It’s Not Just AI. It’s IA: Insights Activation in the Age of GenAI

Over the last year, every company has started talking about AI. But while strategy decks fill up with “transformation,” many organizations still struggle to move from aspiration to activation—especially when it comes to aligning AI with real business outcomes.

The opportunity? We believe researchers and insights professionals are uniquely positioned to accelerate meaningful adoption of GenAI by driving what we call IA: Insights Activation.

The Real Power of GenAI Starts with IA

Most organizations are experimenting with GenAI to boost efficiency—automating tasks, summarizing reports, or answering internal questions. But when you stop at task automation, you miss the bigger value proposition: using AI to activate insights at scale—bringing data closer to the decisions that matter.

While many executives are eager to prioritize generative AI, the reality of adoption tells a different story. According to Business Insider, nearly 70% of leaders prioritize GenAI for data and analytics, yet less than 40% feel equipped to implement it at scale. Even more striking, research-specific AI adoption lags further behind—Kantar reports that only 5% of companies have integrated AI into their insights generation processes. This gap highlights a critical opportunity for researchers to lead AI-driven transformation in their organizations.

We’ve worked with clients across industries—CPG, retail, logistics, and ecommerce—and we’ve seen that the true power of GenAI is unlocked when it’s embedded into the knowledge workflows of a business. Not just collecting data, but turning it into action. Not just reporting numbers, but influencing outcomes. That’s where insights teams shine.

Researchers: Your Seat at the AI Table is Already Reserved

GenAI may be new, but your skills as a researcher are more relevant than ever. Structuring questions, validating sources, analyzing unstructured data, designing effective prompts—these are core strengths of research professionals. And these capabilities are exactly what’s needed to ensure GenAI is accurate, effective, and aligned to business priorities.

We’ve seen firsthand how insights leaders can take the lead in building use cases, stress-testing tools, and guiding their organizations through this evolving space. In fact, researchers are already some of the best positioned to ensure AI isn’t just “smart,” but strategically useful.

Start Small. Scale Smart.

Rather than waiting on an organization-wide AI roadmap, researchers can start small—identifying specific business pain points where GenAI can enhance existing insights processes, and piloting tools that streamline or scale knowledge delivery.

For example, a leading beauty brand’s insights team piloted a GenAI summarization tool that condensed thousands of open-end survey responses into thematic narratives. The result? What used to take 10 hours of manual work per study now takes 20 minutes—with 80% faster turnaround times, freeing up staff to focus on analysis and stakeholder storytelling.

These small wins can serve as proof points to bring forward to leadership, enabling faster organizational buy-in for AI acceleration. This bottom-up momentum—when aligned with top-down strategy—helps build a culture where GenAI is embraced, not feared.

Insights professionals are also uniquely positioned to ensure GenAI tools are deployed responsibly—bringing rigor to prompt frameworks, monitoring for bias, and ensuring the training data reflects true market diversity. By acting as early stewards of quality and context, they can safeguard against AI missteps while accelerating real value.

From Efficiency to Business Impact

Too often, AI use cases focus narrowly on productivity gains. But the real business upside comes from activation: using GenAI to shorten the path from data to decision.

In client work, we’ve seen GenAI-assisted insights processes directly improve campaign testing cycles, reduce redundant research spend, and increase speed-to-market for innovation launches. When researchers plug into these higher-order business outcomes, AI becomes a multiplier—not just a shortcut.

This Is the Moment for Researchers to Lead

We’ve seen what works. And we’ve seen where organizations stall. Those who unlock real value from GenAI do so not by waiting for perfect alignment—but by creating space for experimentation, use case development, and internal advocacy. Researchers can lead here, grounded in data, equipped with context, and focused on outcomes.

The IA mindset shifts the conversation from “Can we use AI?” to “How do we use AI to make smarter, faster, better decisions?”

Don’t Go It Alone

If your team isn’t sure where to begin, don’t go it alone. We’ve helped Fortune 500s and scrappy startups alike take the first step toward AI-powered insights activation.

Third parties like Springboard Management can help you assess internal readiness, map research-to-AI alignment, and identify high-impact pilots that balance innovation with risk. Let’s make your insights team the spark that accelerates AI adoption—with strategy and structure, not just software.

If you’re looking to make AI work for your team, reach out to Springboard Management. We’re here to help you turn insights into real results—together.