November 18, 2025
AI Is Resetting the Role of Research Inside Modern Organisations, Survey Reveals
Market research is entering a phase where influence inside organisations is no longer earned through tenure, experience, or process discipline. According to Qualtrics’ new 2026 Market Research Trends report, the real dividing line is whether teams have moved beyond basic AI features and into purpose-built, research-grade capabilities.
The findings show a structural shift in how companies assign budget, trust, and strategic responsibility. Teams that still rely on generic AI tools or limited automation are four times more likely to lose organisational influence than those using synthetic data, agentic AI, and embedded research-specific models.
Meanwhile, 72% of AI-first teams report that their organisations now depend far more on research than last year, driven by rising budgets and greater visibility.
Traditional teams, on the other hand, were nearly twice as likely to report flat or falling demand for their work.
Momentum Toward Specialist Tools
Researchers have pushed the market to a tipping point, with 53% now using AI regularly and nearly 90% having experimented with it. The momentum is clearly moving toward specialist tools. AI embedded directly within research platforms rose from 62% to 66% adoption, while general-purpose chatbots dropped seven percentage points over the same period.
This change towards AI is driven by capabilities that generic models simply cannot provide. Conversational analytics and AI-driven visual content analysis, each now used by roughly half of teams, allow researchers to analyse interviews, focus groups, and open-text responses in hours instead of weeks. The effect is not only speed but the kind of work teams are able to take on.
A second divide is forming inside organisations themselves. Leadership teams often believe they are further along in AI transformation than their researchers do. While 39% of leaders say AI has already transformed their processes, just 19% of individual contributors agree. Leaders also consistently overestimate their expertise and confidence with synthetic data. Similar issues occur in CX programmes, where AI investments often fail to translate into impact due to misalignment and fragmented ownership.
Since modern CX relies on a continuous flow of timely, actionable insights, AI-first research teams might be the ones who are able to produce them at scale. Many researchers also expect AI agents to handle most project execution by 2028, which will further increase output speed and reduce operational bottlenecks.
