In light of the launch of the Thematic Analysis tool available in the Reporting Dashboard, we decided that we need to address a few questions!

What does the launch of the Thematic Analysis tool have to do with Artificial Intelligence (AI)?

Well, the Thematic Analysis tool utilises AI to conduct analysis on free text data, collected in Culture Counts. It’s a fantastic tool which really speeds up the analysis of your qualitative data. Check out a few questions and our answers below…

 

What do we mean by AI in this context?

When we refer to AI, we are primarily talking about Large Language Models (LLMs)—AI that can generate, summarise, and interpret text at scale—and products which make use of LLMs. An example of a product which utilises LLMs is image generation.

We recognise that AI is a much broader field, covering many different technologies and approaches, but we also know that LLMs are currently the most disruptive and are the technologies which people have concerns about.

 

What do we think we should use AI for?

A short, snappy way to summarise our position on this is “Artists for art; AI for everything else”.

By ‘Artists for art’, we mean that work which requires genuine human creativity, artistic expression, or originality, should remain the domain of skilled, creative people—no AI here.

By ‘AI for everything else’, we don’t literally mean that AI should do everything else! But for tasks that are repetitive, efficiency-driven, or require some quick brainstorming, there is scope to make use of AI to speed things up, improve accuracy, and free-up capacity.

Examples of ‘AI for everything else’ include drafting documents, summarising information, and automating routine processes.

An exception to this general rule is quantitative analysis. This may change in the future, but, as of September 2025, LLM technology struggles with numbers. Therefore, we would not recommend using AI to crunch numbers and run data analysis.

 

Will AI replace our staff?

We acknowledge that there is concern AI will replace people in the workplace. Our view is that AI is best used to support and empower staff, not replace them.

One aspect of this is, by using AI tools, we will reduce time spent on repetitive or administrative tasks, so that our people can focus on higher-value, creative, and relationship-driven work.

Beyond this, everybody has some aspects of their work which they enjoy less than others, or feel less confident in. By making use of AI, we can be empowered in our work to become more confident and content.

 

How should we use AI responsibly?

Perhaps AI technology will be good enough in the future to allow us to hand over responsibility for our work to AI, but we are not there today.

If we are using AI in our work, it should be in a collaborative fashion, where we are still responsible for the quality and truthfulness of the work that we do. This means we should always read, digest, understand, edit and own the outputs of any work where AI has been used.

We consider it irresponsible to take the output of AI and welcome it, without taking time to understand and own it.

 

What are the impacts of AI?

In the workplace, we believe there is a risk that AI could displace creatives and other skilled workers, if we do nothing. In our opinion, the best way to mitigate the risk of this negative impact is to invest in learning how AI can be used effectively and to demonstrate that a person using AI will always have the best outcomes.

We are also aware of concerns about the environmental impact of AI. Clearly, the data centres that power AI use a lot of energy, and, by using AI technology, we are contributing to that energy use.

However, it’s important to remember that in using AI we should be able to achieve more with the same team. A 2025 paper in the journal Nature[1] found that the carbon emissions of using AI for writing and illustration were lower than for humans. So, it’s possible that a smaller team using AI would be more energy efficient than a larger team of people without AI.

 

Closing thoughts

Clearly, this is a developing story, and we don’t have all the answers now. However, with the information currently available, we believe that the best approach is to tackle this head-on and start bringing AI into our processes.

As always, if you have any questions, please don’t hesitate to get in touch.

 

 

Featured Image credit – Igor Omilaev

 

[1] https://www.nature.com/articles/s41598-024-54271-x