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The Cost of AI Features (Spoiler: It Adds Up)
Alright, PMs, let's talk money. AI features are like that fancy avocado toast — looks great, but the bill can surprise you. Understanding the true cost of AI features is crucial to making strategic decisions in your product roadmap. Today, we're diving into the dollars and cents of AI.
Development Costs
First up, development costs. You don't just snap your fingers and get an AI model. It's more like assembling IKEA furniture — you need time, resources, and the occasional swear word.
- Data Acquisition: AI models feast on data. Depending on your feature, you might need to buy datasets, which can be pricey. Even if you're using your own data, cleaning and labeling it isn't free.
What comes next
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Talent: AI talent doesn't grow on trees. You'll need data scientists, machine learning engineers, and maybe even a few unicorns to get things rolling.
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Infrastructure: Training models require serious computing power. Whether you're using cloud services or on-prem hardware, these costs add up faster than your UberEats tab on a Friday night.
Operational Costs
Once your feature is live, the costs don't magically disappear. Welcome to the world of operational costs.
Finish: The Cost of AI Features (Spoiler: It Adds Up)
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