The #1 Use of AI Is Companionship. Aga Thinks That's a Leadership Problem.

The most fundamentally human thing we do is ask to be understood. In 2026, more and more of us are asking a machine.

Aga Pociecha came across a Harvard Business Review study that ranked over 12,000 real AI use cases by frequency, and the result stayed with her. The number one use case was not productivity. Not coding. Not data analysis. It was therapy and companionship — people taking the most human need they have, the need to feel heard, to an algorithm.

As Strategic Development Partner at Sigrix, Aga spends her days close to what AI can do at the top of its range. So her reaction to that finding is worth paying attention to, because it is not the reaction you would expect from someone whose work is built on the technology.

She does not think the story is about AI at all. She thinks it is about us.

The uncomfortable question sits with leaders, not machines

If people are taking their fears, their doubts, their relationship problems and their need for connection to software, Aga's question is a blunt one: what does that say about the environments we are building?

That question, she argues, is more uncomfortable than anything a model can generate. And it is the one leaders should be sitting with right now — instead of the easier debates about tools and features.

Writing this from an AI marketplace is the point, not a contradiction

For many people, a Sigrix partner writing about the limits of AI on an AI platform might sound counterintuitive. Aga sees it the other way around.

The whole premise of Sigrix is that AI works best when humans direct it with intention. Every listing on the marketplace is verified by a person before it goes live — not because AI cannot be powerful, but because that power is only useful when it is guided by human judgment, human context and human accountability. For Aga, that is not a compromise position that softens the pitch. It is the position.

How Aga actually uses AI

Her own use cases are deliberately unglamorous. She uses AI to:

• Challenge her approach to projects
• Pressure-test ideas before they go in front of people
• Automate the tasks that eat time without creating value

She organises her AI conversations by project, tracks progress there, and treats the tool as a capable assistant and a thinking partner.

But there is a line she does not cross. When she needs to really talk something through — when the decision matters, when a relationship is at stake, when the room needs to be read — she turns to people. Every time. For Aga that is not sentiment. It is strategy.

Why wisdom is the part that doesn't scale

A line from a leadership workshop has stayed with her since.

Intelligence is cheap. Wisdom is not.— a line Aga picked up in a leadership workshop

AI can process. It can pattern-match. It can produce, at remarkable speed, outputs that look like insight. What it cannot do is generate wisdom — the kind that reads a room, knows that what someone said is not what they meant, and understands that the right answer in a given moment is silence.

There is a well-worn figure most people in leadership roles know: 55% of communication comes through body language, 38% through tone of voice, and only 7% through words. The precise percentages are debated, and Aga is careful to say so, but the principle holds. Most of what passes between people when something important is being communicated is not in the transcript. It is in the hesitation before an answer, the energy in the room when a decision lands, the thing nobody said but everyone felt. A model cannot read that — and any leader who hands that interpretation to a machine is outsourcing the most important part of the job.

The shift Aga is betting on

None of this makes AI the enemy in Aga's telling. Quite the opposite.

Used well, she argues, it is one of the most significant productivity tools leaders have ever had. It can compress the hours spent on analysis, briefing, drafting and research, and give that time back for the things that actually require a human: more real conversations, more presence, more of the leadership no algorithm can replicate.

That is what she is building toward at Sigrix. Not a world where AI replaces human judgment, but one where people use it precisely and intentionally, so they have more