企業使用助手證據

2026年8月14日 00:00
站內 AI 整理稿

Economics > General Economics arXiv:2608.

12236 (econ) [Submitted on 12 Aug 2026] Title:How Organizations Use AI: Evidence from ChatGPT Authors:Aaron Chatterji, David Holtz, Neel Rakholia, Prasanna Tambe, Gawesha Weeratunga View a PDF of the paper titled How Organizations Use AI: Evidence from ChatGPT, by Aaron Chatterji and 4 other authors View PDF HTML (experimental) Abstract:We study how organizations use frontier generative AI by linking ChatGPT Enterprise account records to usage, worker roles, task classifications, and public-company financial data through March 2026.

These linked data enable a privacy-preserving analysis of adoption, worker roles, and message-level tasks at scale: for instance, the worker-level sample we analyze at the six-month adoption horizon includes over 1,500 organizations and over 17 million messages.

We document four facts about enterprise AI adoption and use.First, ChatGPT Enterprise usage has grown rapidly due to a combination of new firm adoption and growing intensity among existing adopters.Second, U.S.

-based public company adoption is concentrated among larger, more valuable, and more R&D- and SG&A-intensive firms.Third, active use within adopting firms spans job functions and seniority levels, with especially high usage intensity among early-career workers.

Fourth, ChatGPT Enterprise usage encompasses a broad range of knowledge work tasks, including writing, technical work, communication, and information synthesis.

In aggregate, these results suggest that firms differ widely in the speed, breadth and purpose of their enterprise AI adoption, and that they are still actively learning how to integrate AI into organizational workflows.Subjects: General Economics (econ.GN); Artificial Intelligence (cs.

AI); Human-Computer Interaction (cs.HC) Cite as: arXiv:2608.12236 [econ.GN] (or arXiv:2608.12236v1 [econ.GN] for this version) https://doi.org/10.48550/arXiv.2608.

12236 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: David Holtz [view email] [v1] Wed, 12 Aug 2026 16:32:52 UTC (12,864 KB) Full-text links: Access Paper: View a PDF of the paper titled How Organizations Use AI: Evidence from ChatGPT, by Aaron Chatterji and 4 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: econ.

GN < prev | next > new | recent | 2026-08 Change to browse by: cs cs.AI cs.HC econ q-fin q-fin.EC References & Citations NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading...BibTeX formatted citation × loading...

Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.

ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?

) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.

AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?

) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community?Learn more about arXivLabs.Which authors of this paper are endorsers?| Disable MathJax (What is MathJax?)

Related

相關文章

鈦媒體生成式AI

王興興“錯配”梁文鋒?

王興興“錯配”梁文鋒?字母榜2026.08.24 17:44 · 來自河北全文4818字00:00 / 13:21關於世界模型,宇樹和DeepSeek理念分歧明顯。文 | 字母榜宇樹科技的股價還在持續下跌。市值從上市首日的4449億元高點,跌至2400億元,截至8月24日收盤,市值較最高點蒸發了2000億元。然而比股價更值得關注的是,宇樹接下來要怎麼走。8月20日,也就是宇樹上市第二天,王興興出現在北京世界機器人大會論壇。十多分鐘的分享裡,AI成為了高頻詞彙。他談到AI實時生成、實時識別,也談到AI模型投入,更透露了宇樹正在預研的一件事:讓物理AI機器人實現“自進化”。王興興講的每一件事,最後都指向一個關鍵要素:AI大模型。特別是最後一點,王興興說,要實現“物理AI自進化”,要用目前最前沿、最頂尖的AI大模型來驅動。而這恰恰是宇樹目前不太擅長的部分。不過,宇樹找到了DeepSeek。今年8月,兩家公司已經達成合作,圍繞AI大模型與具身智能相關技術展開合作。說到具身智能公司和AI大模型公司的合作,就不得不提當年Figure AI和OpenAI的合作。2024年,OpenAI在投資Figure AI後,雙方簽署了三年合作協議,合作開發人形機器人AI模型。但是僅一年後,FigureAI終止合作,轉向自研。於是問題來了:王興興和梁文鋒,會不會重走Figure AI和OpenAI的老路?01為什麼宇樹需要DeepSeek?對於宇樹來說,過去幾年,模型研發已經有了一些積累,但顯然投入不足,進展緩慢,所以找到一個頂尖的AI大模型公司合作,是一個比較自然的選擇。先來看宇樹目前的模型研發進展。當前,具身智能大模型沒有一個統一的技術路線,但VLA和世界模型,是行業重點探索的兩個方向。行業甚至也在探索兩者融合的技術路線。宇樹也在摸索,採取了“兩條腿走路”的策略,並行研發兩種模型。所謂VLA(視覺

剛剛
量子位生成式AI

阿里視頻大模型Wan3.0正式上線,行業評價“穩定、真實、有質感”

阿里巴巴影片生成大模型Wan3.0正式上線,單次可生成30秒影片,並首次支援doc、xls、ppt、pdf、md等文檔輸入。企業用戶普遍評價其「穩定、真實、有質感」,能穩定保持角色與場景一致性,並已進入短劇、影視、廣告等生產流程。即日起可於阿里雲百鍊、千問等平台體驗,標準版並推出限時7折優惠。

剛剛
IT之家生成式AI

阿里雲視頻生成模型 Wan3.0 正式上線,支持單次生成 30 秒視頻、文檔輸入

作者:遠洋 責編:遠洋 評論: 8 月 24 日消息,阿里雲消息,今天,視頻生成模型 Wan3.0 正式上線。官方稱,Wan3.0 在生成時長、萬能創作、全能參考以及真實世界還原等維度全面升級,單次可生成 30 秒視頻,並首次支持 doc、xls、ppt、pdf、md 等文檔格式輸入,力求準確還原真實世界。

剛剛