This presentation from Ray Poynter of NewMR shares the findings from the latest NewMR study. The study looks at the use of Artificial Intelligence in insights and research, including a deeper dive into the topic of Synthetic Data. Find out how many people are using AI, how many are testing it, what they are doing, and what people think about Synthetic Data. And, hear about where AI and research might be in two year’s time. Listen to the recording of this presentation via NewMR.org/Play-Again, and also access other presentations from NewMR on all things market research, insight, and AI.

1. The State of AI in Insights & Research
Results and Findings
April 2024
Ray Poynter

2. NewMR Sponsors

3. What’s happening with AI in Research and Insights?
A survey circulated to
the NewMR network
442 people 21 March to 7 April Caveats
NOT a rep sample
English speaking
Tends to be more
innovative
Note, ResearchWiseAI (an AI tool) was used to assist the analysis

4. Mostly Suppliers
N=442

5. Global Spread
N=441

6. Almost 80% Using or Piloting AI
N=442

7. ‘Maybe’ Suppliers are more likely to be using AI
Base: Suppliers=292, Buyers=76

8. Usage of AI similar in the big regions
Base: Europe=121, USA/Canada=125, Asia Pacific=119

9. Please describe the ways you are using AI (Those using AI for Live Projects)
Base: 181

10. Please describe the ways you are piloting or testing AI
Base: 144

11. Are you familiar with the term Synthetic Data
in the context of insights and research?
Base: 441

12. What does the term 'Synthetic Data' mean to you?
Using AI to generate one of
– Answers to questions
– Constructed participants (qual or quant) that can then be questioned
Answers are generated from one of
– The general information the AI system already had
– From first-party data
– From a combination of these two
Key aspects
– Creating personas that can then be ‘questioned’ in a qualitative way
– Creating quant data sets that can be analysed conventionally
– Augmenting data sets, for example to boost hard to reach samples (qual and quant)
Base all familiar with the terms, at least to some extent, 331 answers

13. Three Archetypical Descriptions
General
"Data that is created by AI or with the use of algorithms to mimic real-world data for the
purposes of analysis or simulation where actual data is not available or cannot be used.”
Negative
"Mostly bollocks. The shallow simulations offered by what is termed as 'synthetic data'
rarely capture the nuanced complexities of real-world scenarios."
Positive
"Synthetic data is essential for augmenting our datasets, allowing us to simulate a wider
range of scenarios than our real-world data permits."

14. Is Synthetic Data Likely to be a Good or Bad Thing?
Base: 344
Good 35%
Bad 26%
Other 37%

15. Looking forward two years,
what impact do you think AI will have on research and insights?
Enhanced Efficiency, Analysis and Creativity (the majority)
– "AI is unlocking the power of vast text datasets, enabling us to uncover insights that were once buried
under the sheer volume of information."
– "Thanks to AI, researchers can now focus on crafting more compelling stories, with rich media
presentations that bring data to life in ways we've never seen before.”
– "The efficiency AI brings to the table is a game-changer – smaller sample sizes, quicker insights, and lower
costs, all while elevating the standard of our work.”
Losses, Changes, and Risks (a minority)
– "There's a growing concern that the art of research is being lost as we lean more on AI, which doesn't
always 'understand' the nuances that experienced researchers do."
– "While AI offers many benefits, we can't ignore the risks – subtle errors and biases in AI can lead to
significant missteps in our strategies and decisions.”
– "More and more marketers are bypassing agencies to run their own AI-driven research projects, but
they're often overlooking the importance of quality and depth in the process."
417 statements

16. The Big Picture
• AI is here and it is global
• Most people in this study were positive about AI
– Faster, Deeper, Bigger data sets, freeing up human thinking
• Some are negative
– Loss of skills, hidden failings (e.g. bias), loss of jobs in agencies
• Synthetic Data is perhaps the hottest topic
– At best it makes research faster, cheaper, better
– At worst it is doomed to failure
– A few people are already using it
• Two risky strategies
– Do nothing
– Bet big on a specific approach

17. Thank You

18. Ray Poynter
NewMR
Questions?

19. NewMR Sponsors