The Sea Change: Insights from the 2025 GRIT Business Outlook

GRIT’s Business Outlook reveals a research industry at a crossroads—tech-driven, cost-conscious, and demanding insights that drive real decisions.

The Sea Change: Insights from the 2025 GRIT Business Outlook

The Business Outlook section of the latest GRIT Report doesn’t pull punches—it’s a stark snapshot of an industry at the largest inflection point since the internet. After years of post-pandemic recovery, we’re not just settling into a new normal; we’re staring down a fundamental change. Research spending is tightening, technology is rewriting the rules, and client expectations are evolving faster than ever. For senior leaders, this isn’t a time for nostalgia; it’s a call to action. Adapt or get left behind. 

Clients aren’t just cutting costs; they’re recalibrating what they value. The message is clear: insights that drive decisions now trump reports that describe them.

The AI Tipping Point: From Novelty to Necessity

Let’s start with the biggest signal in the report. Sixty-seven percent of suppliers now embed generative AI directly into client deliverables, automating everything from survey design to cross-tab analysis. This isn’t about replacing researchers; it’s about freeing them. Take agentic AI systems which handle complex tasks; correlation detection, qualitative synthesis, predictive modeling within three-day project cycles. The result? Analysts spend less time cleaning data and more time asking, “What does this mean for our business?”

But here’s the rub: AI adoption is a double-edged sword. While 80% of organizations endorse AI, nearly half still grapple with thorny issues of quality and impact. As one GRIT respondent noted, “Bad data amplified by AI erodes trust faster than ever.” The solution isn’t to slow adoption, it’s to build transparency. Leading firms now audit AI outputs with the rigor once reserved for human respondents, ensuring algorithms enhance rather than replace critical thinking.

The Bifurcation Battle: Research vs. Analytics

The industry is splitting into two camps. On one side: traditional researchers, often centralized in formal insights groups. On the other: analytics teams, increasingly embedded in executive suites. The numbers don’t lie:

  • 11% of analytics professionals sit on executive teams, compared to just 3% of research-focused peers.

  • Analytics teams dominate organizations with 20+ insights staff (61% vs. 27% for research-centric firms).

This isn’t just about titles, it’s about influence. Analytics teams thrive because they speak the language of outcomes. As budgets tighten, clients prioritize partners who can quantify ROI, not just deliver findings. Clients aren’t just cutting costs; they’re recalibrating what they value. The message is clear: insights that drive decisions now trump reports that describe them.

The Consolidation Wave: Survival of the Tech-Integrated

M&A activity isn’t just heating up; it’s reshaping the competitive landscape. Smaller firms clinging to legacy methodologies face existential threats, while tech-forward suppliers score 98.2 in revenue health (versus 34.0 for full-service research). The playbook? Acquire capabilities that matter:

  • 58% of tech suppliers use sample marketplaces, versus 19% of brand-side researchers.

  • Top-performing suppliers automate 5.1 processes with AI, outperforming laggards by 15%.

The lesson: Scale alone won’t save you. Integration will. Firms combining AI-native platforms with human expertise are pulling ahead, offering clients end-to-end solutions rather than fragmented tools.

The Talent Reckoning: Hybrid Skills or Obsolescence

The workforce divide mirrors the industry’s bifurcation. Staff growth in research has stalled, while analytics teams expand relentlessly. Why? The hybrid skills gap. GRIT data reveals:

  • 50% of insights professionals are reskilling for AI collaboration.

  • 33% of buyers now value AI literacy over traditional expertise.

Successful firms aren’t hiring data scientists, they’re creating them. Upskilling programs focus on bridging domains: teaching researchers to interpret machine learning outputs, while training analysts to contextualize findings for C-suites.

The Trust Imperative: Quality in an Age of Synthetic Respondents

Data quality concerns have surged 40% year-over-year, driven by “synthetic respondents” and Gen Z’s survey fatigue. Clients aren’t just demanding faster insights; they’re demanding authentic ones. Forward-thinking suppliers respond with:

  • Biometric verification tools that catch bad actors traditional QA methods miss.

  • AI certifications (read: trust) score price premiums.

As one GRIT participant warned, “Cut corners on quality, and you’ll lose more than clients, you’ll lose credibility.”

The Path Forward: Three Non-Negotiables

  1. Lead with business impact, not methodology. Only 34% of research buyers cite management support for budget increases, down from 65% last year. Tie every project to measurable outcomes.

  2. Invest in hybrid talent. Teams blending AI proficiency with strategic storytelling are more likely to secure executive buy-in.

  3. Build ethical tech partnerships. Clients pay premiums for transparency. Differentiate through accountability, not just automation.

The 2025 GRIT Business Outlook isn’t a warning, it’s a roadmap. The industry’s future belongs to those who embrace change without sacrificing rigor, leverage AI without losing sight of ethics, and prioritize outcomes over outputs. The question isn’t whether you’ll adapt, but how fast.

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