CRN Asia warns AI ‘bubble’ talk masks 2026 execution challenges

This round‑up is useful because it captures how Asia‑Pacific operators—not just model labs—see the next phase of AI. The consensus from Google Cloud, Lenovo, Cloudera and others is that 2026 won’t be about whether AI ‘bursts’ but about who can operationalize it: getting data quality, governance, security and power infrastructure to match the ambition of agents and copilots. Several leaders explicitly say “AI winter is not coming”; instead, poorly designed projects and frothy valuations will be culled while underlying adoption deepens.

For the race to AGI, that’s a sign the capital cycle is maturing rather than peaking. When boards start asking about unit economics—cost per bug fix, per feature, per fraud case prevented—attention shifts from headline benchmarks to long‑lived agents working safely against production systems. That dynamic is likely to drive investment into monitoring, identity, non‑human identity management and secure MLOps, areas repeatedly flagged in the piece.

It also highlights hard constraints: grid power and sustainability in markets like ASEAN, regulatory fragmentation and a shortage of AI‑literate talent. These are not existential threats to AI progress, but they will shape where agentic systems can be deployed fastest. The takeaway: AGI‑class models may keep arriving, but without disciplined operating models, many enterprises will fail to realize their potential.