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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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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Malaysia's top banks navigated a mixed FY-2023, with net interest income pressured even as non-interest income and fee-based revenue expanded across much of the sector. Net revenue, profitability, margins, asset quality, and loan growth mark the comparison across the country's nine leading banks, including Maybank, CIMB, Public Bank, RHB, Hong Leong Bank, AMMB, Alliance Bank, Affin Bank, and Bank Islam.
Performance diverged sharply by institution: some banks grew net revenue and fee income through gains in investment and foreign exchange income, while others faced steep declines tied to weaker net interest and non-interest income. Shifts in net interest margin and changes in cost efficiency across the Malaysian banking sector explain much of that divergence.
Loan portfolios and deposits expanded across Malaysia's banking system during the year, with some institutions posting notably stronger profitability trends than others. Cost efficiency ratios moved in different directions from bank to bank, reflecting how each institution balanced technology investment against branch network rationalisation amid a slower revenue environment. It is built for banking analysts and investors benchmarking Malaysian financial institutions against regional peers.
<ul>
<li>Bank-by-bank breakdown across nine major Malaysian banks</li>
<li>Net interest margin and non-performing loan trends</li>
<li>Fee income and non-interest income growth drivers</li>
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<blockquote>Which Malaysian banks best converted fee income and cost discipline into profit growth in FY-2023?</blockquote>

Malaysia's leading banks: FY-2023 update

Net revenues for the top 9 Malaysian banks declined by 1.6% YoY

Net profits for the top 9 Malaysian banks grew by 6% YoY

Fee income for the top 9 Malaysian banks grew by 3.6% YoY

Average NIM declined by 25 basis points in FY-2023

Average NPL improved by 2 basis points in FY-2023

CE for the top 9 banks in Malaysia declined by 265 basis points between FY-2022 and FY-2023

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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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Malaysia's top banks navigated a mixed FY-2023, with net interest income pressured even as non-interest income and fee-based revenue expanded across much of the sector. Net revenue, profitability, margins, asset quality, and loan growth mark the comparison across the country's nine leading banks, in

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Malaysia's leading banks: FY-2023 update

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