Organizations are rapidly accelerating investments in artificial intelligence, analytics, automation and modern data platforms. Yet many continue to struggle to turn those investments into sustainable business value. Insights from RSM’s 2026 AI survey highlight why: Leaders consistently cite data quality, integration and governance as the primary barriers to scaling AI and analytics.
Join RSM’s data analytics, risk and tax leaders for a discussion on why data foundations serve as the operating layer behind modern business performance. This session will focus on the foundational capabilities organizations must get right first—and how these capabilities must work together to enable trusted insight, reliable reporting, regulatory readiness and scalable performance.
The discussion takes a cross-functional view to address integration, master data management, data strategy and governance, and modern data architecture and analytics. It will also highlight why tax, risk and regulatory considerations are increasingly shaping data foundation requirements. You’ll gain clarity on where data initiatives most often break down and how a data-first approach can help your organization scale with confidence.
Key takeaways:
- Understand why data quality, integration and governance are the primary inhibitors to scalable AI.
- Learn how data foundations function as a single enterprise operating layer rather than a collection of disconnected capabilities.
- Explore where organizations should start to build momentum without creating fragility.
- Discover the tax, risk and regulatory considerations that raise the bar for trusted data.
- Gain insights into how a foundational, data-first approach supports speed, confidence and growth.
