Associate Led Design Thinking Initiative
Augmenting The Associate Role In The Age of AI
Business Need— The company needed to scale AI adoption in research to align with its positioning as a provider of cutting-edge AI implementation research.
Associate Need— Associates felt underutilized, time-strapped, and craved more professional growth opportunities.
Enablement and Operations Need — The enablement team needed research production to become more efficient to support the companies strategic goals.
Challenge: How do you evolve the associate role for the GenAI era without losing the human expertise that makes it valuable?
Applied the human-centered design framework, beginning with divergent thinking to uncover everything we could about the challenge. Assembled a diverse team of 5 associates across teams to tackle the challenge together.
Deliverables designed from scratch as an associate-led initiative:
Project proposal
Interview guide
Qualtrics survey
Design Approach
Conducted 24 in-depth interviews across roles and seniority levels. We led hour-long interviews with current and former associates across teams to understand sentiment toward the role, AI adoption, and professional development opportunities, grounding our insights in firsthand qualitative research.
Built AI agents to scale and validate qualitative analysis. We built two AI agents to identify key themes and quantify how many interviews aligned with each theme. Because we conducted the interviews ourselves, we were able to validate the agents’ outputs using firsthand context, with human oversight ensuring themes and insights accurately reflected participant perspectives.
Designed a quantitative survey to establish baseline metrics. We surveyed 31 associates to assess current AI adoption and time spent on use cases. Questions were intentionally designed to avoid leading language and to capture concrete, baseline measures that could be used to track progress over time.
Research Process
Associates are an underutilized resource. Associates want more stimulating, creative work and fewer project‑management tasks; leveraging the inherently collaborative nature of the role would unlock more of their potential.
Time is the biggest barrier to growth. Associates consistently cited lack of time, not lack of interest or ability, as the primary constraint on pursuing stretch work.
AI adoption is held back by distrust, not disinterest. Associates recognized AI’s potential but felt behind and skeptical of using it for complex tasks. They expressed a clear preference for high‑touch training and collaborative development over top‑down mandates.
Writing and data skills offer the highest ROI. Associates prioritize these skills above others and and those would most improve research quality and productivity.
Associate goals and business goals are more aligned than leadership realized. Associates’ goals directly support business needs for higher‑quality research and faster, more effective AI adoption. Investing time and resource to upskill associates would advance core business priorities.
