Organizations Face Growing Gap in AI-Driven Research: Qualtrics

Research teams adopting purpose-built AI systems are gaining organizational influence and budget at a faster rate than peers that rely on basic AI tools, according to new data from Qualtrics. The company’s 2026 Market Research Trends report shows a widening competitive gap, with nearly eight in 10 researchers predicting that AI agents will run more than half of all research projects by 2028.

Ali Henriques, Executive Director of Edge, Qualtrics, says the shift marks a structural change in how research is conducted and used across organizations. “The research teams embracing AI build advantages that latecomers will find difficult to overcome,” says Henriques, noting that these teams are repositioning research earlier in the innovation cycle and expanding the scope of questions they can address.

The findings come as organizations around the world attempt to align fast-growing AI use with leadership strategies, a challenge that has already surfaced across sectors. Studies from McKinsey, Michael Page, and enterprise technology providers show similar patterns: teams rapidly adopting AI tools often outpace organizational structures that were not designed for hybrid systems of people and autonomous agents.

Qualtrics’ study suggests that reliance on AI in market research has passed a tipping point. More than half of researchers now use AI regularly, but those integrating purpose-built capabilities are seeing the most substantial returns. Seventy-two percent of teams using synthetic responses, agentic AI, and embedded analytics report that their organizations rely more heavily on research than a year ago, correlating with expanded budgets. In contrast, 37% of traditional teams report flat or declining demand.

The transition toward specialized AI is altering workflows. Adoption of conversational analytics and automated visual content analysis has reached 49% each, allowing teams to process qualitative inputs in hours instead of weeks. Synthetic research data is reshaping the early stages of product development, with researchers who use it more likely to participate in innovation planning, go-to-market validation, and product testing. Nearly half of those using synthetic data view it as their most reliable source, surpassing traditional panels. Companies such as Gabb have incorporated Qualtrics’ synthetic models to shorten timelines and reduce costs, with Garred Sheppard, Marketing Research Director describing the data as a “cultural radar” that accelerates message testing while guiding decisions that are later validated with human inputs.

Across industries, the rise of AI agents is reinforcing the shift. Fifteen percent of researchers already use agentic AI, and 78% expect agents to manage most research projects within three years. Early adopters report notable efficiency gains, with 84% saying these agents have significantly improved capacity without increasing headcount. Henriques notes that these systems allow non-research teams to obtain insights independently, reducing bottlenecks and repositioning researchers as strategic advisors.

However, the report highlights a misalignment between leadership and individual contributors, which has emerged as a barrier to effective AI deployment. Leaders are more optimistic about their transformation efforts, with 39% saying AI has revolutionized their workflows, compared to 19% of frontline staff. Gaps also appear in confidence, adoption, and expertise, leading to underutilized tools and slower execution. Henriques says organizations must establish clear expectations and strengthen training to prevent investment waste.

The challenges outlined by Qualtrics echo broader trends documented in recent workforce studies. McKinsey argues that organizations are moving toward agentic operating models where managers oversee integrated systems of people and AI agents. The firm says this requires new forms of literacy, including the ability to evaluate agent performance, mitigate failures, and align automated processes with business outcomes. It estimates that 75% of jobs will require redesign or upskilling by 2030 as AI reshapes workflows and expands leadership accountability.

In Mexico, rapid adoption among professionals is influencing labor trends even as companies struggle to update job requirements. Michael Page reports that 37% of professionals already use AI tools daily, often without formal recognition in job descriptions. Recruiters face persistent challenges meeting talent needs as organizations prioritize analytical thinking, problem-solving, and digital fluency. Technology leaders note that many operational tasks in HR, recruitment, and frontline services are shifting to AI agents, increasing the urgency for workforce adaptation.

The need for clearer governance is also driving new enterprise partnerships. Workday’s collaboration with Microsoft introduces a centralized system to manage AI agents alongside human employees, using identity verification and unified analytics to monitor performance and maintain secure workflows. Executives from both companies say visibility and accountability frameworks are essential as agents become embedded in business operations.