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The rise of generative AI has changed how we work. Tools like ChatGPT, Gemini, or Perplexity can summarize reports, draft emails, and brainstorm ideas in seconds. For foresight professionals, they offer an easy entry point to explore futures questions with a simple prompt.

Foresight professionals are under more pressure than ever. They’re expected to deliver meaningful insights quickly, stay ahead of change, and support strategic decisions. And all this with limited time and resources. The volume of information is already challenging, but turning that flood of data into something useful is the real hurdle.

At FIBRES, we set out to solve this problem in a bold new way.

I’ve often argued that the first step towards foresight work is simply to start talking about your future. Also I think such conversations can no longer be left to a handful of specialists hidden away in strategy units or innovation labs.

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.

If you work in foresight, you know the feeling. Endless context-switching. Drowning in signals and data. Colleagues asking for fast answers while you struggle to ensure engagement. And too often, little visibility into the actual impact of all your hard work.

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.

Strategic planning has always been challenging. But today, the pace and complexity of change make it tougher than ever. Annual planning cycles that rely on past data feel increasingly out of sync with reality. To stay competitive, we need to do more than react: we need to anticipate, sense shifts as they happen, and adapt together when the change happens.