Insights

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The APAC telco enterprise business landscape in the first half of 2026 is shaped by evolving revenue streams, competitive pressures, and the growing influence of artificial intelligence infrastructure. Enterprise services, including both connectivity and non-connectivity offerings, remain central to operator strategies across Asia-Pacific, but shifts in revenue contribution and growth dynamics are prompting reassessment of core and emerging segments.Key themes include the rise of non-connectivity services, the strategic value of telco-owned land and power assets for hyperscalers, and the challenges telcos face in capturing value from AI infrastructure—particularly as most AI margins accrue to chip and model providers. The analysis also covers state-driven investment models in markets like China, the impact of regulatory resets, and the strategic choices facing operators: whether to build, partner, or risk decline in the enterprise sector.<ul><li>Coverage spans major APAC markets and highlights differences in enterprise performance and strategy.</li><li>Explores the interplay between traditional connectivity, digital services, and AI-driven opportunities.</li><li>Examines how regulatory, accounting, and market structure factors shape operator outcomes.</li></ul><blockquote>How can APAC telcos redefine their enterprise business models to capture growth from non-connectivity and AI-driven opportunities while managing a weakening core?</blockquote>

APAC telcos enterprise business update: H1-2026

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Managed access to Chinese frontier AI models is reshaping enterprise AI strategy. The arrival of Moonshot AI’s Kimi K3 on Amazon Bedrock signals a shift in how large organizations approach AI model selection, procurement, and governance. Enterprises can now leverage advanced, open-weight Chinese AI through familiar AWS APIs, billing, and security frameworks, reducing operational friction and enabling new options for cost management and deployment flexibility.Kimi K3’s integration with Amazon Bedrock introduces prompt caching and supports multi-model architectures, allowing organizations to distribute workloads between open-weight and proprietary models based on cost, complexity, and business needs. This development prompts a re-examination of AI infrastructure, balancing performance, cost efficiency, and governance across diverse use cases.Key considerations for CIOs, CFOs, and CISOs include model provenance, licensing, regulatory compliance, and data residency—especially as regional availability and legal obligations differ across the United States, Europe, and Asia Pacific. The managed environment provides strong infrastructure-level security, but enterprises must still evaluate the governance of Chinese-origin models before adoption.<ul><li>Explores managed deployment options for open-weight AI on AWS</li><li>Assesses security, compliance, and procurement implications</li><li>Compares regional constraints and opportunities for global enterprises</li></ul><blockquote>How will the availability of Chinese frontier AI models like Kimi K3 on Amazon Bedrock change enterprise AI procurement and governance strategies?</blockquote>

The Managed Front Door to Chinese Frontier AI: What Kimi K3 on Amazon Bedrock Means for Enterprise Buyers

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Global telecommunications operators are navigating a period of significant transformation, as highlighted in the H1-2026 performance benchmark. The analysis covers global telco performance across revenue growth, capital expenditure, operational efficiency, and strategic shifts in service offerings. Key areas include the impact of tariff changes, the expansion of wireless broadband for rural and suburban connectivity, and the adoption of satellite-to-phone services to address customer churn in coverage gaps.The benchmark provides detailed insights into how leading telecom operators are reallocating capital expenditure from traditional 5G infrastructure to AI data centers and digital platforms, with China and Korea setting the pace for AI investment. It also examines the trend of telecom companies spinning off fintech divisions to enable independent financing and lending, and the growing role of private equity and external investors in funding telco-backed AI infrastructure.<ul><li>Revenue, EBITDA, CAPEX, and ARPU trends for H1-2026</li><li>Comparative analysis of wireless broadband versus fiber in different geographies</li><li>Emerging strategies in satellite connectivity and fintech restructuring</li></ul><blockquote>Which operators are leading the shift from connectivity to digital platforms, and how are capital and technology investments reshaping global telco performance?</blockquote>

Global telcos performance benchmark: H1-2026

Insights on H1-2026's pricing winners, mature defenders and AI investors

Revenue analysis of Global telcos: H1-2026

FWA scales fast on spare 5G capacity but in dense cities fibre still wins on quality and retention

Telcos are moving CAPEX from 5G to AI compute, and China and Korea and furthest ahead

EBITDA analysis of Global telcos: H1-2026

Telcos are restructuring fintech for standalone financing 

PE funds and outside investors are funding telco backed AI infrastructure 

ARPU analysis of Global telcos: H1-2026 

Telcos are adding satellite-to-phone service so that customers stop leaving over dead zones 

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AI compute and chips are undergoing rapid transformation as enterprises shift from a focus on peak training performance to a more nuanced approach that weighs workload requirements, utilisation economics, and infrastructure flexibility. The landscape now extends beyond general-purpose GPUs to include hyperscaler-designed silicon, specialised processors, and regionally controlled architectures. This evolution is driven by growing demand for inference, AI agents, real-time applications, and distributed deployment models, all of which are reshaping how compute is sourced and deployed.Key considerations now include not only processing power, but also cost per workload, energy efficiency, software compatibility, supply resilience, and long-term adaptability. Enterprises must evaluate chip architectures and suppliers across technical, financial, strategic, and operational dimensions, with an increasing emphasis on matching infrastructure to specific application needs rather than standardising on a single chip type.<ul><li>Coverage of general-purpose GPUs, custom cloud silicon, inference specialists, and regional AI chip providers</li><li>Analysis of workload-driven procurement strategies for AI infrastructure</li><li>Examination of supplier risk, software lock-in, and multi-chip strategies</li></ul>For CIOs and technology leaders, the central question is no longer which chip is the fastest, but which combination of compute, software, and supplier ecosystem best supports evolving business and AI workload requirements.<blockquote>How are enterprise AI infrastructure decisions shifting from performance-led to workload-led strategies, and what forces are redefining the AI chip market?</blockquote>

AI Compute & Chips​: Trends and analysis in a fast-evolving market​

Beyond Connectivity

Future Telco

Global telecommunications operators are navigating a period of significant transformation, as highlighted in the H1-2026 performance benchmark. The analysis covers global telco performance across revenue growth, capital expenditure, operational efficiency, and strategic shifts in service offerings. 

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Global telcos performance benchmark: H1-2026

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