AI in Corporate Decision Making: What Do Your Decisions Really Rest On?

Most companies are already using AI in their decision processes. They are just not aware of it, and, even more problematic, they do not know what the AI actually bases its recommendations on.

That was the core of the keynote RECO founder Mag. Paul H. Schindler gave last week on "AI & Corporate Decision Making". The deeper you go into the topic, the clearer it becomes: the problem is not that AI is involved in decisions. The problem is that we drastically underestimate how deeply it is already involved.

Hardly any decision in a mid-sized or large company still happens today without AI influence. Not directly, but indirectly all the time: in summaries, in prioritizations, in meeting notes, in research, in decision drafts, in data interpretation, in recommended actions. AI has long become the silent sparring partner in the background. This changes everything we used to know about decision-making.

The critical question is therefore no longer "should we use AI?" but: "do we actually understand what the AI is referring to?", Which data flows in? Which information is missing? Which perspectives are over-represented? Which under-represented? Who last changed something and why?

This is where, in most corporates and larger SMEs, the real problem begins. There simply is no clean knowledge base. Knowledge lies in heads, in scattered meetings, in PDFs, in chat threads, in gut feelings or in long-forgotten decisions. And then we wonder why AI sometimes makes "strange" recommendations. Garbage in, garbage out, the rule holds for AI just as much as for any other analysis.

That is exactly why we at RECO are so consistently focused on knowledge documentation that emerges in everyday work, without extra effort for people who already sit in too many meetings. Not because documentation is sexy. But because good decisions are only ever as good as the knowledge base beneath them.

RECO captures employee conversations, jour fixes, handovers and decision rounds in a structured way, makes the contents searchable and versionable and ensures that every derived recommendation is tied to a clear context. Human-in-the-loop is not a slogan here, it is anchored in the product: people decide, AI delivers context, sources remain visible.

This unlocks the use cases that actually work in a corporate environment: better onboarding across all locations, targeted employee development with a documented learning curve, knowledge transfer ahead of upcoming retirement waves, structured handovers in leadership changes and after M&A transactions, more robust leadership decisions on a traceable factual basis, faster and auditable corporate processes

Our thesis after many conversations with boards, division heads and HR leads: whether a company uses AI will not be the question in two years, everyone will. What matters is who has a clean, living knowledge base for the AI to find something solid in. The rest automate their own blind spots.

If you are wondering how far your organization actually is in knowledge documentation and AI integration and where the biggest levers sit, we are happy to talk, with concrete experience from the keynote and from live implementations.