4 Big Insights Trends to Watch in 2026

The 2025 GRIT Business & Innovation Report draws on responses from thousands of brand-side and supplier-side insights professionals around the world and shows that the industry is in the middle of a major shift. Aside from simply speeding up research workflows, AI is responsible for major change in how teams understand audiences, make decisions, and use data.  

At Yabble, we see this change spreading rapidly across countries, industries, and job functions. Below is our take on the trends identified in the report as well as what we believe is missing from the conversation, and how the insights industry looks likely to shift in 2026. 

1: Insights served on-demand using AI

The GRIT report calls out an unmistakable trend: AI-led platforms are growing, while service-only models are struggling to keep pace. According to the report, more than 80% of organizations are now using generative AI to support, enhance, or replace primary research processes. This does not mean traditional research is disappearing. Rather, it signals that organizations are prioritizing tools that can deliver answers continuously, without the rigid constraints of traditional project-based services. 

Teams are shifting from planning isolated studies to asking continuous questions of their data. They expect instant access to reliable answers to help them remain agile and on-trend even in unfamiliar or unusual market conditions. 

We are seeing this shift first-hand, with our on-demand insights tool Gen being used to deliver more answers than ever before. By giving teams a way to ask questions in natural language and receive accurate, research-grade insights immediately, Gen turns existing datasets into an always-on source of intelligence. Instead of waiting for formal studies to conclude, teams can test assumptions, explore patterns, and validate decisions the moment questions arise. This makes the promise of on-demand insights both practical and scalable. 

Why this matters now:
The pace of change in consumer behavior, media trends, and competitive activity is accelerating. The cost of delayed insight is rising with it. Marketers, researchers, and strategists who continue relying solely on episodic research cycles will struggle to keep up, missing opportunities and reacting too slowly to shifts that require fast interpretation. Those who adopt AI-driven, continuous insight models will reap the benefits of making confident decisions at pace.  

2: Generic AI is out, purpose-built AI is in

GRIT highlights several challenges with current AI usage: difficulty with reasoning, weak integration into workflows, concerns about quality, and uneven adoption across teams. These are real issues, and many of them stem from a simple cause: teams are experimenting with generic AI assistants like ChatGPT or Gemini to do work that actually requires purpose-built research tools. General models can summarize information, but they aren’t designed to interpret meaning, connect behavioral signals, or produce structured insight you can trust. ChatGPT for example is used by more than 85% of insights suppliers, but nearly half believe that the tool isn’t competent at reasoning or thinking critically. 

As expectations rise, teams are shifting away from broad, undifferentiated AI and toward tools that can think with more structure and research logic. They want AI that understands context, explores motivations, and helps them see beyond surface-level patterns, especially when making complicated decisions that require deeper interpretation. 

Yabble’s tools are purpose built for research and shaped by a team that knows this industry inside out. We have decades of experience in insights and have been building AI for research since 2019, well before the arrival of mainstream tools like ChatGPT. That background gives us a clear view of how much time and effort traditional research requires and where AI can make the biggest difference. 

Unlike generic AI assistants which often lack nuance or context, Yabble’s tools are built to follow research logic, integrate smoothly into workflows, and deliver results that teams can rely on. They help organizations move beyond surface-level observations, producing structured insights that inform real-world decisions and keep teams aligned, confident, and ahead of market trends. 

Why this matters now:
The demand for credible, reasoning-led insight is growing, while tolerance for shallow outputs from generic AI is rapidly declining. In 2026, teams that rely solely on general AI assistants will face blind spots, misread consumer signals, and make decisions that fail to hold up under scrutiny. Those who adopt purpose-built, research-grade AI will gain a meaningful edge: richer interpretation, faster alignment, and a clearer view of the behaviors shaping their market.

3: Insights are breaking out of the research department

One of the clearest signals in this year’s GRIT report is that insight demand is no longer contained within research and insights teams. Decision-makers across the business — marketers, executives, product teams, R&D, and CX — are hungry for answers they can trust. According to the report, somewhere between 4-5 teams are working as active collaborators on the insights process, but while demand is high, data access remains fragmented. Research reports live in one system, customer feedback in another, surveys in a third, and behavioral data somewhere else entirely. Instead of one cohesive story, organizations are left with competing narratives that slow decisions and undermine confidence. 

This shift is exactly why teams are moving to tools that free insight from the research department and make it usable for everyone. People want to explore data, uncover hidden patterns, and validate assumptions without decoding dashboards or waiting for a specialist to run analysis. 

Gen helps solve this issue by enabling anyone to ask complex research questions in plain English and get reliable, research-grade answers. Gen creates tables, summaries, comparisons, and breakdowns that would normally require pivot tables or advanced tools. This means a marketer can analyse campaign performance, a product manager can investigate feature behaviour, and a finance leader can dig into customer segments, all without needing analyst-level skills. Insights that once sat buried in decks, spreadsheets, or siloed systems become accessible, consistent, and ready to use across the organisation. 

Why this matters now:
The pressure to make faster, evidence-backed decisions is intensifying. Organizations that empower cross-functional teams with direct access to clear, consistent insights will move with more speed and alignment than competitors stuck navigating data chaos. As expectations rise, integration and accessibility are no longer nice-to-haves. They are foundational to modern insight operations.

4: Lazer-focus on data and insight quality

As AI usage spreads across organizations, concerns about the quality of insights are intensifying. Teams are encountering shallow analysis, hallucinations, inconsistent reasoning, and outputs that cannot stand up to scrutiny. GRIT recognizes this challenge with Sample & Data Quality identified as a top 3 pain point for the industry, but the desire for trustworthy, research-grade insight is growing even faster than the report suggests. Leaders want speed, but not at the cost of accuracy, transparency, or methodological integrity. 

The next generation of AI insight tools must embed rigor directly into their design. Virtual Audiences was created with this expectation at its core. It delivers insights that benchmark at around 90% accuracy compared to traditional research and draws from a wide variety of traceable, high-quality sources. This ensures that outputs reflect real consumer dynamics rather than guesswork. Its built-in bias protections help safeguard against skewed interpretations, and its research logic ensures that insights remain structured, interpretable, and grounded in evidence.

Why this matters now:
Brands are becoming increasingly aware of the risks associated with fast but shallow AI. As pressure grows to make rapid decisions in volatile markets, teams will choose platforms that combine speed with proven rigor. Tools that consistently deliver defensible, high-quality insights at pace will earn trust, win adoption, and set the new standard for AI-driven research.

Final thoughts

The 2025 GRIT Business & Innovation Report captures a moment of transformation. The industry is moving toward faster cycles, always-available intelligence, and deeper integration of AI into every stage of insight work. But speed alone is not enough. Teams want clarity, confidence, and the ability to turn data into meaningful decisions. 

At Yabble, our mission is to support that shift. We build fast and rigorous AI tools that help teams to deeply understand their customers and make smarter decisions. 

If you would like to discuss how Yabble can support your 2026 insights plans, book a time to chat with our team.