Louis Landry on data
From Let's Blend podcast with Teradata CTO Louis Landry · · Teradata
“Data is what you pre-train these models on, post-train them with, and augment them with to solve real problems. Teradata's story is centered on integrating data and activating that data to generate business value.”
On , Louis Landry, Chief Technology Officer at TERADATA CORP, spoke about data during Let's Blend podcast with Teradata CTO Louis Landry on Teradata.
About Louis Landry
Louis Landry, Chief Technology Officer at Teradata, has been speaking publicly about the company's strategy for enterprise AI, emphasizing the importance of integrating data with AI systems to generate business value. In a series of appearances in 2025 and early 2026, Landry discussed the "enterprise AI paradox," arguing that the complexity of enterprise data, often seen as a liability, can become a competitive advantage when properly managed. He described Teradata's "open and connected philosophy" and its AI Factory, a solution that brings cloud-based AI capabilities to on-premises deployments, which he said addresses regulatory, economic, and asset utilization pressures. Landry also highlighted the shift from model-centric to data-centric AI thinking, stating that data quality and governance are where real value is unlocked. Landry has focused on the concept of "agentic AI," which he described as AI systems that not only analyze data but also act on it to drive decisions. He stated that organizations successfully deploying such systems are seeing significant returns, though he noted that most AI projects fail to scale beyond proof of concept. He stressed the need for a "knowledge layer" that understands business context, including regulatory requirements and operational constraints, to enable true AI autonomy. Landry also discussed the importance of trust in AI, cautioning that users should not blindly trust AI outputs and remain responsible for the outcomes they create. He characterized Teradata's role as helping enterprises "intersect their data with their AI ambitions" across cloud, on-premises, and hybrid environments.