This is not a piece on the latest AI trends but one about how AI-driven tools can play a role in your trend research process.

At the moment there’s a lot of attention on outsourcing trend related tasks to artificial intelligence tools, particularly things like generating summaries, analysing datasets or creating visuals. These tools offer efficient solutions for trend researchers by providing quick results and automating various aspects of the research process.

To understand which AI tools are most helpful in trend research you need to first understand the research process. You also wouldn’t be able to use a calculator if you didn’t know the basics of mathematics.



Going through the process of spotting signals, analysing your findings and applying your trend insights yourself at least once will help you navigate uncertainty, ambiguity and not knowing. It stimulates taking the long view and activates your future consciousness.

While outsourcing your work by buying a trend report or relying solely on AI tools may provide faster results, it won’t allow you to fully experience and learn from the process. In the end, there is a distinction between knowledge and knowing: knowledge is about building a repository of data, while knowing is an inner comprehension and understanding.

Education is key in training your trend muscles. This means practice, practice, practice and experiencing the process in-depth. These are things that buying a yearly trend report or using generative AI tools can never replace.

image made with Dall-E

Image made with Dall E with the prompt: a photo showing a person working on a computer using ai tools during their trend research process.



There are many things AI can help you with, from collecting signals, transcribing interviews to analysing information. Let’s look at one aspect of the trend research process: scanning.

Desk research is one of the activities in trend forecasting in which AI tools can be very helpful. Using language processing tools powered by artificial intelligence can help to find information if you prompt them in the right way. There are all kinds of services available to scan the world wide web for you on a scale you could never do yourself. The key thing is to combine this ‘automated’ input with your own desk research and field research activities.

Many trend agencies use a combination of types of scanning, such as social listening dashboards, AI-powered web crawlers, a network of global trend spotters and their own in-house researchers spotting signals.

EXAMPLES: Cultural intelligence company Sparks & Honey uses an AI-powered cultural intelligence platform called Q™ to collect daily signals from over 9,000 global data sources across 140+ countries in 16 languages. And trend firm TrendWatching collects signals via their global trendspotter community tw:in, via an AI-driven feed that tracks thousands of sources and via their in-house team of trend analysts.

Scanning is about finding emerging signals of change that challenge the status quo. This means looking at the fringes and diving into niches. Be aware that at the time of writing a lot of AI tools are not using very current data sets, and therefore can give outdated results. Also, they generate information using data that is not necessarily neutral. Western content is dominating and misinformation also comes into play. Be like a detective and verify before you share any statements or statistics found online. Sounds old school, but libraries often share tips on how to check sources.



Which tools to use and which prompts work best? There is no one size fits all. My advice is to experiment with many different tools and exchange with peers on the (dis)advantages.

At the time of this writing, developments in LLMs like ChatGPT and ChatSonic, are moving super-fast. To use them you will need to understand how they work and what their strengths and their limitations are. Writing or voicing the right prompts is essential, and there are many tutorials out there to help you with this. You can consider outsourcing some of the desk research to AI-powered search services such as or Strat7.



What I actually hope this whole AI movement will spawn is a revival and revaluing of the role of field research.

While online research is a great way to gather information from around the world, it is still only one way to collect material. Algorithms can make it hard for serendipity to happen and tend to keep you in your biased bubble. Doing field research makes you an anthropologist of the future who uses ethnographic techniques to explore. It takes you closer to where possible futures are emerging.

Field research is primary research, where the researcher gathers information first-hand doing their own observations. You meet people and have unexpected conversations. You can hit the streets and smell, feel and taste the change. Whereas most desk research relies on secondary research, using findings that are compiled by others. Which can make it harder to really feel immersed in the information.

As the following quote shows, talking to people provides a lot of value to your research:

“Interviews with experts are very useful. I recently spoke to multiple experts about the future of work. These conversations brought different signals to the forefront than our online desk research did, so it really paid off.”

– Eva Burm, Port of the Future Advisor at Port of Antwerp-Bruges


That being said, let’s go out right now and let the AI tools do their work while we are having fun with street hunting!