In this episode, we explore the intersection of AI and behavioral science with Ryan Scott, Head of Product at DNA Behavior, who has transformed traditional personality testing into an AI-powered behavioral intelligence platform over his 15-year journey with the company.

Keywords

Ryan Scott, DNA Behavior, Behavioral Intelligence, AI Personality Testing, Digital Scan, DISC Alternative, Myers-Briggs, Machine Learning, Behavioral Prediction, Enterprise Psychology, Workplace Analytics, Custom GPTs

Key Takeaways

DNA Behavior's Evolution Journey

- Started with faxed PDF questionnaires requiring manual data entry by interns

- Four major iterations over 15 years: workplace talent → financial insights → combined platform → AI-driven enterprise solution

- Founded in Australia, moved to Atlanta for Georgia Tech research partnerships

- Differentiated by making behavioral insights actionable through dashboards vs. static PDF reports

The Traditional Assessment Problem

Traditional personality tests (DISC, Myers-Briggs, Enneagram) follow a broken model:

- 60-90 minute questionnaires that produce PDF reports

- Reports "die in a dust drawer" and aren't used day-to-day

- No integration with business systems or decision-making processes

- High switching costs for organizations with existing assessment data

Digital Scan AI Innovation

DNA Behavior's breakthrough solution predicts behavioral insights using only:

- Person's name and job title

- Company information and background data

- No questionnaire required

Training data foundation:

- 3.5 million behavioral questionnaire responses

- 3.25 million people across 4,000 behavioral insights

- Backwards compatible with 15 years of historical data

- Machine learning algorithm predicts same insights as traditional assessments

AI Implementation Cost Savings

Ryan's practical tips for reducing LLM costs:

- Clean and standardize data locally before cloud processing

- Use local LLAMA models for initial data processing

- Convert to CSV format before uploading to cloud services

- Use custom ChatGPTs for R&D before paying for APIs

- Structure responses as JSON instead of unstructured text (reduces hallucinations)

- Process only necessary data rather than scanning entire documents

Organizational AI Adoption

- Required making "hard decisions" about team members resistant to change

- Used behavioral insights to identify team members suited for fast-paced innovation

- Some people "weren't really suited for the fast-paced innovation that AI brings"

- Essential to choose adaptable people for AI transformation success

Business Model Innovation

B2B2B structure with coaches/consultants as intermediaries:

- Reduces switching costs by importing existing DISC/Myers-Briggs reports

- AI translator contextualizes insights in familiar assessment languages

- No retraining required for managers familiar with other systems

- Seamless comparison between AI-scanned and traditionally assessed individuals

Market Differentiation Strategy

- Contextualized insights for specific use cases (financial decisions, relationships, management)

- Enterprise-grade platform vs. individual assessment tools

- Big data approach with millions of behavioral data points

- Focus on actionable intelligence rather than static reports

This episode demonstrates how AI can revolutionize traditional industries by solving fundamental usability problems while maintaining compatibility with existing systems and knowledge.

Links

https://dnabehavior.com/