Title of the Talk:

Navigating the Future: BI as the Control Architecture for AI

Abstract:

Artificial intelligence systems often fail not because of model limitations, but due to weak control over data, metrics, and decision pathways. This talk reframes Business Intelligence as the control architecture that governs AI systems in production environments. Instead of treating BI as a reporting layer, it positions BI as the mechanism that enforces consistency, observability, and trust across data pipelines and AI outputs.

Drawing from enterprise implementations using Microsoft Fabric, Power BI, and low-code platforms, the session presents a structured approach to managing data quality, metric definitions, and decision latency. It introduces practical constructs such as semantic models as control layers, governed metrics as decision contracts, and dashboards as operational feedback systems.

Attendees will examine how organizations improved data availability, reduced reporting inconsistencies, and established measurable control over AI-driven decisions. The focus remains on engineering discipline, governance, and system design rather than tooling alone. The session provides a clear framework for building AI systems that are measurable, auditable, and aligned with business outcomes.

Profile:

Milan Parikh is a Lead Enterprise Data Architect with 15 years of experience in enterprise architecture and digital transformation across life sciences, manufacturing, and financial services. At Cytel, he leads Microsoft Fabric and Power Platform architecture, translating complex data strategies into business outcomes. He holds fellowships from BCS and IETE, and is an IEEE Senior Member. An active contributor to global standards and professional communities, he serves as Secretary of the BCS Enterprise Architecture Specialist Group. He has advised Fortune 500 organizations and presented at international conferences on AI, data platforms, and digital transformation strategy.