In short, their work outlines how they foresee AI assistants and agents playing a role in five different buckets of transaction types, from routine ones like grocery shopping where AI agents may execute a purchase when you’re close to running out of an item and the price drops to your preferred level (a modern version of price tracker camelcamelcamel perhaps), to functional purchases like an oven, or a bike for commuting, where specialized AI consultants might guide you toward the best purchase in exchange for a small fee.
“If you’re buying a bike for $3,500 that you’re going to use every day,” Moore told me, “and you have this AI coach who walks through with you exactly what you might need, based on all of these specifications, maybe you’re willing to throw an extra $50 that way, versus if you’re buying a $50 sweater, you’re probably not going to be willing to pay the AI.”
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