Translating high-risk AI requirements into system architecture, data lineage, and lifecycle controls before August 2026 enforcement.
Who owns AI value creation, who kills non-scaling pilots, and how outcomes are measured beyond experimentation.
Resolving ownership, quality, and governance in federated data environments where political dysfunction blocks AI at scale.
Scaling AI, data, and application delivery without scaling complexity, headcount, or technical debt.
Reducing application sprawl, vendor complexity, and technical debt to free budget and capacity for AI, compliance, platform modernization, and innovation.
Digital Sovereignty Decisions
Balancing control, economics, and strategic flexibility in cloud and hybrid strategies under regulatory pressure and vendor dependency.
Reducing operational load through AIOps and intelligent automation while maintaining human oversight, explainability, and accountability.
Operating Models and Accountability in the AI Era
