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GPT-5 flopped: is the US AI hype finally catching a reality check?

By L L Seow | Wednesday, August 27, 2025, 8:40 PM Asia/Singapore

GPT-5 flopped: is the US AI hype finally catching a reality check?

Multiple reports seem to concur: the US AI hype bubble has not quite burst yet, but pragmatism is sharpening a pinprick

Last week, several news reports have jointly pointed to signs that the United States “AI hype machine” is undeniably in a state of shakeup, moving from boundless excitement toward a sobering plateau.

The high-profile rollout of GPT-5 in early August had exposed cracks in the narrative of unstoppable, exponential AI progress. As reported by the LA Times, the launch product had failed to deliver the revolutionary leap promised — instead showing limitations similar to its predecessors, sparking disappointment among users and critics alike. This bust is not just about a single product, but signals a broader reckoning with AI’s real-world capabilities versus the outsized expectations fueled by marketing and investor zeal.

Meanwhile, a Forbes report had echoed concern over the persistent hype cycle, warning that normalizing inflated AI expectations could lead to an “AI winter”: a fading investor enthusiasm reminiscent of past tech bubbles. The divide between hype and tangible advancement calls for a reorientation from flashy demos to pragmatism in AI adoption.

Previously, data from Pew Research had described deep public skepticism contrasting with expert optimism: while 51% of Americans polled had expressed more concern than excitement about the role of AI, 56% of experts had expressed hopes of positive impacts in the next two decades. Both groups of respondents, however, did agree on the urgent need for better control and regulation, fearing lax oversight could exacerbate risks.

Also, according to opinions from Pragmatic Coders, AI agents and AI-ready data are now at the peak of inflated expectations, signaling new hurdles ahead related to governance, security, and data readiness — yet the hype is cooling as more grounded practical challenges come to the fore, with real investment shifting towards data engineering and governance over flashy demos.

Together, these perspectives paint a nuanced picture: the promise of AI remains vast, but tempered by the realities of practical and ethical challenges. The US AI scene is hopefully beginning to transition from hype to a more grounded, watchful era.

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