AI in Enterprise Software 2026: What the Data Shows

Enterprises spend billions on artificial intelligence, yet half of new models never leave the sandbox. According to recent data, only forty-eight percent of pilot projects reach production within twelve months. David Ohnstad examines this deployment paradox, revealing why feedback loops and real-world data are essential to bridging the gap between heavy investment and actual enterprise value. Full article: https://davidohnstad.net/state-of-ai-machine-learning-enterprise-software-2026/

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-02
DOI
https://doi.org/10.5281/zenodo.23893319
Primary Topic
Artificial Intelligence Applications
Type
article
Field-Weighted Citation Impact
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article

AI in Enterprise Software 2026: What the Data Shows

David Ohnstad
2 links
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence Applications
article

AI in Enterprise Software 2026: What the Data Shows

David Ohnstad
article en

Abstract

Enterprises spend billions on artificial intelligence, yet half of new models never leave the sandbox. According to recent data, only forty-eight percent of pilot projects reach production within twelve months. David Ohnstad examines this deployment paradox, revealing why feedback loops and real-world data are essential to bridging the gap between heavy investment and actual enterprise value. Full article: https://davidohnstad.net/state-of-ai-machine-learning-enterprise-software-2026/

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 17%
Artificial Intelligence Applications
DOIOpen Access PDFOpenAlex
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AI in Enterprise Software 2026: What the Data Shows — David Ohnstad · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS