The 2026 GRIT Insights Practice Report shows the AI debate has matured. The "should we use it?" binary is mostly behind us. Yet reading between the lines, the industry's view of AI for insights still feels too narrow.

Four limiting beliefs surface across the verbatims. AI is treated as a force that replaces the human voice rather than amplifies it. The comprehension of AI is dominated by synthetic data and synthesizing the past, which eliminates the human at the very moment we need them most. AI is read more as a threat than an opportunity, especially around jobs and value. And much of the AI conversation is perceived as not method-backed: hype unmoored from research craft.

This framing is restrictive and may lead to missed opportunities.

We believe the opposite is true. AI, used well, leads to more research, more insight, and more human empathy, not less. It expands the footprint of insights in two directions at once: generating deeper understanding and activating it inside the business. And AI for insights cannot be a tech experiment bolted onto research. It has to be built by researchers, for researchers. Method and rigor have to come first!

GRIT participants pointed to the right frame themselves when they talked about integrating AI across the research value chain, and when agentic AI emerged as a top buzz topic. Agentic workflows, used right, are not about removing humans or expertise. They are the operational scaffolding that lets human empathy show up in more decisions, more often. These are common human-centered methods (e.g., design thinking) and AI, working together. Thinking about AI this way lays the foundation for insights as an always-on operating system: a living layer of consumer understanding that compounds with every conversation, every wave, every market.

The most exciting signal in GRIT is that AI is creating a genuinely new methodology that is complementary to our toolbox. AI for insights becomes an assistant that gives us superpowers. A mash-up of qualitative and quantitative: AI-moderated conversations with real people, at the magnitude and power of quant. Structured data with human nuance. The "why" finally has a number next to it.

The final emerging signal of added value that AI can bring is insight activation and storytelling. What that really means is not better slides. It is about bringing the consumer into the boardroom: their voice, their face, their video-based reality, their reasoning, sitting next to the P&L. Decisions made with the customer present, not just represented.

Opportunities ahead for AI and insights!