A form of artificial intelligence oriented around the needs, preferences, and lived context of a single individual, designed to act as an ongoing cognitive partner rather than a general-purpose tool. Personal intelligence systems learn from a user’s history, communications, habits, and goals to provide tailored assistance such as organizing information, drafting messages, anticipating tasks, or making recommendations. Unlike broadcast or platform-scale AI, which optimizes for aggregate behavior, personal intelligence focuses on depth over breadth, adapting to one person’s values, voice, and decision patterns to extend their memory, attention, and problem-solving capacity.
In contemporary AI discourse, the term describes a shift from impersonal automation toward individualized augmentation, where models function as persistent companions or “digital doubles” that accumulate long-term context. Advocates frame personal intelligence as empowering, giving users more agency and leverage over complex systems, while critics raise concerns about surveillance, dependency, and the concentration of intimate data in private infrastructures. As such, personal intelligence sits at the intersection of assistance and identity, blurring the line between tool and proxy by acting not just for the user, but increasingly like the user.