Post By: Sakari Nisula

When multiple people contribute to foresight and you are still running it in decks and spreadsheets, alignment quietly becomes your full-time job.

In many strategy conversations, someone eventually says something like: “The future of our industry is clearly heading toward X.” At that moment, something subtle happens in the room. The conversation narrows. The discussion shifts toward confirming that one direction. Alternatives quietly disappear and we start to assume one option for the future.

Traditional risk management is built to manage what is already known. Risk registers capture risks whose impacts and likelihoods can be estimated based on historical data, past experience and existing categories.

Most teams assume they will know when it is time to upgrade their foresight setup. They expect a dramatic moment: a missed disruption, a boardroom surprise, a strategic bet that aged badly. However, it is usually much quieter than that.

(or  why being “right” about the future is the wrong goal)

The foresight radar has become one of the most recognizable tools in futures work. Done well, it’s more than a visualization, it’s a living map of what could shape our tomorrow.

This year, at Nordic Business Forum 2025, the slogan “Moving Forward” is a call to action! It highlights foresight, growth, and culture as critical drivers of organizational success. Inspired by this, and to support leaders in making sense of the emerging forces shaping these areas, we’ve created the Future-Ready Business Trend Radar.

The truth is, foresight has long been treated as an accessory, not a necessity. Teams worked hard to produce thick reports, build scenarios and analyze trends, but too often the work stayed on the shelf. Leaders would skim, nod politely, and move on to the next pressing issue, often an operational one. Foresight felt detached from the real conversations that actually shaped strategy.

With all the attention AI has received lately, it’s easy to assume that strategic foresight might soon be another thing machines do better than people. After all, AI is incredibly efficient at processing large datasets, spotting correlations, and summarizing vast amounts of information in seconds. That kind of analytical speed (even with its caveats) can be extremely helpful for any organization working to understand change.