The real breakthrough in AI won't come from pushing model sizes to the extreme—it'll emerge from solving the trust problem. Right now, enterprise adoption is bottlenecked by data reliability, not computational power. Companies need AI they can actually verify and audit, not just black boxes that spit out answers. Building trustworthy data infrastructure is where the next wave happens. That's why compliant, traceable data systems matter more than raw scalability. We're seeing teams focus on verifiable data pipelines, transparent provenance, and auditable AI workflows. This shift will define how enterprises adopt AI at scale—quality and integrity over hype.