AI Data Movement Challenges Revealed in Global Research
According to reports from Riverbed’s 2025 Global AI Research, three-quarters of 1,200 surveyed organizations plan to establish an AI data repository strategy, with 90% identifying data movement as vital to their AI success. The research indicates that just 10% of AI projects progress beyond pilot mode into full enterprise deployment, with analysts suggesting that data quality issues and slow data movement represent significant barriers.
Oracle-Integrated Solution for Accelerated AI Implementation
Riverbed has launched its Data Express Service deployed on Oracle Cloud Infrastructure (OCI) to address these challenges. Sources indicate the service aims to provide faster, more secure methods for moving massive datasets required for AI initiatives. “Customers are looking for faster, more secure ways to move massive datasets so they can bring AI initiatives to life,” said Sachin Menon, Oracle’s vice president of cloud engineering, in an official statement. The service reportedly accelerates time to value while reducing costs and maintaining data protection.
Advanced Security and Performance Architecture
The Riverbed service utilizes post-quantum cryptography to secure petabyte-scale datasets through encrypted VPN tunnels, according to technical documentation. “The time for preventing harvest-now, decrypt-later is now,” company representatives stated, referring to the emerging security threat where encrypted data is intercepted for future decryption once quantum computers achieve sufficient power. The technology builds upon Riverbed’s SteelHead acceleration platform running RiOS 10 software, with cloud-optimized design delivering higher data retrieval, movement, and write rates.
Multi-Cloud Orchestration and Deployment Timeline
While initially deployed on Oracle Cloud Infrastructure, the service will eventually orchestrate data movement across AWS, Azure, and Google Cloud Platform, as well as on-premises data centers. This expansion reflects broader industry developments in hybrid and multi-cloud strategies. General availability is planned for Q4 2025, according to the company’s announcement, positioning it alongside other emerging technology solutions addressing AI infrastructure challenges.
Broader Industry Context and Implications
The launch occurs amid significant market trends in technology valuation and increasing enterprise investment in cloud computing infrastructure for AI workloads. Industry observers note parallel related innovations in data security and movement across sectors. According to the full company announcement, the service specifically targets use cases spanning AI model training, inference operations, and emerging agentic AI applications, addressing what analysts suggest is a critical bottleneck in enterprise AI adoption.
Looking Ahead: As organizations increasingly prioritize AI implementation, solutions addressing data movement challenges are becoming essential components of enterprise technology strategy. The Riverbed service represents one approach to overcoming these hurdles while preparing for future security threats in the quantum computing era.
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