Software Ate the World. Hardware Must Not Starve the Dream.
The choices leaders make about AI infrastructure will determine who can afford intelligence.
AI is often treated as a model-selection decision. But as intelligence becomes a metered, infrastructure-dependent resource, leaders face a more consequential question:
Who controls the cost curve?
The next AI divide may not be between organizations that have access to AI and those that do not. It may be between those able to follow a falling cost curve and those locked into one they cannot control.
In this Executive Perspective, I examine the infrastructure economics beneath AI and three decisions leaders need to make now: right-size the intelligence, place the workload deliberately, and preserve leverage.
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From Data Intelligence to AI
What the evolution of analytics, Big Data, Machine Learning, and AI taught me about creating business value from emerging technology.
Want to see the experience behind the perspective?
Explore the career journey across Business Analytics, Big Data, Machine Learning, and AI that shaped how I connect emerging technology to market adoption, commercial strategy, and business value.
Built through every era of data intelligence. Proven at enterprise scale.
Innovation creates possibility. Execution creates value.
I bring the technology context to understand what is possible and the GTM operating experience to turn that possibility into adoption, revenue, and scalable growth.
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