Why Isn't AI Adoption Showing Up in Your P&L?
At one bank, a team accelerated its pull request pipeline with AI. Incidents per pull request rose roughly 243%. It had gotten faster in exactly the wrong place.
- ▪At one bank, a team accelerated its pull request pipeline with AI.
- ▪Incidents per pull request rose roughly 243%.
- ▪It had gotten faster in exactly the wrong place.
Hacker News (AI / LLM) files mainly under ai. We currently carry 7,341 of its stories.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | IT Revolution |
| Canonical URL | https://itrevolution.com/articles/why-isnt-ai-adoption-showing-up-in-your-pl/ |
| Publication time | Fri, 02 Oct 2026 12:57:51 +0000 |
| Retrieval time | 2026-10-02T13:21:35.761Z |
| Last seen | 2026-10-02T13:21:35.761Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 4RGFz06DcTn6 · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
At one bank, a team accelerated its pull request pipeline with AI. Review time rose roughly 441%. Incidents per pull request rose roughly 243%. The team hadn’t gotten slower. It had gotten faster in exactly the wrong place. Speed didn’t disappear when it hit the next stage of the pipeline; it just showed up somewhere else, as a queue. That anecdote, and the population-scale data behind it—Faros AI’s 2026 research spanning 22,000 developers across more than 4,000 teams—anchors AI-Driven Organizational Value, a paper in the Fall 2026 Enterprise Technology Leadership Journal from IT Revolution, authored by Rodo Abad, Jason Cox, Jeff Gallimore, Betty Junod, Tapabrata Pal, Brian Scott, and Max Reele.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at IT Revolution.
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