Executive Summary

This research was conducted during the ideation phase of My Stack.ai, an AI tool discovery platform designed to reduce overwhelm and improve the clarity of how users find, compare, and manage AI tools. With the rapid growth of the AI ecosystem, users face increasing challenges not only in discovering the right tools for their goals, but also in making sense of overwhelming options and inconsistent information.

To explore these challenges, a survey of 107 participants was conducted, covering a range of professions and student backgrounds. The survey aimed to identify user behaviours, emotional friction points, and unmet needs across the tool discovery journey. Importantly, it also validated three core feature directions for MyStack.ai:

• Drop (mood-based guided discovery),

• T-bot (chat-based assistant trained on real user reviews), and

• Stack (tool organisation and revisit system).

The findings reveal a diverse but converging set of needs among AI users, with particularly strong signals from high-stress single-tool users and cautiously engaged multi-tool users. Across the board, the report highlights a widespread appetite for more structured, explainable, and emotionally supportive discovery experiences — especially those that adapt to mindset, reduce decision friction, and offer trusted peer- or expert-informed recommendations.