How KS&R Is Scaling Research Insights with AI Chatbots | Signal & Noise Ep 14

In this episode of Signal & Noise, hosts Brian Lamar and Andrew DeCilles speak with Ben Cortese, Vice President of Decision Sciences and Innovation at KS&R, to explore how custom AI chatbots are reshaping the way research insights are accessed, shared, and expanded beyond traditional deliverables.

Ben explains how his team is combining qualitative and quantitative research with secure AI systems to build proprietary chatbots that allow clients to interact naturally with their own data. These tools help stakeholders ask new questions, explore nuances, and identify early opportunities without re-fielding studies or relying solely on static reports.

The discussion covers how KS&R structures these models to remain accurate, safe, and aligned with proven research findings. Ben also walks through the technical evolution of the tool, including early failures, the role of system guardrails, the importance of loading structured data, and why transparency and validation matter more than speed or novelty.

Key Takeaways:

• What it means to extend insights beyond traditional deliverables

• How custom chatbots are powered by proprietary qualitative content

• Why guardrails are essential to prevent drift, hallucination, and off-topic responses

• The process of grounding AI output to match known research narratives

• How AI can support ideation, early concept testing, and faster client exploration

• Where AI can accelerate the workflow versus where human judgment remains irreplaceable

• How researchers may evolve into curators, validators, and strategic translators

• The future role of AI in tracking, longitudinal analysis, and blended data environments

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