Observed Signal · Dec 17, 2025 · Other · Source: CMSWire · Impact: 2/5 · Sentiment: Positive

Synthetic Research Adoption Boosts CX Team Influence

Executive Signal Summary

The article discusses the findings of Qualtrics' 2026 Market Research Trends report, which indicates that CX and market research teams using synthetic research and agentic AI are gaining significantly more organizational influence and budget compared to teams using traditional methods. Teams with advanced AI adoption report 72% agreement that their organizations rely more on their research, while traditional teams are four times more likely to lose influence. Purpose-built synthetic models are now seen as reliable as human panels, with 45% of adopters considering it their most reliable data source. The article also highlights a gap between leadership expectations and frontline execution, and predicts that AI agents will run over half of research projects by 2028. It advises leaders to invest in purpose-built AI capabilities and bridge the alignment gap.

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High Confidence

Insightful report on AI adoption in market research, but not a major industry event or platform change.

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Key Takeaways & Evidence Grounding

  • Qualtrics' 2026 Market Research Trends report found that teams using synthetic research and agentic AI report 72% higher organizational reliance.
  • Traditional research teams are 4X more likely to report declining organizational influence.
  • 45% of synthetic data adopters consider it their most reliable data source.
  • Synthetic data users are 11% more likely to engage in early-stage innovation.
  • 78% of researchers predict AI agents will run over half of research projects by 2028.

Connected Companies & Entities

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“The 2026 Market Research Trends report from Qualtrics reveals a critical divergence in organizational strategic influence driven by AI adopt...”

Primary Source Grounding & Direct Attribution
Direct Origin Attribution
Primary Reporting: CMSWire•Published: Dec 17, 2025
Original Coverage Title: “The CX Teams Moving Fastest Are Rewriting How AI Research Works”

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