Accenture: Then and now, and how it may signify things to come
The article discusses the evolution of Accenture from its early days to its current state, and speculates on what its trajectory might indicate about broader business and technology trends. It questions whether recent developments at Accenture are a temporary anomaly or part of a larger pattern.
Background
- Gary Marcus is a prominent AI researcher, author, and frequent critic of large language models (LLMs) and deep learning approaches. He runs a popular Substack on AI.
- Accenture is a massive global consulting and professional services firm (approx. 750,000 employees) that advises enterprises on technology adoption, including AI.
- In late 2024, Accenture reported a massive decline in its stock amid rumors that its large-scale generative AI consulting deals were underperforming or being paused by clients, suggesting skepticism about near-term ROI from LLM-based products.
- Marcus has long argued that LLMs (like GPT-4) face fundamental limitations — reliability, cost, coherence — that will hinder enterprise deployment. This post appears to treat Accenture's troubles as evidence for that thesis.
- The post contrasts Accenture's AI hype cycle (the "now") with its earlier role in the dot-com boom (the "then"), implying a pattern of consulting-driven tech exuberance followed by disappointment.