What building an AI-native finance function taught me
The article discusses the lessons learned from building an AI-native finance function, which involves giving everyone access to AI tools and creating a reason to use them. The goal is to redesign the full workflow around the decision, allowing finance professionals to become builders and providing a real-time view of the company's financial position. By adopting this approach, finance teams can move beyond static spreadsheets and manual searches, and instead use live tools built on the full context and data of the business.
- ▪The author's company aimed to build a finance function from the ground up, making AI fundamental to how they work and make decisions.
- ▪The company set two bold ambitions: a zero-day close and automated, continuously updated forecasting.
- ▪The work has changed how the team operates, pushing them beyond the limitations of static spreadsheets and manual searches.
- ▪The real promise of an AI-native finance function is a team that understands what is happening as it happens and helps leaders see the choices ahead.
2 outlets in our directory ran this story. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ What building an AI-native finance function taught me - OpenAI — Google News
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Story provenance
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Record
| Original publisher | OpenAI Blog |
| Canonical URL | https://openai.com/index/building-an-ai-native-finance-function |
| Publication time | Mon, 10 Aug 2026 17:00:00 GMT |
| Retrieval time | 2026-08-10T16:30:44.389Z |
| Last seen | 2026-08-10T16:30:44.389Z |
| 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 | v99NA13kRgRA · 2 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
August 10, 2026CompanyWhat building an AI-native finance function taught meFive lessons for CFOs redesigning work around artificial intelligence.Loading…Share1. Give everyone access, then create a reason to use it1. Give everyone access, then create a reason to use it2. Redesign the full workflow around the decision3. Finance professionals become builders4. Pair speed with clear accountability and controls5. Measure value per unit of intelligenceThe CFO’s opportunity1. Give everyone access, then create a reason to use it2. Redesign the full workflow around the decision3. Finance professionals become builders4. Pair speed with clear accountability and controls5. Measure value per unit of intelligenceThe CFO’s opportunityFinance has become a real-time function.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at OpenAI Blog.
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