Import AI 452: Scaling laws for cyberwar; rising tides of AI automation; and a puzzle over gDP forecasting
Rapid AI cyber-capability growth and broad labour automation projections directly inform Australian government risk frameworks, workforce strategy, and cyber policy.
Key points
- AI offensive cyber capability is doubling roughly every 5-10 months, with frontier models now matching half a day of expert hacking work.
- MIT research projects AI will reach 80-95% success on most text-based labour market tasks by 2029, via gradual 'rising tide' automation.
- A major forecasting study finds experts expect AI progress but only modest GDP impact - a tension worth noting for economic policy assumptions.
Implications for Australian agencies
- Consider APS cyber and security policy teams may want to consider the Lyptus Research findings when updating threat models for AI-augmented offensive cyber risk.
- Monitor Workforce and labour market policy teams may want to monitor the MIT 'rising tide' automation research as it develops, given its implications for APS workforce planning and service delivery assumptions.
- Consider Agencies involved in AI economic impact analysis could consider the Forecasting Research Institute's GDP paradox findings when stress-testing assumptions in AI strategy documents.
Implications are AI-generated. Starting points, not advice — see methodology for how they're framed.
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Weekly digest, 6 April 2026
"Import AI 452: Scaling laws for cyberwar; rising tides of AI automation; and a puzzle over gDP forecasting"
Source: Import AI – Substack (Jack Clark)
Published: 6 April 2026
URL: https://importai.substack.com/p/import-ai-452-scaling-laws-for-cyberwar
Jack Clark's Import AI 452 covers four substantive threads. First, Lyptus Research finds frontier AI models are improving at offensive cybersecurity tasks on a ~6-10 month doubling cycle, with the best models now achieving 50% success on tasks requiring 3+ hours of expert human effort. Second, an INSEAD/Harvard field experiment shows AI-integrated startups significantly outperform peers on revenue and task completion, with managerial 'mapping' identified as the key bottleneck. Third, MIT research across 3,000 O-NET job tasks projects a broad 'rising tide' of AI automation reaching high success rates on most text-based work by 2029. Fourth, the Forecasting Research Institute finds that despite expectations of AI progress, surveyed economists, AI experts, and forecasters expect only modest GDP impact by 2030, a paradox Clark flags explicitly.
Implications for Australian agencies:
- [Consider] APS cyber and security policy teams may want to consider the Lyptus Research findings when updating threat models for AI-augmented offensive cyber risk.
- [Monitor] Workforce and labour market policy teams may want to monitor the MIT 'rising tide' automation research as it develops, given its implications for APS workforce planning and service delivery assumptions.
- [Consider] Agencies involved in AI economic impact analysis could consider the Forecasting Research Institute's GDP paradox findings when stress-testing assumptions in AI strategy documents.
Retrieved from SIMS, 18 July 2026.