To evaluate the potential impact and ROI of AI integration in UX research processes, enabling informed decisions about AI tool investments while maintaining research quality. Our goal was to develop a scalable framework that would help organizations efficiently implement AI in their research workflows while understanding the limitations and opportunities of current AI technologies.

Our systematic evaluation of AI in UX research delivered both immediate and long-term value. We developed a scalable methodology that improved research efficiency while maintaining quality, created new revenue streams through innovative service offerings, and established the agency as a thought leader in AI-UX integration. Most importantly, we provided a clear framework for ethical AI implementation that helped both our team and clients navigate the future of research.

Organizations are increasingly looking to integrate AI into their UX research processes but lack frameworks to evaluate tools and implement them effectively. The challenge was multifaceted: understanding which tasks could be enhanced by AI, measuring the real business value of AI integration, and ensuring research quality isn't compromised. With numerous AI tools available and significant investments at stake, organizations needed clear guidance on how to approach AI implementation in research workflows while maintaining ethical standards and research integrity.

• AI evaluation framework

• Tool comparison methodology

• Implementation playbook

• Service offering documentation

• Training program

• Ethical guidelines

• Research findings synthesis

• Best practices guide