Euromonitor International

GenAI: When to Use for Market Research (and when to Call an Expert)

The episode of Opportunity‑minded explores when generative AI (GenAI) should be deployed in market research and when traditional expertise remains essential. Host Jessica interviews Lamein Lewaznia, head of AI innovation at Euromonitor, to map the boundary between rapid, low‑risk insight generation and high‑stakes decision making that demands rigor. Lewaznia highlights three core pitfalls: the plausibility trap—AI’s confident but potentially false answers; the slot‑machine effect—probabilistic models yielding different results on identical queries; and agreement bias, where AI readily conforms to incomplete prompts. He stresses evaluating the cost of being wrong, distinguishing between the need for clarity (idea generation) and credibility (traceable, reproducible data), and ensuring reproducibility for quantitative tasks. The conversation turns into a practical “prompter paths” game, classifying real‑world prompts as suitable for GenAI or requiring expert input. Summarizing longevity trends is a clear‑cut prompt, while estimating market size for ready‑to‑drink coffee or confirming premium‑import preferences are passes that need specialist data and validation. Lewaznia likens the evolving AI landscape to “playing chess on a ship where the board keeps shifting,” underscoring the volatility of model updates. For practitioners, the takeaway is to harness GenAI for brainstorming, hypothesis generation, and rapid framing, but to embed guardrails—structured data, expert interviews, and reproducible workflows—when the outcome influences significant investments or brand reputation. By aligning AI use with risk tolerance, firms can accelerate insight cycles without sacrificing credibility.