Qualtrics report reveals widening competitive gap as AI-first research teams capture significantly more budget and strategic influence

78% of researchers predict AI agents will run more than half of all research projects by 2028

Qualtrics’ Ali Henriques: “The research teams embracing AI build advantages that latecomers will find difficult to overcome”

Research teams still using basic AI functionalities are four times more likely to lose organizational influence than teams embracing purpose-built AI for market research—and the competitive gap is widening fast, according to the 2026 Market Research Trends report from Qualtrics.

Seventy-two percent of teams using synthetic responses, agentic AI, and purpose-built capabilities report their organizations depend on research significantly more than a year ago, translating directly to budget gains. Meanwhile, traditional teams were nearly twice as likely to see flat or declining demand for their research (37% vs. 20%).

“In today’s fast-moving economies, rapid access to consumer insights is a huge advantage, and the research teams embracing AI build advantages that latecomers will find difficult to overcome,” said Ali Henriques, Executive Director of Edge at Qualtrics. “The research teams gaining strategic influence are reimagining what research looks like across the entire organization, they’re conducting different kinds of research, asking bigger questions, and moving earlier in the innovation cycle.”

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Purpose-built AI platforms for Market Research deliver strategic advantage over generic tools

AI adoption in market research has reached a tipping point. While more than half of researchers (53%) now use AI regularly and nearly nine in ten have experimented with it, they are increasingly choosing purpose-built capabilities over generic tools. AI embedded directly in research software has grown from 62% to 66%, while general-purpose AI tools like chatbots have dropped from 75% to 67%.

The research teams winning budgets and delivering impact have moved to specialist capabilities. Conversational analytics (49% adoption) enables researchers to get richer insights from consumers in the experience. AI for visual content analysis (49% adoption) extracts qualitative insights from focus groups and customer interviews at scale in hours rather than weeks.

Teams using synthetic research data are doing fundamentally different work and delivering greater strategic value: researchers who have integrated synthetic data are 11% more likely to engage in early-stage innovation, 7% more likely to conduct go-to-market research, and 5% more likely to perform final product testing. Among researchers who have adopted synthetic data, 45% now view it as their most reliable data source, outpacing traditional online panels. Organizations like Gabb are using Qualtrics’ purpose built synthetic model, which is proven to outperform generic LLMs and produce results nearly identical to human responses, to reduce fielding costs, shorten time to insights, and expand audience reach.

“Synthetic data became our ‘cultural radar’—cutting research timelines from a week to hours while giving us confidence to test messaging against emerging trends. The blended approach lets us move faster on early-stage testing, then validate high-stakes decisions with human panels.” – Garred Sheppard, Marketing Research Director, Gabb

Research teams improve efficiency and democratize insights with AI agents

Researchers are bullish on agentic AI’s potential: 15% are actively using AI agents and 78% believe research agents will handle more than half of projects end-to-end within three years.

Research agents improve research capacity without adding headcount and the impact is measurable. The majority of researchers (84%) regularly using agentic AI report their team’s research efforts have become significantly more efficient, compared to 68% of those who haven’t tried it yet.

“Equipped with the right AI tools, research teams can allow product managers to test concepts without submitting tickets. Marketing teams can analyze sentiment without waiting for reports. Executives can explore markets without going through intermediaries. The barrier to insights is no longer specialist knowledge. It’s simply asking the right question,” added Henriques.

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Leadership-team misalignment with individual contributors hinders AI execution

Even organizations investing heavily in AI face an execution problem that’s costing them competitive advantage.

Research leaders believe they’re innovating (39% say AI has revolutionized their processes) while frontline teams remain skeptical (only 19% agree). The adoption, expertise, and confidence in AI tools gap is equally stark:

• 5% of leaders fear layoffs due to AI vs. 15% of individual contributors
• 68% of leaders consider themselves synthetic data experts vs. 41% of individual contributors
• 84% of leaders have experimented with synthetic research vs. 68% of individual contributors
• 79% of leaders are confident in synthetic data quality vs. 61% of individual contributors

This misalignment wastes budget on underutilized tools and allows competitors with better organizational alignment to move faster while leaders believe they’re already innovating.

“When frontline teams don’t buy in, expensive AI tools go unused and competitors with better alignment move faster,” said Henriques. “Organizations need to bridge this divide by establishing shared definitions of success, providing hands-on training, and ensuring teams at every level understand both the potential and practical application of new AI capabilities.”