This new reality is forcing organizations to undertake careful assessments before making platform decisions for AI. The days when IT leaders could simply sign off on wholesale cloud migrations, confident it was always the most strategic choice, are over. In the age of AI, the optimal approach is usually hybrid.
Having openly championed this hybrid path even when it was unpopular, I welcome the growing acceptance of these ideas among decision-makers and industry analysts. Enterprises now have a rationale for an integrated, best-of-both-worlds platform, not as a retreat from cloud, but as a progression toward mature, sustainable AI. Hybrid approaches allow organizations to optimize costs, address regulatory and latency needs, and retain vital security controls, while also continuing to leverage the cloud’s strengths for experimentation and growth.
Artificial intelligence, with its intense resource demands and complex risk profile, has normalized a pragmatic approach to platform architecture. Ignore the rhetoric. Hybrid is the future for organizations that intend to scale AI, strike the right cost-performance balance, and adapt to ever-changing requirements. With authoritative references both validating and reinforcing this view, it’s clear that what was once dissent is now fast becoming conventional wisdom. I’m pleased to witness this change. Proof that the path to successful AI lies not in cloud-only solutions, but in the thoughtful combination of cloud and non-cloud strategies.
