AI is reshaping the telecom industry, but not all change is equal. In this video, we explore the two strategic directions for AI in telecom: revenue innovation vs network efficiency.
You’ll discover:
• Cost-saving AI in telecom: predictive maintenance, traffic management, and network optimisation
• Revenue-driven opportunities powered by 5G, network slicing, network APIs, IoT, and SaaS
• Real-world operator examples: SK Telecom, Telkomsel, DoCoMo, Rakuten, Swisscom, and MásMóvil
• The four layers of AI impact in telecom: automation, prediction, augmentation, and creation
• Why innovation is less predictable, more complex, and requires human strategic judgement
📌 Whether you’re in telecom, product management, or technology strategy, this video gives you a clear roadmap of AI’s impact on the future of mobile networks.
00:00 Introduction - AI's Two Strategic Tracks
01:56 What's Happening with AI in Telecom Right Now
02:48 NVIDIA Survey Results - Claims vs Reality
03:30 Cost-Saving AI Examples (Nokia, NTT DoCoMo, Rakuten)
05:26 Revenue-Focused AI Examples (SK Telecom, Telkomsel)
07:26 The Four Layers of AI Impact Framework
09:44 Standardised vs Complex Input - Key Insight
11:04 Why Revenue Opportunities Are Different
12:23 The AI Convergence - SaaS Growth & Network APIs
15:00 Two Paths Forward - Innovation vs Efficiency
#telecomstrategy #aistrategy #5gmonetization #networkbusiness #telecomtransformation #telecominnovation #FutureOfTelecom#TelecomVision#digitalstrategy #NetworkStrategy
Sources: NVIDIA 2025 Survey, Nokia/stc Saudi Arabia, Rakuten Mobile, MásMóvil/Ericsson Spain, Swisscom/Ericsson Switzerland, NTT DoCoMo Japan, SK Telecom, Telkomsel, McKinsey Network API Market study, AI-Created SaaS Market report
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