Insights

ai-cxvendorlandscapeslide01png-1790182040211

slide-04png-1789984218287

slide-03png-1789984218287

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

State-of-Indian-bank_Instabits-1

State-of-Indian-bank_Instabits

Slide2-4

Slide3-4

India's banking sector is shifting from a recovery narrative into one focused on sustained growth. Projected GDP and credit growth for the coming fiscal year, the impact of Reserve Bank of India rate hikes on government security yields and bond investors, and how rising interest rates are flowing through to net interest margins across major Indian banks all shape that transition.
Operating revenue, fee income, and return on equity for leading Indian banks are benchmarked against Asia Pacific averages, identifying which institutions are leading on digital-driven fee income and why. Structural challenges also loom, including margin compression, rising operating costs tied to aggressive branch expansion, and how banks like ICICI, Kotak, Axis, IndusInd, and HDFC are each pursuing distinct digital transformation strategies, from super-app style retail platforms to embedded banking APIs for MSMEs.
Looking forward, growth opportunities centre on branch network optimisation, ecosystem partnerships that diversify fee income beyond interest revenue, and lending growth across retail, MSME, and corporate credit segments through the rest of the forecast period.
<ul>
<li>Benchmarks operating revenue, fee income, and ROE across major Indian banks</li>
<li>Profiles distinct digital transformation strategies at ICICI, Kotak, Axis, IndusInd, and HDFC</li>
</ul>
<blockquote>What will determine whether India's banks can convert a strong recovery into durable, diversified growth?</blockquote>

State of Indian Banks 2023 – From Recovery to Growth

slide1jpg-1791788242676

slide1jpg-1791788281589

slide2jpg-1791788294216

slide3jpg-1791788306256

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

slide1jpg-1791365595650

slide1jpg-1791365755400

slide2jpg-1791365977433

slide3jpg-1791365988491

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​

Customer Experience

bankoftomorrow

India's banking sector is shifting from a recovery narrative into one focused on sustained growth. Projected GDP and credit growth for the coming fiscal year, the impact of Reserve Bank of India rate hikes on government security yields and bond investors, and how rising interest rates are flowing th

Feed

Buddy

Events

Blogs

State of Indian Banks 2023 – From Recovery to Growth

Summary