For the last decade, the IT mantra was simple: "Move everything to the cloud." But as enterprises rush to adopt Agentic AI, they are hitting a wall. The surprising truth? Cloud migration alone is no longer enough for AI readiness.
A recent report reveals a major shift in enterprise thinking: 81% of CDOs state that modern AI works best when the architecture brings the AI to the data, not the other way around.
Data gravity is real. Enterprise data lives everywhere, on prem systems, legacy databases, SaaS apps, edge devices, and departmental tools. Trying to pipe all that data into a single cloud repository results in:
▪️High Costs: Massive egress and storage fees.
▪️Latency: AI can’t wait for nightly ETL jobs; it needs real-time access.
▪️Risk: Moving data creates compliance and security exposure.
The solution isn't to stop using the cloud, but to adopt a Hybrid-by-Design approach. This architecture allows:
▪️Data Residency: Data stays where it was generated (on-prem or edge).
▪️Portable Policy: Governance and access policies travel with the data.
▪️Distributed Workloads: AI models run wherever they are needed, central cloud for training, edge for inference.
Hybrid architecture pairs perfectly with Multimodal AI (AI that processes text, images, and audio simultaneously). Because multimodal data (like video footage or massive PDF repositories) is heavy, moving it is inefficient. Hybrid-by-Design allows AI to process this heavy data locally, unlocking:
▪️Real-time anomaly detection.
▪️Context-aware decisioning without latency.
▪️Richer predictions based on immediate data access.
As you adopt agentic systems, your architecture is your differentiator. Companies embracing hybrid-by-design will leapfrog those trapped in centralization by making their AI faster, cheaper, and safer.