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市場調查報告書
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2031184

Verizon：通訊業自動化、人工智慧和自主網路 (AN)案例研究——作為全球最大的通訊業者之一，Verizon 如何在六年內裁員 33% 的同時，保持市場領先的利潤率？

Verizon: A Case Study in Telco Automation, AI and AN - How Does One of the World's Biggest Telcos Cut 33% of its Workforce in Six Years and Maintain Market-leading Margins?
出版日期: | 出版商: MTN Consulting, LLC | 英文 14 Pages | 訂單完成後即時交付

價格

自 2019 年以來，Verizon 已裁員 33%，同時將其運作中的人工智慧模式擴展至 1000 多個，運行通訊業最先進的自動化程式之一。儘管公眾關注的焦點集中在成本效益和裁員上，但 Verizon 也正致力於透過其「AI Connect」計畫實現人工智慧的商業化。本報告將說明Verizon 的成果、我們可以從中學到的經驗教訓以及需要進一步發展的領域。

Verizon 預測， 2025 年營收將達到 1,382 億美元，年增 2.5%。其息稅前利潤率 (EBIT 利潤率) 為 21.1%，高於全球通訊業15% 至 16% 的平均水準。去年年底不久，Verizon 完成了 Frontier Communications 的收購，這是過去十年美國最大的有線通訊業務收購案。 Verizon的目標是到2028年實現每年10億美元的營運費用協同效應。員工總數從2019年的約13.5萬人減少到2025年底的8.99萬人，六年內減少了33%。該公司還宣布將在2025年第四季進一步裁員超過1.3萬人。 2023年至2024年，每位員工的人事費用上升至約16萬美元，但在2025年第三季回落至約14萬美元。這反映出公司正在轉型為成本更低的非工會員工群體。人事費用佔營運費用（不包括折舊免稅額）的比例從2019年的19.5%下降到2025年第三季的15.9%，比21.9%的全球平均低約6個百分點。這一差距正在逐年擴大。 Verizon 的資本支出比率（CAPEX 強度）為 12.6%，遠低於全球平均水平，預計到 2026 年將進一步降至 11.6% 至 12.0%，即便 Frontier 的光纖網路建設正在加速推進。

Verizon是TAIA領域的全球領導者，在此次評測中獲得4.0分（滿分5分）。該公司在人工智慧營運部署和開放式無線存取網路（Open RAN）方面擁有豐富的經驗。其令人矚目的項目包括超過1000個運作中人工智慧模型、一個商用多廠商RIC、一個正式的人工智慧委員會和管治註冊機構，以及其北極星架構的「基於ODA運作」認證。該公司面臨的挑戰包括：關鍵效能指標的自我報告缺乏第三方檢驗；缺乏明確的自主網路層級目標和ANLAV認證；以及基於代理的人工智慧在Catalyst聯盟中仍處於研究階段，尚未投入生產。對供應商而言，Verizon在無線存取網（三星、愛立信、高通）和人工智慧基礎設施（Google雲端、AWS、英偉達、Vultr）方面採取的多廠商採購策略表明其有意避免對單一廠商的依賴。基於標準合規性、互通性、簡易性和價格的競爭優勢才是更關鍵的因素。 AI Connect 產品套件與 Frontier 有線網路的整合代表了兩個短期內最有可能與新供應商建立合作關係的領域。

上市機構

  • Alphabet (Google Cloud)
  • Amazon Web Services (AWS)
  • Amdocs
  • AOL
  • Apollo Global Management
  • AT&T
  • BSNL
  • China Mobile
  • Chunghwa Telecom
  • Ericsson
  • FCC
  • Frontier Communications
  • Intel
  • Linux Foundation
  • Meta
  • NTT
  • NVIDIA
  • Oi
  • Orange
  • Qualcomm
  • Red Hat
  • Samsung
  • Telecom Italia
  • TM Forum
  • T-Mobile
  • Vultr
  • Yahoo!

