Global Study Reveals AI Adoption Surges in User Research, But Human Collaboration Remains Essential

A comprehensive global study of 300 research professionals reveals that artificial intelligence has rapidly become central to research analysis, with 54.7% of practitioners now using AI-assisted tools – virtually tied with traditional team collaboration methods (55.0%) as the most common synthesis approach.

From chaos to clarity: How teams synthesize research in 2025, published by user research platform Lyssna, surveyed researchers, designers, product managers, and marketers globally to understand how teams transform raw user feedback into actionable insights.

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Key findings:

• AI integration is mainstream: More than half of research practitioners now incorporate AI tools into their analysis workflows, primarily for generating summaries (82.9% of AI users) and identifying patterns (61.0%).
  
  
• Speed is critical: Nearly two-thirds (65.3%) of research synthesis is completed within 1-5 days, with time-consuming manual work cited as the biggest frustration by 60.3% of practitioners.
  
  
• Democratization continues: Research synthesis extends far beyond dedicated research roles, with designers, product managers, and marketing professionals actively involved in analyzing user data.
  
  
• Confidence remains high: Despite challenges, 97% of participants express at least moderate confidence in their synthesis processes.

“Our research shows an interesting point,” said Mateja Milosavljevic, CEO at Lyssna. “AI is being integrated into research workflows not as a replacement for human judgment, but as a tool that handles repetitive tasks and surfaces data, freeing up people to connect more of the dots.”

Human oversight remains essential

While AI excels at initial data processing, practitioners maintain strong preferences for human oversight in interpretation. Only 47.6% of AI users trust the technology for translating insights into actionable recommendations, compared to 82.9% who use it for generating summaries.

“We have found that the most successful teams are the ones that can balance AI capabilities and human insight,” added Mateja. “AI is great at mining data and pattern-matching, whereas humans are key to sense-making and strategic alignment.”

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