News and Insights
Beyond the Hype: Why Generative AI Can’t Be the Final Word on Data Accuracy
September 18, 2025
Key Takeaways:
- AI Accuracy: Generative AI often produces plausible but unreliable outputs, making human validation essential.
- Risk of Misleading Data: Overreliance on AI can amplify errors, erode trust, and miss critical nuances in research.
- AI as Assistant, Not Authority: Best used to speed up scanning and synthesis, with researchers ensuring context and accuracy.
- Human Intelligence Builds Trust: Client’s value transparent sources, context, and interpretation that only people can provide.
When the Market Research Society (MRS) released its latest report on the inaccuracies of generative AI for extracting data, one point stood out loud and clear: what looks polished and authoritative isn’t always reliable.
At FINN Partners, our Global Intelligence team spends every day working at the intersection of research, data, and storytelling. And this report couldn’t be timelier. As clients and colleagues alike experiment with GenAI tools for everything from quick fact-checking to building pitch decks, the temptation is real to treat AI outputs as truth. But as the MRS analysis shows, the veneer of confidence can mask deep inconsistencies.
What the MRS report found
The MRS experiment was simple but revealing: ask multiple AI-powered tools for the UK’s quarterly GDP change in 1973. The real answer (from the ONS) was straightforward, but the AI responses varied wildly; sometimes accurate, sometimes approximate, sometimes flat-out wrong. Even more troubling, the same tool could provide different answers when asked twice.
The takeaway? AI outputs live in the realm of plausibility rather than certainty. They sound right, they look right, and they feel right; but “believable” is not the same as “accurate.”
Why this matters for research and intelligence
From our point of view, as researchers, we see this play out every day. Our work is built on trustworthy, verifiable evidence; because our insights directly shape clients’ strategies, campaigns, and sometimes even policy positions. If we relied solely on generative AI to extract and summarize data, we’d risk:
- Amplifying noise instead of signal: AI models trained on large datasets don’t always know which number is the “right” one, especially when dealing with revisions, duplicates, or historical quirks.
- Undermining credibility: A confidently delivered but incorrect statistic can erode client trust in both the data and the consultancy providing it.
- Missing nuance: Models can return neat summaries, but they rarely flag anomalies, caveats, or methodological differences; exactly the kinds of details that often matter most in strategic decision-making.
Our approach? AI as a tool, not a source
As part of our work at Global Intelligence, we’re embracing AI’s potential, but with clear guardrails. Here’s how we think about it:
- AI can accelerate, not replace: Tools help us scan, surface, and synthesize at speed. But the validation still rests with us.
- Context matters: Unlike AI, we know when a “0.1% revision” in an ONS dataset is meaningful, or when two seemingly contradictory sources are, in fact, complementary.
- Human intelligence wins trust: Clients don’t just want a number; they want confidence in the number. That means showing sources, explaining revisions, and offering an interpretation that machines can’t provide.
Looking ahead: staying critical
As the MRS report rightly points out, the reality is that most of these models are in a constant state of flux; new capabilities are being added, errors are patched, outputs are changing daily. That means reproducibility is near impossible, and sole reliance on AI can create a fragile foundation for research.
Until there’s far greater stability and transparency, we need to keep the human in the loop. For us, that means treating AI not as a researcher, but as a research assistant: helpful, fast, and creative – but never the final authority.
Final thought
Generative AI is revolutionizing how we access and interact with information. But the MRS report is a vital reminder that the most convincing answer isn’t always the correct one. In research and intelligence, accuracy isn’t a “nice-to-have.” Instead, it’s the foundation of every strategic decision.
At FINN Partners, we continue exploring and adopting these tools, but always with the consistency and discipline our clients rely on, because in our world, insight is all about truth and not just about speed.
Want to learn more? Get in touch with FINN Partners’ Global Intelligence team.
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