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.
The AI Free Ride is Ending
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There’s a meme that’s been doing the rounds recently that shows a text message from someone’s significant other, who has noticed a $15k withdrawal from their joint bank account and assumes it’s for an engagement ring. Below that is the punchline - a screenshot of an Anthropic bill for $15k. Some people are now spending so much on AI that their “oh crap” billing moments have become a running joke. But if you think things are bad now, it’s only going to get worse. We are currently living through a period of subsidised intelligence. This year, for example, OpenAI is projected to lose $14 billion and isn’t expected to reach positive cash flow until around 2029 or 2030. Yet, the AI companies aren’t giving the world access to their models out of the goodness of their hearts. Both OpenAI and its rival, Anthropic, are expected to launch IPOs within the next year. Once there are public shareholders to answer to, it’s only a matter of time before the cost of using AI models starts going up. And any organisations or data professionals developing AI initiatives based on today’s pricing are going to be in for a nasty shock. In the latest Value Boost episode of Value Driven Data Science, Nicholas Kelly, author of The AI-Driven Data Team, returns to explore why organisations shouldn’t be building their AI future entirely on rented intelligence, and what data professionals need to understand to be the strategic voice in the AI infrastructure conversation. In just 14 minutes, you’ll learn:
The free ride won’t last forever. The data professionals who understand what comes next will be the ones organisations turn to when it ends. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 116: What Data Scientists Need to Know Before the AI Free Ride Ends 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.
When I’m looking for guests for my podcast, the first place I turn is invariably my bookcase. The authors of data science books have already demonstrated their authority in the field to the point of developing their own original IP. That makes them ideally suited to a podcast about data science expertise. And it’s no coincidence that many of those authors started off by writing blogs. It turns out conference organisers do something similar. When Cynthia Dunlop, who helps organise two major...
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