Four years after ChatGPT caught so many by surprise, the primary role of higher education seems to be slowing down the public’s transition to the AI era. For many faculty, this is a win. For those focused on the future, this is the biggest institutional failure since the Victorian Post Office, with its monopoly on telegraph lines, dismissed the telephone because it had plenty of messenger boys. Adoption was slowed so much there were waiting lists for a home phone line into the 1970s.Some facts. More than 90 percent of notable AI models released in 2025 came from industry: GPT-5, Gemini 3, Claude Opus 4.5, Grok 4, Llama 4, DeepSeek-V3.2, Qwen 3, Kimi K2. The infrastructure supporting frontier development is also overwhelmingly from industry. Global AI compute capacity has been growing 3.3x annually since 2022, doubling every seven months, driven by hyperscalers and enormous data-center investments. Some universities are entering the compute space. Ten New York universities spent two years and $340 million to get to about 400 GPUs. In 2024, xAI in Memphis stood up 100,000 GPUs in 122 days. In the past two years a site in Abilene, Texas got to 500,000.2