Building the case for specialized AI
Ask any business what it actually does and the answer is almost always specific. A quarrying company extracts rock. A peatland conservation organization restores peatlands. A retailer sells items. The answer is not "we send emails" or "we have meetings."
This distinction between what makes a business unique and the common operations surrounding it has always mattered. More than two centuries ago, Adam Smith recognized that productivity comes from specialization.
Workers focusing on narrow tasks consistently outperformed generalists, and economies grew by dividing labor into ever finer slices. Businesses succeeded not by doing everything, but by becoming exceptionally good at one thing.
Founder and Managing Director of New Gradient.
Artificial intelligence (AI) doesn’t change this principle. If anything, it reinforces it. So why does much of today’s AI discussion assume the opposite?
The prevailing belief is that increasingly capable general-purpose models will eventually become the best solution for almost...
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