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健康狀態 健康來源類型 媒體原文權限 站內改寫最近入庫 2026-09-28ID emerj-ai運行狀態 已啟用

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最新公開文章

待翻譯:What Mature Security Programs Need Before Deploying AI

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Enterprise CISOs are under pressure to buy AI-powered security tools, but with vendors increasingly marketing their products as AI, it is hard to tell which tools will reduce risk and which will add cost. And when AI is deployed atop weak access controls, poorly classified data, or limited network visibility, it can exacerbate those gaps. […]

Emerj AI Research站內正文待翻譯:What Mature Security Programs Need Before Deploying AI

待翻譯:Artificial Intelligence at Cleveland Clinic

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Cleveland Clinic is a nonprofit academic medical center headquartered in Cleveland, Ohio, with operations in Florida, Las Vegas, Toronto, London, and Abu Dhabi. The health system employs 83,000 caregivers and operates 23 hospitals and 300 outpatient facilities.​ In 2025, Cleveland Clinic reported $18.3 billion in operating revenue and recorded 15.9 million patient encounters, including 14.4 […]

Emerj AI Research站內正文待翻譯:Artificial Intelligence at Cleveland Clinic

待翻譯:Precision CX in Regulated Industries

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Customer service is one of the first areas where banks, insurers, and healthcare organizations have deployed AI directly in front of customers, according to the U.S. Government Accountability Office. In financial services, all ten of the country’s largest commercial banks now use chatbots to engage customers, and more than 98 million U.S. consumers interacted with […]

Emerj AI Research站內正文待翻譯:Precision CX in Regulated Industries

待翻譯:How to Build the Unified Data Foundation Drug Discovery AI Depends On

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This article is sponsored by CDD Vault and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.​ Drug discovery is one of the slowest, costliest processes in enterprise R&D. Developing a single FDA-approved therapy typically […]

Emerj AI Research站內正文待翻譯:How to Build the Unified Data Foundation Drug Discovery AI Depends On

待翻譯:Building a Reliable Foundation for Agentic AI in SMBs

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This article is sponsored by Salesforce and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Customer-facing organizations now face a widening capacity gap driven by escalating multi‑channel demand and the constraints of human-only workflows […]

Emerj AI Research站內正文待翻譯:Building a Reliable Foundation for Agentic AI in SMBs

待翻譯:Artificial Intelligence at BHP – Two Use Cases

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:BHP is reported to be the world’s largest mining company by market capitalization, according to Wikipedia, citing 2025 data. It has more than 80,000 employees and contractors working across operations in Australia, Chile, Peru, Brazil, Canada, and the United States. The company posted US$51.3 billion in revenue for fiscal year 2025, on record production of […]

Emerj AI Research站內正文待翻譯:Artificial Intelligence at BHP – Two Use Cases

待翻譯:Solving for the Medical Device Field Service Knowledge Gap

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This article is sponsored by Aquant and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Field service organizations are losing expertise faster than they can capture it, a measurable operating risk, not only a […]

Emerj AI Research站內正文待翻譯:Solving for the Medical Device Field Service Knowledge Gap

待翻譯:How Retail Leaders Can Scale AI Beyond Pilots

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This article is sponsored by Unframe and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Retail has an AI operationalization bottleneck, converting AI investment and experimentation into governed, integrated production capabilities that deliver measurable […]

Emerj AI Research站內正文待翻譯:How Retail Leaders Can Scale AI Beyond Pilots

待翻譯:Building Compute Foundations for the Physical Economy

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:The core imbalance behind industrial AI’s stalled progress is structural: physical‑operations AI is being asked to run real‑time, safety‑critical control workloads on a fraction of the compute maturity the digital economy already built. This is a compute‑maturity lag — the architectural deficit. OECD data on AI adoption across G7 economies show a clear industry […]

Emerj AI Research站內正文待翻譯:Building Compute Foundations for the Physical Economy

待翻譯:Risk and Cost Governance for AI Agents in Regulated Institutions

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This interview analysis is sponsored by Zafin and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Regulated institutions are deploying AI agents into real workflows. This requires the governance, control, auditability, and cost discipline […]

Emerj AI Research站內正文待翻譯:Risk and Cost Governance for AI Agents in Regulated Institutions

