Sam Altman, chief executive of OpenAI, told a Commonwealth Bank of Australia conference in Sydney on 26 May that artificial intelligence is unlikely to trigger the widespread white-collar job losses he and other tech leaders had previously warned about.
In a virtual interview at the conference, Altman said he was “delighted to be wrong” about the pace of AI-driven job displacement. He had previously predicted that AI would replace 30 to 40 per cent of all work tasks “in the not very distant future” during a 2025 interview.
Speaking to conference hosts and attendees, Altman acknowledged that his earlier concerns had not materialised. “I thought there would have been more impact on entry-level, white-collar jobs being eliminated by now than has actually happened,” he said, according to remarks reported by Reuters and the conference organisers.
The comments represent a notable shift from one of the most prominent voices in the AI industry, who has previously been among the loudest in warning about the technology’s potential to disrupt professional and managerial roles.
Why does it matter?
Altman’s revised outlook could affect investor sentiment around AI-exposed stocks and the broader narrative that has driven tech valuations higher over the past two years.
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The venue for the remarks is also significant. Commonwealth Bank hosted the Sydney conference where Altman spoke, and the bank has been vocal about its own AI investments and digital transformation plans. Major Australian banks and corporates have committed substantial capital to AI projects, and a cooling of the job-loss narrative may reduce the political and reputational risk around those initiatives.
For ASX-listed technology and professional services companies, the shift in tone from a leading AI figure could ease concerns about disruptive competition from automated systems. If the rollout of AI into white-collar work is slower or less disruptive than initially feared, it may give incumbent firms more time to adapt without facing immediate margin or headcount pressures.
The AI employment debate
Altman is far from the only tech executive to have raised alarm about AI’s potential impact on jobs. Other industry leaders have warned that automation could displace millions of workers, particularly in administrative, clerical and professional roles where tasks are routine or data-driven.
Those warnings have fed into a broader debate about the pace of AI adoption and the extent to which machine learning tools will complement or replace human workers. Some economists and labour market researchers have argued that AI is more likely to augment jobs than eliminate them, while others point to historical precedents where new technology did lead to significant displacement before new roles emerged.
The gap between prediction and reality may reflect several factors. AI tools have proven more difficult to integrate into complex workflows than early demos suggested, whilst regulatory and compliance constraints have slowed deployment in sensitive industries. Many organisations have also found that human oversight remains necessary even when AI systems handle routine tasks.
Altman’s change of tone does not mean AI will have no impact on employment, it suggests the timeline and scale of disruption may be less severe or more gradual than the most dramatic forecasts had implied.
What comes next?
For ASX-listed tech and services firms, the question is whether slower-than-expected AI disruption creates breathing room or whether it reflects deeper challenges in monetising AI tools at scale. Altman’s remarks are not going to settle the debate either way. Other tech leaders and policymakers will continue to offer their own views on AI’s employment impact, and the evidence will ultimately come from actual adoption patterns and workforce data rather than predictions.
For now, the takeaway for is that the AI-driven job apocalypse narrative has softened, at least from one of its most prominent sources but how that plays out in corporate strategy, capital allocation and market pricing remains to be seen.
