of Australian workers have personally identified an error made by an artificial intelligence (AI) tool at work, according to new research from Appian. The study, which surveyed 500 employees in Q3 2026, found that while AI mistakes are commonly noticed, confidence in the technology remains fragile: only 14 % said they fully trust the AI‑generated outputs used within their organisation. As Charlie Hutchinson, SVP Asia‑Pacific and Japan at Appian, observed, “It is hardly surprising that complete trust in AI is so low when workers are catching it making mistakes and are discouraged from questioning its outputs.” This gap between experience and trust sets the stage for broader organisational challenges.
Impact of AI Mistakes on Business Operations
The research shows that AI errors are not merely technical glitches; they have tangible consequences. One in five workers said the most significant AI error they encountered caused a customer‑service issue, while 13 % reported operational disruption. Almost half of respondents indicated that the most significant AI error they experienced resulted in consequences beyond minor inconvenience, including financial, compliance, or reputational impact. Hutchinson warned, “Every visible error gives workers another reason to question whether AI should be trusted with more consequential work,” underscoring how repeated mistakes can erode confidence and increase resistance to AI adoption.
Barriers to Questioning AI Recommendations
A troubling cultural factor emerged: more than one in five respondents said employees in their organisation are discouraged from challenging AI’s recommendations or decisions. This discouragement removes a critical human safeguard, as workers often serve as the last line of defence before an incorrect output reaches a customer or influences a business decision. Hutchinson noted, “If they are discouraged from speaking up, organisations remove one of their most important safeguards.” When staff feel unable to question AI, they may either avoid the technology altogether or blindly trust flawed outputs, both of which undermine the productivity gains AI promises.
Calls for Human Oversight and Governance
Reflecting the desire for accountability, 94 % of workers said AI should not be allowed to make decisions affecting employees or customers without limits or human oversight. This sentiment aligns with Hutchinson’s advice that AI must operate within the same governance processes and controls as the rest of the business, with clear mechanisms for people to step in before a significant error occurs. By embedding AI within governed workflows—defining what it can access, the rules it must follow, and when a decision must be handed to a person—organisations can preserve accountability while still capturing AI’s efficiency benefits.
Comparative Trust in Senior Management vs AI
The study also juxtaposed trust in AI with trust in senior leadership. While only 29 % of respondents said they trust AI more than senior managers, a majority — 52 % — placed greater trust in senior leaders. This disparity highlights that, despite AI’s promise, workers still look to human judgment for critical decisions. Hutchinson’s comment that “senior management remains more trusted than AI” reinforces the notion that technology must earn its place alongside, not replace, established leadership credibility.
Business Awareness vs Implementation Gap
Global research from Harvard Business Review Analytic Services, sponsored by Appian, revealed a significant gap between recognising AI risks and acting on them. While 92 % of business leaders agreed that AI agents need rules‑based guardrails to operate safely and effectively, less than half (48 %) said their organisation has actually defined such guardrails. Hutchinson warned, “Businesses know AI needs rules, but many are deploying it before those rules are in place. Doing so without the right controls can quickly lead to unexpected token costs, operational disruption and accountability gaps.” The findings suggest that without proactive governance, the rush to embed AI could exacerbate the very issues workers are already experiencing.
Worker Preferences for AI Decision‑Making
When asked about the appropriate role of AI, two‑thirds (66 %) of Australian workers believe decisions affecting employees or customers should either require human review and approval or always be made by people. A further 28 % would restrict AI to low‑risk decisions only. Hutchinson concluded, “Australian workers are rejecting unchecked AI. Businesses will only realise the full value of AI if employees build trust, are willing to use it within critical processes, and confident enough to act on its outputs.” This preference for bounded AI use underscores the need for clear policies that delineate where automation can safely operate and where human oversight remains essential.
Methodology and About Appian
Appian commissioned Zoho Research to survey 500 Australian workers in Q3 2026 to generate the insights presented. The company describes itself as a provider of AI automation for mission‑critical work, automating complex processes in large enterprises and governments. Appian notes its platform is known for unique reliability and scale, boasting more than 25 years of experience in enterprise operations. For further details, readers are directed to appian.com and the firm’s social‑media channels on LinkedIn, YouTube, Instagram, Facebook, and X.
Forward‑Looking Statements Disclaimer
The press release includes forward‑looking statements identified by words such as “anticipate,” “believe,” “continue,” “estimate,” “expect,” “intend,” “may,” “will,” and similar expressions. These statements are subject to risks and uncertainties detailed in Appian’s most recent Annual Report on Form 10‑K, quarterly reports on Form 10‑Q, and other SEC filings. Appian undertakes no duty to update these statements after the date of the release to conform them to actual results or revised expectations, except as required by law.
https://www.prnewswire.com/apac/news-releases/six-in-10-australian-workers-have-caught-ai-getting-it-wrong-at-work-302900918.html