ITmedia tested Anthropic's Claude Fable 5 AI model by asking it to predict how IT engineers' jobs will change by 2036 and what steps they should take now to prepare.
The outlet also posed the identical question to Google's Gemini 3.1 Pro and OpenAI's GPT-4.5 to compare how different leading AI systems forecast the future of technical work.
What happened
ITmedia tested Anthropic's Claude Fable 5 by asking it to predict what IT engineers' work will look like in 2036 and what they should prepare for now. For comparison, the outlet posed the same question to Google's Gemini 3.1 Pro and OpenAI's GPT-4.5.
Why it matters
As AI models become more widely deployed, understanding how different systems forecast industry change—and what they recommend for professional readiness—helps workers and managers weigh which tools to trust for career planning. The comparison across three major vendors may show meaningful differences in how each model approaches the future of technical work.
What to watch
The full responses from all three models are presented in the ITmedia report, with Fable 5's predictions and preparatory guidance as the centerpiece of the evaluation.
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ITmedia's test of Claude Fable 5 was designed to evaluate the model's performance on a practical, forward-looking question that many professionals care about: how will my field change, and what should I do about it now? By comparing responses across three of the most widely used AI systems—Anthropic, Google, and OpenAI—the outlet aims to show whether different architectures and training approaches produce meaningfully different forecasts about the labor market.
The framing of the test assumes that AI models can offer useful perspective on long-term professional change, even though no AI system has access to real future data. What the comparison likely reveals instead is how each model's training and design philosophy shapes its tone, specificity, and recommendations when presented with an inherently uncertain question. The results may help readers understand which systems' reasoning aligns with their own intuitions about technology adoption and workforce evolution.
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