BUSINESS TECH | Philippine firms face data bottleneck in scaling AI
The figures suggest that while businesses are experimenting with AI, integrating the technology into daily operations and scaling its use remain difficul
Philippine businesses seeking to expand their use of artificial intelligence (AI) face infrastructure challenges involving data storage, access, computing capacity and network performance, according to a commentary by Synology Philippines Country Manager Claire Huang.
A 2025 study on AI adoption in the Philippines found that 92% of organizations had used AI in some form over the previous year, while 65% remained at the proof-of-concept stage, Huang said.
The figures suggest that while businesses are experimenting with AI, integrating the technology into daily operations and scaling its use remain difficult.
Huang said data infrastructure is an important part of the equation because AI applications depend on access to the information needed for analytics, model training and other workloads.
Business data is often distributed across servers, cloud platforms, databases and applications accumulated during years of digital transformation. As organizations grow, managing these separate systems can make it harder to retrieve the right information when AI applications need it.
Fragmented data can also reduce the efficiency of computing resources when information is difficult to locate or slow to access.
A 2026 study conducted across Asia, including 62 Philippine organizations, found that 71% of respondents cited insufficient computing power, storage or network capacity as a barrier to advancing their AI initiatives. The same share reported that delays in accessing or moving data were already affecting performance.
Huang said growing data volumes also increase the need for storage, backups, protection and retention, potentially raising costs for businesses that rely heavily on subscription-based cloud storage.
She said companies should assess where their data is stored, how quickly it can be retrieved, how it is protected and how infrastructure costs may change as AI workloads expand.
This does not necessarily mean abandoning cloud services, Huang said. Businesses should evaluate which workloads are suited to the cloud and whether owning infrastructure offers greater control over frequently accessed or business-critical data.
Storage technologies and system architecture can also affect performance and availability. Huang cited NVMe storage for improving access to large datasets, active-active configurations for supporting service availability during component failures, and scalable capacity and centralized management for handling growing data volumes.
Synology’s PAS Series is designed around these requirements, combining an active-active NVMe architecture with scalable capacity and centralized data management to support business-critical data, according to the company.
As businesses move from AI experiments to operational applications, Huang said, establishing a reliable data foundation will be critical to scaling their use of the technology.
Full disclosure: All news articles published on the TechSabado website are written by human journalists, unless otherwise specified. Final text editing is also performed by human editors, with artificial intelligence (AI) used only to assist with additional grammar and style guide corrections..
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