Artificial Intelligence

Magnetic tape has been declared obsolete approximately once per decade since the 1980s. And yet, in 2026, tape remains in active operation across a substantial fraction of large enterprise environments—not for primary storage, where flash and disk have comprehensively won, but for long-term archival of compliance data, backup archives, and decades of accumulated historical records. […]

Before the Model Context Protocol (MCP), enterprise AI governance faced a fundamental architectural problem: AI agents accessed data through dozens of custom integrations, direct database connections, REST API calls, and SDK-based queries—each with its own authentication, its own data retrieval logic, and its own (usually absent) governance configuration. Enforcing consistent access controls, masking, lineage capture, […]

Every enterprise transformation initiative of the past decade has included “AI” somewhere in its vision statement. Very few have included a serious accounting of the data infrastructure transformation that AI production actually requires. The result is a growing gap between AI ambition and AI reality—a gap that is becoming more visible, more expensive, and more […]

Enterprise analytics has gone through three generations in forty years. Operational reporting. Business intelligence and OLAP. Self-service analytics and machine learning at scale. Each generation delivered genuine productivity gains—but each also arrived with a hidden constraint: it was built on a data platform designed for the workloads of its era, not the workloads of the […]

La question n’est plus de savoir si la souveraineté des données IA Canada est une priorité stratégique. Elle l’est. La question est désormais de savoir à quelle vitesse les organisations canadiennes peuvent aligner leur infrastructure d’intelligence artificielle sur cette réalité réglementaire et géopolitique incontournable. Pourquoi les protections contractuelles ne suffisent plus Pendant des années, les […]

Every model inference generates data. Every RAG pipeline retrieval writes metadata. Every agentic workflow produces a timestamp, an input record, a confidence score, and a lineage entry. Multiply that footprint across thousands of daily users and dozens of enterprise AI applications, and the result is an operational data mountain that most IT organizations were never […]

Enterprise AI spending is accelerating, but results are not. Analyst data shows that the overwhelming majority of AI pilot programs never produce measurable financial impact, leaving boards in a holding pattern that industry observers now call AI pilot purgatory—the costly limbo between a promising proof of concept and a production system that moves the P&L. […]

La Phase Pilote Est Devenue un Piège Stratégique La question de la préparation des institutions financières canadiennes à l’IA en production est devenue la priorité stratégique la plus urgente d’un secteur qui a consacré des ressources considérables aux projets pilotes sans atteindre une déploiement à grande échelle. Les conseils d’administration des banques, assureurs et coopératives […]