The comments from Google DeepMind executives suggest the company believes a significant AI capability leap is approaching. The current wave of AI investment is not simply about expanding existing applications; it is aimed at reaching the next stage where AI systems increasingly help create better AI systems through recursive self-improvement (RSI).
RSI means AI models assisting with research, software development, optimisation, training methods and data generation, creating a feedback loop where improved AI accelerates the development of even better AI. Google’s view is that the foundations of this process are already emerging, and betting against the current AI buildout would be unwise.
The scale of spending reinforces this confidence. The major technology companies are committing hundreds of billions of dollars to AI infrastructure. Industry AI capital expenditure is expected to exceed $700bn in 2026 after more than $400bn in 2025, with Google alone forecasting around $195bn-$205bn of 2026 capex. This investment covers GPUs, advanced memory, networking, data centres and power infrastructure required for the next generation of AI.
While revenues currently lag behind investment, this reflects a transition phase where infrastructure is being built ahead of widespread adoption. The comparison with previous industrial revolutions suggests the largest economic benefits may appear after the technology platform is established.
The next 12-36 months are likely to see major improvements in AI agents, coding ability, research assistance and automation. If AI systems begin materially accelerating AI development itself, progress could become much faster later this decade, potentially marking one of the biggest technological shifts in history.