The greatest challenge in using any Generative AI today is a peculiar one: you must know what you want to know. This presents a strange paradox. If you are aware of a specific gap in your knowledge, what you actually need is a reliable knowledge source. This could be a search engine, an internal wiki, or even a trusted colleague. The path to the answer is relatively straightforward.

The real problem emerges when you don’t even know the right questions to ask. You sense a problem or a need, but its shape is undefined, its boundaries are fuzzy. In such moments, you need more than an oracle; you need a guide who can ask you probing questions to help you articulate your own need. A vanilla LLM interaction, which waits passively for a prompt, is fundamentally insufficient for this. This is where the true potential of AI begins to shine. The challenge is particularly acute within an enterprise, a restricted data environment where context is everything. Here, the correct answer to a single question can differ dramatically based on the asker’s role, their department, location, and specific authorisations.

An LLM, for all its knowledge, knows what it knows; it remains oblivious to what you know or, more importantly, what you truly need to know. A genuinely helpful AI response, therefore, must be born from a dialogue. The system shall learn to clarify and differentiate between what a user has asked and what they actually require. This is the subtle but profound shift from a tool that gives answers to a partner that helps formulate the questions.

Agentic AI systems represent the first concrete step in this direction. However, the true leap will happen when these systems evolve beyond mere self-reasoning—explaining their own logic—to embrace counter-reasoning. Imagine an AI that doesn’t just process your query but gently challenges its premise, questions your assumptions, and helps you see the problem from a new vantage point. When our digital counterparts can engage in this level of intellectual partnership, we will begin to see the first visible patterns of a coming super-intelligence.