In an exclusive interview with Rishi Mehtani, Vice President and Head, Technology License and Multicloud, Oracle India, insights emerged on how Oracle’s multicloud strategy is helping enterprises overcome one of the biggest barriers to AI adoption—data gravity.
As enterprises accelerate their AI ambitions, one constraint continues to dominate boardroom conversations: data gravity. Moving large volumes of enterprise data across environments is not only expensive but also introduces latency, governance risks, and operational complexity.
Oracle’s multicloud strategy is designed to address this challenge head-on—by bringing AI to the data, rather than moving data to AI.
At its core, Oracle’s multicloud solutions enable organizations to run data, analytics, and AI workloads across Oracle Cloud Infrastructure (OCI) and other hyperscalers, while maintaining performance, governance, and flexibility. This approach is increasingly becoming critical as enterprises adopt hybrid and distributed architectures.
Placing Oracle’s database services where enterprise applications and operational systems already live, Oracle eliminates the three most common barriers to cloud data adoption: latency, migration risk, and organizational resistance. Enterprises no longer need to choose between their existing Oracle investments and their preferred hyperscaler — they get both, seamlessly.
Reimagining Where AI Meets Data
A key advantage of Oracle’s multicloud solutions lies in their ability to place workloads where they perform optimally. Through high-bandwidth and, low-latency private interconnects with major cloud providers, enterprises can minimize delays typically associated with cross-cloud data movement.
This enables flexible architectural patterns—organizations can choose to keep sensitive data within Oracle environments while leveraging AI services in other clouds or run AI workloads directly where the data resides. The result is faster model training, real-time inference, and improved application performance without the burden of continuous data replication.
“The biggest shift we’re seeing is a move away from ‘moving data to AI’ towards ‘bringing AI to where the data already lives’. That’s where multicloud becomes a strategic enabler,” says Mehtani.
Building an AI-Ready Data Foundation
AI success depends heavily on the strength of the underlying data architecture. Oracle’s multicloud solutions support modern, hybrid data foundations by integrating Oracle AI Database and Exadata with cloud-native analytics ecosystems.
This allows enterprises to create unified data pipelines, real-time ingestion frameworks, and scalable lakehouse or warehouse models—all essential for reliable AI deployment. By ensuring high data quality and consistency, organizations can move from experimentation to production-grade AI projects with greater confidence.
“AI outcomes are only as strong as the data foundation behind them. What multicloud enables is consistency—across pipelines, governance, and performance—without forcing consolidation into a single environment,” he explains.
Flexibility Without Fragmentation
One of the long-standing challenges in multicloud adoption has been balancing flexibility with operational complexity. Oracle’s approach enables best-of-breed choices without forcing trade-offs.
Enterprises can continue to rely on Oracle for mission-critical data while leveraging other clouds for specialized AI services, developer ecosystems, or GPU-intensive workloads. This eliminates the “either-or” dilemma and allows workload placement based on performance, cost, and compliance requirements.
Governance and Security at the Core
In an AI-driven world, security and governance need to be built in from the start. Oracle’s multicloud solutions focus on layered security, combining built-in protections with consistent controls across different cloud environments.
Features such as in-database SQL firewall, default encryption with Transparent Data Encryption (TDE), centralized identity integration, and robust key management help protect sensitive data. At the same time, with the right identity and security controls in place, enterprises can enforce consistent policies, maintain auditability, and support Zero Trust architectures. .
This approach allows organizations to expose data to AI systems through controlled access mechanisms—APIs, queries, and services—rather than uncontrolled data copies, significantly reducing risk.
“Enterprises don’t just need AI—they need AI they can trust. That means consistent security, auditability, and control across every environment where data and models interact,” notes Mehtani.
Oracle can embrace openness without abandoning its traditional strengths in security and governance – an advantage in regulated sectors and for large enterprises that will remain hybrid for years.
Bringing AI to the Data
To address data gravity, Oracle’s multicloud solutions promote architectural patterns that minimize unnecessary data movement.
For instance, in Retrieval-Augmented Generation (RAG) use cases, enterprises can keep authoritative data within Oracle systems while sharing only derived elements such as embeddings or curated datasets with AI applications. Similarly, batch AI workloads can be executed where the data resides, with only model outputs being transferred across environments.
Co-located deployments, such as Oracle AI Database services integrated with hyperscaler ecosystems (Oracle AI Database@Azure, Oracle AI Database@AWS, Oracle AI Database@Google Cloud), further reduce latency and enable seamless interaction between data platforms and AI services.
Performance, Resilience, and Scale
Oracle Cloud Infrastructure is widely used for high-performance database and enterprise workloads, and multicloud extends this capability by integrating external innovation.
Organizations can design resilient architectures with cross-cloud redundancy, ensuring business continuity even in the event of failures. Oracle’s Maximum Availability Architecture (MAA) and Zero Data Loss Recovery solutions further strengthen reliability, enabling rapid recovery with minimal data loss in well-architected environments.
Driving Cost Efficiency
Beyond performance, cost optimization remains a major driver for multicloud adoption. Oracle’s architecture helps enterprises minimize expensive data egress and duplication, while also reducing operational overhead through automation and converged database capabilities.
Enterprises can leverage:
- Existing cloud commitments through hyperscaler marketplaces
- Bring Your Own License (BYOL) models
- Oracle Support Rewards to offset costs
- Higher consolidation density with Exadata
Together, these factors contribute to lower total cost of ownership and improved financial predictability.
The Multicloud Advantage for Indian Enterprises
For Indian enterprises, the benefits of multicloud are particularly tangible. Organizations operating in regulated sectors such as BFSI, telecom, and public services can better align with data residency and compliance requirements while still accessing global innovation.
Additionally, multicloud enables:
- Stronger resilience for customer-facing digital services
- Cost-performance optimization through intelligent workload placement
- Faster modernization without disruptive “big bang” migrations
- Accelerated AI adoption by addressing data gravity challenges
As enterprises increasingly operate across on-premises and multiple cloud environments, Oracle’s multicloud solutions provide a pragmatic path forward—balancing innovation with control.
“In markets like India, multicloud is less about choice and more about necessity—balancing regulation, cost, and innovation while working with highly distributed data environments,” adds Mehtani.
Ultimately, the shift toward multicloud reflects a broader evolution in enterprise IT—from centralized systems to distributed, intelligent ecosystems. By enabling organizations to align AI strategies with where their data actually resides, Oracle is positioning multicloud as a critical enabler of scalable, responsible AI.
As AI adoption deepens, strategies that reduce friction between data and intelligence will define competitive advantage—and multicloud is fast emerging as a cornerstone of that transformation.
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