How AI in market research is redefining growth through discomfort

AI is creating meaningful change in market research. For insights professionals, there's a balance to strike between trusted methods and fresh approaches. Monika Rogers, strategic growth leader at CMB, captured this tension perfectly during the Insightful Inspiration podcast.

"If you're riding the horse and you're comfortable, you're riding it wrong," Rogers says.

Her perspective highlights a fundamental truth about progress in the AI era. Growth, both personal and organizational, often begins outside our comfort zone.

Below, we’ll explore why the uncertainty brought by AI in market research represents an opportunity instead of a challenge.

Why discomfort signals progress

Market research has traditionally relied on judgment, observation, and established methodologies. AI has introduced new dimensions to how insights are gathered and interpreted, from extensive data processing to predictive analysis.

With these advances comes natural hesitation. Ethical considerations, changing dynamics, and questions about professional roles have created tension. Yet according to Rogers, AI functions as a tool that depends on creativity and thoughtful implementation.

"AI forces us to constantly assess how we operate and adapt along the way," Rogers explains during the podcast.

Through her work with AI projects at CMB, she's found that moments of uncertainty often indicate progress and reveal possibilities for innovation.

Learning through experience

When CMB tested AI-powered interviews, they encountered initial obstacles. Interviews frequently extended beyond necessary timeframes because the tools misinterpreted conversational signals. This revealed where adjustments could improve the balance between technology and human guidance, ultimately creating a more effective system.

These experiences highlight a valuable insight about integrating AI. Though it may create initial uncertainty, embracing these moments provides essential opportunities to reimagine existing approaches.

Pairing human insight with technological capability

Incorporating AI into research requires more than technical skill; it demands cultural intelligence, particularly when analyzing data across cultural contexts. While AI provides remarkable scale and efficiency, the true value comes from the researcher's ability to interpret cultural subtleties, regional expressions, and nuanced behaviors. These elements offer the context that transforms raw data into actionable insights.

A primary consideration for AI integration in research is its limited capacity to comprehend human complexity. Numbers and patterns alone tell an incomplete story. The skilled interpretation of these findings creates meaningful direction.

Rogers emphasizes this point when she says, "The tasks AI can handle complement our abilities, but the deeper interpretations – that's all human work."

AI relieves researchers from repetitive tasks, preserving the essential role of the professional researcher in connecting context with conclusions.

Strengthening the human-machine partnership

Effective AI use isn't about complete delegation. Rogers advocates for a collaborative approach, where researchers and AI tools work together. While machines excel at data-intensive and repetitive work, humans provide the emotional and cultural understanding that completes the decision-making process. By combining strengths, both elements become essential contributors.

Building confidence through testing

Effective adoption of AI in market research develops gradually. For reliable integration, teams should approach AI testing methodically, focusing on individual phases. Rogers describes this as "thoughtful iteration." Small pilots and regular evaluation create space for adjustments before expanding further.

She also notes how experience refines tools. "Some features will feel half-baked today, but continual testing allows AI to grow alongside our needs," she explained.

Simply put, trust in AI requires first developing confidence that it consistently provides value.

Making AI work effectively

Every professional exploring AI in market research faces a learning curve, but clear strategies can lead to meaningful improvements. Here are five proven approaches for adopting AI successfully, while balancing its potential with its current limitations:

1. Test on a small scale: Begin with contained experiments to explore how AI tools function in your specific context. Whether automating surveys or analyzing text, gradual integration reveals practical potential.

2. Keep insights grounded: AI findings must connect to logic and context. Researchers serve as narrative guides who link data points into practical, actionable stories.

3. Improve through cycles: Don't treat AI-enabled processes as fixed solutions. Conduct regular reviews to identify limitations and evolve approaches that improve over time.

4. Encourage adaptable teams: Teams need space to express concerns about AI while maintaining curiosity. Viewing AI as a collaborative tool shifts hesitation into interest in new possibilities.

5. Value insight over speed: Adopting AI isn't about quick solutions. Focus instead on whether tools help address fundamental research priorities in more thoughtful, forward-looking ways.

Why challenges indicate advancement

Rogers encourages market research professionals to look beyond initial concerns about AI. "If the integration feels too easy, you probably aren't using it to its fullest," she noted. The challenges provided her team with insights they wouldn't have gained otherwise, showing that discomfort, while inconvenient, drives innovation.

The future of AI in market research depends on our willingness to approach it thoughtfully, using each learning moment to create greater insights and operational growth.

Ready to embrace productive discomfort and find growth opportunities in AI-enhanced market research? Connect with our experts for a consultation on balancing human cultural intelligence with technological capabilities, ensuring your insights capture the nuanced context that transforms data into meaningful action.

Insightful Inspiration is produced by Sylvestre & Co., where qualitative excellence meets cultural intelligence. Visit our website to explore how 50 years of human-centered research expertise can benefit your next project.

‍