When AI Becomes More Affordable, Measuring Value Gets Harder
As AI gets more affordable, it makes valuing it more challenging.
Running AI is now much more cost-effective. More workloads are economically viable as the leading model providers continue to lower their inference costs and increase their available choices of models. However, cheaper does not necessarily equate to less spent on enterprise AI. The more we use models, have more context, utilize tools, compare, try things out and retest, and more independently work.
This reflects the trend of the cloud era when the reduced infrastructure costs allowed adoption to begin on a wide scale but ultimately led to a new cost-management issue. AI is on the same trajectory. For the technology leaders, it’s no longer about the cost of an AI interaction, it’s about what business outcome the AI workflow produces and what did it cost to deliver?
The Economics of AI is Changing.
The competition from top providers...
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