Artificial intelligence is accelerating across the architecture, engineering, and construction industry, but many firms are trying to innovate on top of fragmented, unreliable data. Organizations cannot automate what they do not understand, and AI tools cannot scale when information is scattered across disconnected systems. This session explores how firms can prepare for artificial intelligence by first strengthening their data foundations through readiness, governance, and interoperability. Drawing on real-world experience leading enterprise technology strategy at a growing architecture and engineering firm, Brittany Pylant will share lessons learned from implementing ERP systems, navigating “single source of truth” challenges, and moving toward a hybrid data strategy that balances consolidation with purposeful integration.

Attendees will gain practical frameworks for evaluating data maturity, improving data hygiene, and aligning digital transformation with business objectives. The session also addresses the human side of data integration, including stakeholder buy-in, cultural alignment, and designing systems that reflect real workflows instead of forcing teams to work around technology. Participants will leave with actionable guidance for strengthening their firm’s data structures, supporting innovation responsibly, and preparing their organizations to scale AI with confidence.

Learner outcomes:

1. Recognize why effective AI initiatives in AEC depend on structured, governed, and connected data rather than isolated tools or one-off pilots.
2. Apply practical frameworks for assessing data maturity, improving data hygiene, and prioritizing integrations across enterprise and project systems.
3. Identify strategies to build stakeholder buy-in and align data and technology decisions with real workflows and firm-level business goals.