目錄

  • 概括
  • Verizon的成長、盈利和策略
  • Verizon是什麼？
  • 公司簡介
  • 企業業績
  • Verizon的戰略計劃
  • 高階主管就人工智慧、自動化和自主網路發表評論
  • Verizon的自動化、人工智慧和自主網路（AN）
  • 網路自動化和軟體定義基礎設施
  • 重大項目
  • 評估
  • 人工智慧和生成策略
  • 重大項目
  • 評估
  • 邁向自主之路：逐步擴展至L4級運行
  • 重大項目
  • 評估
  • Verizon的前景
  • 附錄
Product Code: TAIA-07052026-1

Verizon has shed 33% of its workforce since 2019 while scaling to 1,000+ AI models in production and running one of the most advanced automation programs in telecom. While the public focus is on cost efficiencies and headcount, Verizon also aims to monetize AI through its AI Connect program. This profile documents what Verizon has built, what we can learn from its trials, and where more progress is needed.

Verizon reported revenue of $138.2 billion (B) in 2025, up 2.5% YoY. Its EBIT margin was 21.1%, above the global telco average of 15-16%. Just after the end of the year, Verizon closed its Frontier Communications acquisition, the biggest wireline deal in the US in a decade. Verizon targets $1B in annual opex synergies by 2028. Total headcount fell from approximately 135,000 in 2019 to 89,900 at year-end 2025. That’s a 33% reduction over six years, and the company announced a further 13,000-plus position cut in 4Q25. Labor cost per employee rose to ~$160K per year in 2023–2024 before moderating to roughly $140K in 3Q25, reflecting a workforce shift toward lower-cost, non-union staff. Labor cost as a share of opex (excluding depreciation) fell from 19.5% in 2019 to 15.9% at 3Q25, roughly six percentage points below the global average of 21.9%. This gap has widened every year. Verizon’s capex intensity was 12.6%, well below global averages, and will dip further to 11.6-12.0% in 2026 even as the Frontier fiber buildout accelerates.

Verizon is a global leader in TAIA, scoring 4.0 out of 5 in our review. It has depth in operational AI deployment and Open RAN. Its 1,000+ AI models in production, commercial multi-vendor RIC, formal AI Council and governance registry, and Running on ODA accreditation for the North Star Architecture add up to an impressive program. Where the company falls short: headline performance figures are self-reported without independent verification, no autonomous networks level target or ANLAV certification has been stated, and agentic AI remains in Catalyst consortium research rather than production deployment. For vendors, Verizon’s multi-vendor procurement posture across RAN (Samsung, Ericsson, Qualcomm) and AI infrastructure (Google Cloud, AWS, NVIDIA, Vultr) signals a deliberate avoidance of single-vendor dependency; competitive positioning based on standards compliance, interoperability, simplicity, and price are the more decisive factors. The AI Connect product suite and the Frontier wireline integration represent the two near-term areas where new vendor engagements are most likely to develop.

Organizations mentioned

  • Alphabet (Google Cloud)
  • Amazon Web Services (AWS)
  • Amdocs
  • AOL
  • Apollo Global Management
  • AT&T
  • BSNL
  • China Mobile
  • Chunghwa Telecom
  • Ericsson
  • FCC
  • Frontier Communications
  • Intel
  • Linux Foundation
  • Meta
  • NTT
  • NVIDIA
  • Oi
  • Orange
  • Qualcomm
  • Red Hat
  • Samsung
  • Telecom Italia
  • TM Forum
  • T-Mobile
  • Vultr
  • Yahoo!

Table of Contents

  • Summary
  • Growth, profitability and strategy at Verizon
  • Who is Verizon?
  • Company snapshot
  • Company performance
  • Verizon’s Strategic Plan
  • Executive Quotes on AI, Automation & Autonomous Networks
  • Automation, AI and Autonomous Networks (AN) at Verizon
  • Network automation and software-defined infrastructure
  • Key projects
  • Assessment
  • AI and GenAI Strategy
  • Key projects
  • Assessment
  • The Path to Autonomy: Scaling Toward Level 4 Operations
  • Key projects
  • Assessment
  • Outlook for Verizon
  • Appendix

List of Figures and Tables

  • Table 1: Telco snapshot – Verizon
  • Figure 1: Revenues and operating profits over time for Verizon
  • Figure 2: Labor cost and capex trends at Verizon
  • Figure 3: Headcount, cost per employee, and labor cost opex for Verizon vs. global average
  • Figure 4: Verizon’s strategic focus in 2025-26