Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
What the ML Wave Taught Us About AI
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Ten years ago, everyone wanted to be doing machine learning. Go to a data conference - someone was presenting on ML. Advertising a data role - just mention ML and applications would 10X. It was the promise of machine learning that inspired an entire generation of data scientists. I know. I was one of them. And then came the statistic that revealed what many data scientists knew but few wanted to admit: around 90% of ML initiatives never made it to deployment. The ideas were there. The enthusiasm was there. The technology was there. What wasn’t there was the strategic foundation to turn any of it into something real. For those of us who were around ten years ago, the current AI wave feels like history repeating itself - only bigger and faster. Every organisation has an inventory of AI ideas. Very few have a way to get them off the ground. In the latest episode of Value Driven Data Science, Santosh Kaveti, CEO and founder of ProArch, joins me to share what organisations consistently get wrong when embarking on AI initiatives, and what data scientists can do to help get it right. In this episode, you’ll discover:
The ML wave delivered just 10% of what it promised. This episode is about making sure history doesn’t repeat. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 105: From AI Idea to Production Reality Talk again soon, Dr Genevieve Hayes |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
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