{
  "id": 15641,
  "url": "https://arxiv.org/abs/2607.29089",
  "title": "The Deployment Wall: A Diagnostic Framework and Instrument for Enterprise AI in the Deployment Era",
  "summary": "arXiv:2607.29089v1 Announce Type: new Abstract: Enterprise investment in generative artificial intelligence (AI) tripled in a single year to roughly US$37 billion, yet independent field research finds that about 95% of enterprise generative-AI pilots deliver no measurable profit-and-loss impact. We argue that the dominant explanation--that models are not yet capable enough--is mistaken, and that enterprise AI has entered a Deployment Era in which advantage derives not from model intelligence but",
  "authors": "Fabricio F. Costa (HCLTech)",
  "category": "research",
  "topics": "healthcare,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-03T04:00:00.000Z",
  "fetched_at": "2026-08-03T05:10:47.622Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/15641",
  "original_url": "https://arxiv.org/abs/2607.29089",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}