AI is here to stay
It’s evident that AI and machine learning aren’t going anywhere. Across the market research industry, more and more organizations and companies are using AI to speed up audience insights analysis.
The reason for this is simple: AI can streamline previously lengthy processes. Formerly time-consuming work can now be done in seconds, with human beings remaining on hand to oversee accuracy.
A survey conducted by Cint in late 2024 found that nearly three-quarters of respondents (74%) are using AI-powered software in their current job roles in the research and insights sector.
That’s all well and good, but can AI be used ethically and without impacting data quality?
How is AI being used in Restech?
AI and machine learning power many of Cint’s products and initiatives, and we will continue to ensure that our use of these tools remains steadfastly ethical, with data quality and customer privacy always top of mind.
What, though, do our customers make of AI? How are they using it, and what concerns do they have around its potential impact on data quality?
Wanting to know more, Cint recently conducted a study to learn more about market researchers’ usage of AI and synthetic data, and their outlook on those shifts in the Restech landscape.
We found that 74% of respondents reported using AI-powered software in their current job roles. Delving a little deeper, the study showed that research titles (e.g. Managers, Directors, and VPs) are 7-11% more likely to use AI in their current job roles than others in the sample.
Regarding how it’s being used, 81% reported data analysis. Over three-quarters (78%) indicate that there’s a strong use case for AI playing a role in the setup and planning of projects.
The pros of AI in market research
For the better part of a decade, Cint has been exploring how AI and automation can play a role in delivering insights at speed and scale without a reduction in data quality, offering a more affordable and efficient way to get hold of the insights researchers need to make crucial business decisions and shape effective strategies.
At Cint, we leverage a combination of AI and machine learning to power tools that make conducting research easier with automated fielding, cost you less by delivering accurate feasibility, and an AI-powered chatbot help to free you up to focus on other impactful tasks.
AI is also a key component of Cint’s fraud mitigation strategy.
The cons of AI in market research
While AI creates opportunities for innovation and advancement worldwide in numerous fields, from medicine to teaching, it is also enabling opportunities for fraudulent communities to improve their attack methodologies.
“With thousands of surveys and millions of respondents interacting with our platform, we need tech that can accurately analyze interactions and behaviours, at scale. This is where our AI-powered Trust Score technology comes in,” says Jimmy Snyder, Vice President of Trust and Safety at Cint.
“The Trust Score model uses artificial intelligence to grade millions of survey participants based on a complex set of criteria to predict fraud before it happens.”
Additionally, it raises ethical dilemmas for researchers as to whether AI usage by genuine respondents, such as using it to support in formulating responses based on their opinions, is ever acceptable.
Zoom out from the world of research and measurement, and you’ll undoubtedly come across concerns about the ethicality of AI, how it’s used, and who benefits most from an increased reliance on machine learning in the 21st century.
Zoom back in on research and measurement, and those concerns are just as loud.
Our aforementioned research indicates that the burgeoning area of synthetic data — that is, data that has been algorithmically generated from previously captured real-world data samples — is an area for pause for some respondents.
Survey respondents reported strong feelings on synthetic data that reinforce the need for transparency and great communication around an emerging and increasingly important tool for market researchers across the board.
The majority of respondents expressed strong opposition to using synthetic samples, citing concerns over ethics, trust, reliability, and authenticity. Many view it as “fake data” or equate it to making up results.
There is also the ethical consideration of whether consumers answering surveys would agree with their answers being utilized to simulate an assumed opinion on their behalf and whether those assumed opinions would be representative, given that human opinions are subject to changes based on real-life events that may not be present in their previous survey answers.
Keeping quality top of mind in an ever-accelerating landscape
While AI promises incredible efficiencies and deeper insights, it also, as we’ve seen in this article, presents challenges that can impact data quality and, ultimately, our customers. We must ensure this powerful tech enhances, rather than compromises, the trustworthiness of our findings.
Cint is committed to continuously evolving its quality measures because fraud doesn’t stand still. Our dedicated team of Trust and Safety experts is focused on evaluating our existing tech and human-led programs to ensure they’re still mitigating fraud to the high levels we expect.
Fraud comes in many different guises and as tech becomes more sophisticated with trends in generative AI, so does the fraudulent activity. Receiving quality responses matters wherever you interact with Cint so we continue to maintain the integrity of our platform.
The world is learning how to adapt to the era of AI and the playbook for AI is still being written. Cint is investing and innovating in our platform is key to keeping ahead of the constant shifts in fraud globally and we’re constantly demanding more of our AI tools, operational strategies and the third party vendors we collaborate with to get you access to real people, fast.
Learn more about Cint’s commitment to quality
Ready to dive deep into Cint’s commitment to quality?
Explore our dedicated quality page. We break down exactly how we leverage advanced technological solutions alongside our vigilant teams to proactively fight data fraud, ensuring you receive only the most robust and high-quality consumer insights.