待翻譯:Scaling Scientific R&D with AI Supercomputing Infrastructure

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:​Pharmaceutical and life sciences enterprises have proven AI can improve individual stages of discovery, development, and manufacturing — but the industry’s legacy IT infrastructure was never built for frontier-scale compute. This is a structural, industry-wide constraint. The economics make the stakes clear. According to the National Institutes of Health, a discovery can take almost 15 […]

Emerj AI Research站內正文待翻譯:Scaling Scientific R&D with AI Supercomputing Infrastructure

待翻譯:Moving AI from Paralysis to Production in Regulated Enterprises

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This (article/interview analysis) is sponsored by Elephant Ventures and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Across banking, financial services, and pharma, AI ambition continues to outpace AI deployment. RAND Corporation found that […]

Emerj AI Research站內正文待翻譯:Moving AI from Paralysis to Production in Regulated Enterprises

待翻譯:Artificial Intelligence at Lowes

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Lowe’s Companies operates as a Fortune 100 home improvement retailer, with fiscal year 2025 sales that exceeded $86 billion. The company employs approximately 300,000 associates and operates more than 1,750 stores, 540 branches, and 120 distribution centers across the United States. Lowe’s reported 16 million customers weekly across an omnichannel network that spans in-store, online, […]

Emerj AI Research站內正文待翻譯:Artificial Intelligence at Lowes

待翻譯:Artificial Intelligence at Caterpillar

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Caterpillar ranks as the world’s largest construction equipment manufacturer and also produces off-highway diesel and natural gas engines, industrial gas turbines, and diesel-electric locomotives, headquartered in Irving, Texas. The company employed 118,000 people worldwide at the end of 2025 and posted $67.6 billion in sales and revenues for the year, the highest full-year total in […]

Emerj AI Research站內正文待翻譯:Artificial Intelligence at Caterpillar

待翻譯:The Mobile Security Imperative for Regulated Industries

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:This interview analysis is sponsored by Appdome and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page. Mobile applications have become the primary interface between enterprises and their customers, and increasingly one of the most […]

Emerj AI Research站內正文待翻譯:The Mobile Security Imperative for Regulated Industries

企業AI的資料優先安全策略

本文探討了AI採用與資料治理之間的差距,指出88%的組織已使用AI,但僅有35%的組織能完全瞭解非結構化資料的儲存位置。文章透過專家見解提出了四個關鍵洞察:即時敏感資料流對映、統一治理、開發前問責框架以及資料級安全控制。

Emerj AI Research站內正文企業AI的資料優先安全策略

梅奧診所的人工智慧應用

梅奧診所是一家非營利學術醫療中心,擁有近85,000名員工,2025年運營收入4.73億美元。該機構正在推進200多個人工智慧專案,涵蓋從早期可行性研究到臨床部署的各個階段。本文重點介紹兩個AI用例:AI心電圖篩查用於早期疾病檢測,以及AI驅動的病歷審查工具Record Time,後者幫助醫生平均每次就診節省5-30分鐘準備時間。

Emerj AI Research站內正文梅奧診所的人工智慧應用

為新的AI產品建立市場合法性

鐵山公司(Iron Mountain)透過與Emerj合作,將其從物理儲存品牌重新定位為AI創新者。透過播客、文章和PDF報告,該公司在銀行和保險領域獲得了超過30,000次下載和數百個合格線索,成功提升了其AI搜尋發現平臺的知名度。

Emerj AI Research站內正文為新的AI產品建立市場合法性

人工智慧如何重塑受監管的專業工作流程

受監管行業(如金融、法律、稅務和審計)對AI的採納面臨零容錯率的要求。斯坦福研究發現通用語言模型在法律問題上的幻覺率高達58%-88%。AI必須滿足受託責任級別的準確性、資料保護和人為籤核要求,才能安全部署。文章提煉了四個關鍵洞察:準確性標準、工作流自動化、資料保障和明確的責任劃分。

Emerj AI Research站內正文人工智慧如何重塑受監管的專業工作流程

將視覺AI轉化為企業業務影響

儘管計算機視覺在製造領域技術表現優異,但77%的專案仍停留在原型或試點階段。本文透過三位專家的見解,分析了阻礙規模化的核心因素:生態就緒度、業務主導的所有權以及透過小勝利積累的操作信任。

