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Cloud Maturity Is the Key to Unlocking AI in Banking
Across banks worldwide, AI initiatives have hit a standstill. Even as boards greenlight budgets, pilots unfold, and models deliver results, the anticipated shift in payments, credit decisions, and customer experiences remains elusive. The real roadblock lies not in AI itself but in the cloud platforms that should power it.
A global NTT DATA study, Cloud‑led innovation in the era of AI: The new rules for driving value with cloud, revealed that 98 % of banking and investment firms now see AI as a catalyst for greater cloud spend. Yet only 14 % view themselves as top‑tier cloud maturities. This mismatch between AI ambition and cloud readiness is why many pilots never scale.
AI’s effectiveness hinges on the environment that hosts it. A fraud‑detection model might spot a suspicious transaction in milliseconds, yet if the underlying system drags minutes to fetch data or fails to act instantly, the insight evaporates. True value emerges when the platform can immediately act on the model’s output.
Despite years of cloud migration, many banks still view the cloud merely as a hosting layer instead of an execution engine. Legacy systems stay fragmented, data siloed, and applications tightly coupled. Introducing AI brings the same integration barriers back into play. Half of the surveyed firms say that modernising applications and data platforms is the main obstacle to cloud innovation.
In the AI age, a modern cloud must simultaneously deliver: a real‑time data backbone that keeps information fresh; an execution platform that runs end‑to‑end intelligent workflows; and a governed, auditable environment that scales safely. Realising this demands cloud‑native design—event‑driven, modular architectures propelled by APIs that evolve without shaking the surrounding services.
Regulation now steers architectural choices. The EU’s Digital Operational Resilience Act (DORA) and India’s Digital Personal Data Protection Act (DPDP) obligate banks to prove that both their models and the environments they run in satisfy stringent resilience and privacy criteria. NTT DATA’s survey of AI leaders in banking finds that 62.5 % of firms list cross‑geography data privacy and sovereignty as their top governance priorities.
Consequently, 99 % of organisations in the cloud research anticipate a surge in private‑cloud adoption, driven by security, sovereignty, and compliance imperatives. Sovereign cloud uptake is expected to climb 50 % in the next two years.
When AI and cloud strategies are crafted in silos, a trio of problems emerges: AI ambitions outstrip what the platform can sustain; cloud investments lose clear business purpose; and scaling becomes slower, costlier, and harder to manage.
Top banks begin with the use case, designing architecture around AI workloads from day one. By aligning data, platforms, and governance early, they create AI that scales without friction.
Agentic AI systems—where an AI orchestrates documents, verifies, assesses, and approves loans with minimal human oversight—are already mainstream in lending. These workflows weave together multiple applications, data sources, and autonomous agents, making manual or disjointed management increasingly untenable.
The study finds that 62.5 % of banking and financial‑services AI leaders deploy hybrid models that blend plug‑and‑play solutions with selective co‑innovation. By contrast, only 29.2 % of laggards follow this path. Hybrid models usually combine hybrid cloud with targeted application adjustments, delivering: an end‑to‑end view of every system; governance embedded in decision execution; continuous cost visibility as AI workloads expand; and automation that sustains processes without constant human input.
Today, most banks have not yet reached a stage where cloud serves as the execution layer for AI. To shift this reality, leaders need to view infrastructure as the bedrock of how the bank operates and expands, unlocking swifter innovation and healthier margins.
NTT DATA’s report, Cloud‑led innovation in the era of AI, provides a benchmark that lets organisations gauge their cloud maturity and spot gaps. When banks align cloud and AI strategies, they can unlock AI’s full potential while satisfying regulatory and security demands.
This article was co‑authored by Kane Stavens, Managing Director: Asia Pacific at NTT DATA.
A global NTT DATA study, Cloud‑led innovation in the era of AI: The new rules for driving value with cloud, revealed that 98 % of banking and investment firms now see AI as a catalyst for greater cloud spend. Yet only 14 % view themselves as top‑tier cloud maturities. This mismatch between AI ambition and cloud readiness is why many pilots never scale.
AI’s effectiveness hinges on the environment that hosts it. A fraud‑detection model might spot a suspicious transaction in milliseconds, yet if the underlying system drags minutes to fetch data or fails to act instantly, the insight evaporates. True value emerges when the platform can immediately act on the model’s output.
Despite years of cloud migration, many banks still view the cloud merely as a hosting layer instead of an execution engine. Legacy systems stay fragmented, data siloed, and applications tightly coupled. Introducing AI brings the same integration barriers back into play. Half of the surveyed firms say that modernising applications and data platforms is the main obstacle to cloud innovation.
In the AI age, a modern cloud must simultaneously deliver: a real‑time data backbone that keeps information fresh; an execution platform that runs end‑to‑end intelligent workflows; and a governed, auditable environment that scales safely. Realising this demands cloud‑native design—event‑driven, modular architectures propelled by APIs that evolve without shaking the surrounding services.
Regulation now steers architectural choices. The EU’s Digital Operational Resilience Act (DORA) and India’s Digital Personal Data Protection Act (DPDP) obligate banks to prove that both their models and the environments they run in satisfy stringent resilience and privacy criteria. NTT DATA’s survey of AI leaders in banking finds that 62.5 % of firms list cross‑geography data privacy and sovereignty as their top governance priorities.
Consequently, 99 % of organisations in the cloud research anticipate a surge in private‑cloud adoption, driven by security, sovereignty, and compliance imperatives. Sovereign cloud uptake is expected to climb 50 % in the next two years.
When AI and cloud strategies are crafted in silos, a trio of problems emerges: AI ambitions outstrip what the platform can sustain; cloud investments lose clear business purpose; and scaling becomes slower, costlier, and harder to manage.
Top banks begin with the use case, designing architecture around AI workloads from day one. By aligning data, platforms, and governance early, they create AI that scales without friction.
Agentic AI systems—where an AI orchestrates documents, verifies, assesses, and approves loans with minimal human oversight—are already mainstream in lending. These workflows weave together multiple applications, data sources, and autonomous agents, making manual or disjointed management increasingly untenable.
The study finds that 62.5 % of banking and financial‑services AI leaders deploy hybrid models that blend plug‑and‑play solutions with selective co‑innovation. By contrast, only 29.2 % of laggards follow this path. Hybrid models usually combine hybrid cloud with targeted application adjustments, delivering: an end‑to‑end view of every system; governance embedded in decision execution; continuous cost visibility as AI workloads expand; and automation that sustains processes without constant human input.
Today, most banks have not yet reached a stage where cloud serves as the execution layer for AI. To shift this reality, leaders need to view infrastructure as the bedrock of how the bank operates and expands, unlocking swifter innovation and healthier margins.
NTT DATA’s report, Cloud‑led innovation in the era of AI, provides a benchmark that lets organisations gauge their cloud maturity and spot gaps. When banks align cloud and AI strategies, they can unlock AI’s full potential while satisfying regulatory and security demands.
This article was co‑authored by Kane Stavens, Managing Director: Asia Pacific at NTT DATA.
