Insights

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AI is becoming standard in CX; execution is becoming the differentiator. The competitive gap is shifting from who has the most AI features to who can connect intelligence across customer context, enterprise systems and workflows to resolve outcomes end to end.

The Twimbit AI-CX Vendor Landscape 2026 therefore evaluates vendors across both AI capability and innovation and market execution and adoption, revealing who can turn AI from impressive technology into scalable enterprise impact.

AI-CX Vendor Landscape 2026

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As digital channels reduce the need for customers to visit physical stores for basic service and support, telecom retail locations are being reimagined as brand experience centres rather than transactional points of sale. The shift accentuates the role storefronts play in shaping brand identity, even as routine account management and troubleshooting move online, pushing operators to rethink what a physical presence is actually for.
One of Japan's largest mobile carriers has responded by redesigning its retail footprint around experience-led concept stores open to anyone, not just existing subscribers. These spaces blend communication services with lifestyle content, hosting cafes, technology classrooms for smartphone users of all ages, cashless vending experiences and mobility services within a single location, deliberately serving children through elderly customers rather than a narrow demographic.
The retail strategy extends beyond the store itself into surrounding community services, including bike sharing, portable battery sharing and disaster-preparedness infrastructure such as backup power storage. This positions the storefront network as part of a broader community utility rather than a pure sales channel, a distinction increasingly important as digital transition reduces the commercial rationale for maintaining large physical networks.
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<li>How the operator segments in-store experiences across different age groups</li>
<li>The role of disaster-readiness services in extending brand relevance beyond retail</li>
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<blockquote>What happens to telecom retail once selling is no longer the primary reason for a store to exist?</blockquote>

Best In-store Experience 2022: NTT Docomo (Asia Pacific telecom service provider winners 2022)

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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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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​

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As digital channels reduce the need for customers to visit physical stores for basic service and support, telecom retail locations are being reimagined as brand experience centres rather than transactional points of sale. The shift accentuates the role storefronts play in shaping brand identity, eve

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Best In-store Experience 2022: NTT Docomo (Asia Pacific telecom service provider winners 2022)

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