Reading up on PwC

AI progress is constrained by long-task reliability, labor reallocation, cost inefficiencies of general APIs, the declining value of raw coding skills, inadequate benchmark testing, the limits of formal verification without strong specs, memory-bound local hardware advantages, the shift from data to environment-driven training, and the rising competitiveness of US open-weight models.

As AI model release cadence accelerates to every 42 days, companies like Harvey, Glean, and ElevenLabs are expanding from single workflow tools into broad platforms, reversing the SaaS-era unbundling strategy.

Amazon uses automated reasoning—formal logic that mathematically proves correctness—to catch and correct AI hallucinations in its generative AI products and agentic AI projects.