Automation vs. AI: A practical decision framework for PMs

In the rapidly evolving landscape of AI, product managers face the challenge of determining when to implement AI solutions versus traditional automation. The blog suggests a practical decision framework that emphasizes intentionality in choosing between deterministic automation, which is predictable and rule-based, and probabilistic AI, which is adaptable but inconsistent. Automation is recommended for scenarios where rules are stable, errors have high consequences, and explainability is required, while AI is more suitable for problems requiring interpretation, frequent rule changes, or handling unstructured data. The article underscores the importance of understanding the trade-offs and using product judgment to discern when AI adds value, advocating for a balanced approach rather than defaulting to AI due to its novelty.

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