Emerj AI Research站內正文將視覺AI轉化為企業業務影響

AI如何重塑關鍵基礎設施的服務運營

服務組織面臨近乎零停機需求與維護能力之間的結構性錯配。透過異常檢測、規範性指導和運營轉型,AI幫助技術人員在故障發生前採取行動,提升首次修復率,減少停機成本。

Emerj AI Research站內正文AI如何重塑關鍵基礎設施的服務運營

設計:企業供應鏈的護城河

隨著AI和最佳化工具的普及,傳統供應鏈規劃模型已無法提供競爭優勢。麻省理工斯隆管理評論與世界經濟論壇的研究顯示,多數企業仍缺乏對一級供應商的可見性。本文基於Emerj播客系列,探討了基於場景的網路建模、AI加速的情景分析以及統一設計環境如何幫助企業在波動中做出更好的決策。

Emerj AI Research站內正文設計:企業供應鏈的護城河

丘博保險的人工智慧應用

丘博保險(Chubb)是一家全球財產及意外險保險公司,計劃在三到四年內透過AI自動化85%的核保和理賠流程。關鍵應用包括智慧核保錄入(將北美週期從24小時縮短至2小時)和AI驅動的理賠文件處理(首次聯絡時間從24小時降至3小時)。公司擁有3500多名工程師,並在全球建立工程中心。經驗教訓包括將AI投資與週期時間指標掛鉤,以及建立理賠與核保之間的閉環反饋。

Emerj AI Research站內正文丘博保險的人工智慧應用

從互聯代理到集體智慧

UC Berkeley研究分析了七個生產級多代理系統的1642條執行軌跡,發現代理協作時故障率為41%至86.7%。故障原因分為結構性問題:41.8%源於規範缺失和共享治理(死鎖),36.9%源於代理間語義偏差。研究還顯示,缺乏協調時錯誤放大可達17倍,即使有集中檢查點仍放大4.4倍。Cisco Outshift的Guillaume De Saint Marc提出,企業需要構建共享語義層、代理特定控制和安全擴充套件的開放互操作性,以實現可靠的協作智慧。

Emerj AI Research站內正文從互聯代理到集體智慧

統一上下文:企業AI缺失的基礎

本文探討了企業AI專案失敗率高達80%的原因,指出碎片化資料和缺乏統一上下文是主要障礙。透過Arango和IBM專家的見解,文章提出了構建可解釋、可信賴的代理AI系統的四個關鍵洞察。

Emerj AI Research站內正文統一上下文:企業AI缺失的基礎

企業AI合同的新策略

企業AI支出與成果之間的差距正在擴大,美國聯邦機構的AI使用量翻倍,但定價難題凸顯。文章提供了四項高管策略:可逆的轉型決策、基於證據的談判槓桿、短週期商業承諾、以及獨立問責制,以保護成本、靈活性和槓桿。

Emerj AI Research站內正文企業AI合同的新策略

Moderna的AI應用

Moderna是一家基於mRNA技術的生物技術公司,透過AI實現企業級生產力提升和mRNA序列設計加速。公司利用ChatGPT Enterprise和自定義GPT實現法律、研發、製造等部門的全面採用,同時透過mRNA設計工作室縮短疫苗和治療方案的設計週期。

Emerj AI Research站內正文Moderna的AI應用

代理型AI如何成為現代客戶服務的核心能力

代理型AI正成為現代客戶服務企業的關鍵能力,幫助企業應對長期以來規模龐大、成本高昂且效率低下的客服運營問題。本文基於Dialpad與Comcast高管的對話,探討了三個核心洞察:歷史互動資料揭示高價值自動化領域、AI主導的智慧分流提升人類工作效率、統一平臺架構解決客服碎片化問題。文章強調,在受監管行業中,準確性、信任和整合是成功部署代理型AI的關鍵。

Emerj AI Research站內正文代理型AI如何成為現代客戶服務的核心能力

將人工智慧試點轉化為企業價值的條件

儘管人工智慧採用率上升,但大多數部署並未觸及運營核心,導致投資回報率有限。本文探討了四個關鍵條件,包括問題定義、組織準備度、認知設計和投資回報率清晰度,幫助企業在試點成功基礎上實現可擴充套件的價值。

Emerj AI Research站內正文將人工智慧試點轉化為企業價值的條件

企業AI實踐:領先企業如何從戰略走向生產

本文探討了企業AI從孤立試點轉向可重複、可衡量業務成果的四個關鍵洞察:端到端工作流是AI價值的真正單位、AI必須構建在即時工作流中、從個人擴充套件到團隊協作、以及工作本身的改變而非僅僅工具。文章基於HTEC三位高管的播客系列。

Emerj AI Research站內正文企業AI實踐:領先企業如何從戰略走向生產

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