FRASER HILL
AI STRATEGY
FRASER HILL
TITLE: VICE PRESIDENT INTERNATIONAL DIGITAL ENABLEMENT
COMPANY: LOCKHEED MARTIN
INDUSTRY: AEROSPACE & DEFENSE
Three steps for success with Gen AI at scale Jim Rowan, Applied AI leader at Deloitte Consulting, said last year that organisations have“ arrived at a pivotal moment for Gen AI, balancing leaders’ high expectations with challenges such as data quality, investment costs, effective measurement and an evolving regulatory landscape.”
Through trial and often expensive error, Fraser’ s team identified three non-negotiable requirements for AI success at scale. The first? High-quality data.“ If your data are pretty mucky, if they are not accessible, they are virtually useless,” Fraser emphasises. His first recommendation?“ Make sure that you have a world-class chief data officer who’ s building governance structures around data.”
The challenge resonates across industries. Deloitte’ s research identifies“ lack of clear data strategy” as one of four critical barriers to Gen AI success, noting that“ Gen AI strategies may struggle without a clear data architecture that cuts across types and modalities, accounting for data diversity and bias.”
The stakes are higher in defense applications, but the principle applies everywhere. When Lockheed Martin’ s AI systems must process massive data volumes to provide“ actionable intelligence” in life-or-death situations, poor data quality isn’ t just inefficient but can mean mission-critical failure.
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