What we do not know

A board’s worst mistakes do not come from what we know wrongly. They come from what we do not know at all.

The board’s task is tomorrow. Yet its materials are yesterday. The income statement, the cash flow, the sales pipeline. All important. All history. We look in the rear-view mirror more carefully than through the windscreen.

Boards talk about AI too modestly. The talk is about efficiency: the machine summarises, transcribes and prepares presentations. Useful, but a side issue. The real value of AI in board work lies elsewhere. It helps us understand what we do not know about the business.

The machine connects what no single person can:

• Historical knowledge. What has happened in similar situations before, in our own industry and in all others.
• Financial knowledge. What the numbers already tell us, before it shows in the result.
• Environment and market knowledge. What is changing around us while we look inwards.
• Trend analysis. Where development is turning. Not one forecast but alternative scenarios.
• Our own view. The machine mirrors all of the above against our vision, plans and goals.

When historical events are combined with the prevailing environment, scenarios and our own view of the future, the board gets something it has never had: a view into the unknown.

At the same time the board’s conversation changes direction. No longer only: what happened and why. But: what happens next and what do we do about it.

The purpose is not to replace conversation or decision-making. The purpose is to grow understanding. To notice things in time. To anticipate. To recognise changes before they show in the numbers. And above all to improve the chances of success. The machine calculates, the human decides.

In practice this means a new standing item on the board agenda. Not ”any other business” but ”what we do not know”. One hour. The machine produces the base: deviations, signals, scenarios, questions. The board discusses what the findings mean for us.

I admit it. After three decades and a hundred mandate years I thought experience was enough. It is not. Experience recognises the patterns I have seen before. AI shows the patterns I have never met.

When did your board last spend an hour on what you do not know?

By Ville Tolvanen. Originally published in Finnish: Mitä emme tiedä. More in English: Aura Boards — start here.