Expert insights into the future of visualizations 

Where market research stands today

At our recent webinar, data visualization experts shared exactly how agencies and in-house teams can stop dashboards drifting into irrelevance. Their advice was blunt, practical, and rooted in years of building dashboards that actually get used. 

Clients are not asking for more dashboards to be the future of visualizations. They are asking for faster answers, simpler storytelling, and evidence that sparks action. GRIT’s 2025 report confirms: Research teams are shifting from “showing the data” to “guiding the decision.” AI is accelerating delivery, but human storytelling is what makes the message stick. 

Watch now: Picture this: The future of visualizations 

Read now: The art and science of data visualization: Turning numbers into narratives 

Learn from our experts: Realities behind dashboard stickiness 

• Dashboards are never set-and-forget: One expert described a program that has been live for seven years, but is never static. Annual reviews align dashboards with new tech, design trends, and business priorities. 

• Fix what wastes time: A single client saved hours per cycle when manual reporting steps were automated, expanding dashboard access from a small marketing team to over 300 stakeholders. 

• Standardization delivers speed: Productized dashboards, templated designs that can be cloned, skinned, and deployed, turn repetitive requests into rapid delivery. 

• Adoption drives retention: Dynamic, easy-to-use dashboards create stickiness. Clients who like the tool tend to stay with the agency longer. 

Why dashboard retention matters 

Adoption equals influence, now and in the future of visualizations. A dashboard that isn’t used is a wasted investment. And adoption doesn’t come from cramming in charts. It comes from role relevance, process automation, and design choices that reduce cognitive load. It also increasingly comes from blending AI speed with human storytelling, because decision-makers respond to emotion as much as logic. 

The role of AI in the future of visualizations

Our panel agreed: AI is becoming a less-than-silent partner in dashboard delivery. It can: 

• Automate repetitive reporting tasks, like building first-pass decks or highlighting anomalies. 

• Create summaries and topic lists from collected data. 

• Accelerate data cleaning and reformatting, especially for qualitative data. 

But despite having a place in the future of visualizations, AI has limits. Today, it gets you 70–80% of the way there. However, it lacks the human social skills that can craft stories that resonate with executives, nor can it replicate the nuance of strong design. As Rachel Cummins, Director, Data Management and Delivery at The Directions Group, puts it: “Clients don’t want the machines to do everything for them. They still want a human to be involved and make sure everything is right.” 

Looking ahead, the group pointed to conversational AI as the next frontier. Instead of clicking filters, users will ask: “How are sales trending since Q2?” and see a visual answer. That lowers the barrier to entry, but it comes with risks. Hallucinations, misinterpretations, and overconfidence in machine answers. Educating clients on the limits of AI is now part of the researcher’s role. 

Emotional storytelling: Why it works 

Good visualization is not just logical, it is emotional. Emotional storytelling connects with audiences on a deeper level, making insights memorable and actionable. Tobi Andersson described it as “the journey the user takes, how they consume data, step by step, to start to understand what kind of decisions to take and act upon.” In a world where attention spans are shrinking, emotional resonance makes the difference between charts that inform and stories that inspire. This is the future of visualizations.

Plays to make dashboards stick 

1. Start with the “why” (and roles, not charts): Tie every dashboard to a business purpose. A CMO wants movement in market share. A sales lead wants territory performance. Build with those lenses first. 
2. Build once, reuse often: Productize trackers and pulse studies. This means finding consistent KPIs across clients and waves. Faster for you, clearer for them. 
3. Blend live and batch: Stakeholders still want decks. Keep one governed dataset that powers both interactive dashboards and editable PowerPoint exports. 
4. Automate the annoying: Free researchers from repetitive reporting so they can focus on insight generation. 
5. Simplify story complexity: Think about story arc, role relevance, and delivery formats before you launch. Avoid information overload. Design for cognitive ease, not chart density. 
6. Measure the mundane: Track adoption, time-to-insight, and the number of decisions influenced. In MR, these are the real KPIs for whether your dashboard program survives. 

If you want to make your dashboards indispensable, treat them like products. Pick one high-visibility program, redesign it around roles and the “why,” automate what you can, and measure adoption and engagement as rigorously as you would revenue. 

The future visualizations will not be defined by dashboards alone. It will be defined by the fusion of AI’s efficiency with human creativity and emotional storytelling. That is the modern alchemy that moves insights from charts to change, and from research to real impact.