Webinar Recap: Building the Research Team of Tomorrow

When everyone can research, what defines a researcher’s rigor?

AI is not just changing what research teams produce. It is changing who is on the team, how performance is defined, and what leadership looks like during the transition. In this session, design and research leaders from Pinterest, TD Bank Group, Taxwell, and Cisco Networking shared what they are learning in real time: where change is taking hold, where it is stalling, and what it takes to move an organization forward without losing the people and craft that make research credible.

Hosted in partnership with Dscout, the conversation featured Gordon Ching (Design Executive Council), Dana Cho (Pinterest), Christian Rohrer (TD Bank Group), Andy Vitale and Rylie Heintz (Taxwell), and Mary Piontkowski and Daniel Avrahami (Cisco Networking).

This session is part of Modernizing Research with AI: Customer Centricity at Scale, a four-part series with Dscout and the Design Executive Council. Track 1 focuses on the foundations: how senior leaders are actually rebuilding their teams, redefining performance, and steering change without breaking trust.

What we covered in the webinar

Future teams and roles: How AI is reshaping the profile, structure, and composition of design and research teams, and what the team of tomorrow actually looks like.
Redefining performance: How leaders are defining high performance with AI in the mix, and which mindsets, behaviors, and skills matter most now.
Change management: What is working and what is not as leaders steer their teams and cross-functional partners through the shift.

Key takeaways

Research is evolving from static insights towards intelligent systems of insight.

AI isn't just automating research tasks. Teams are using it to scale the quality of thinking across the organization.
Execution rigor is now the floor and leaders are evaluating research impact by whether it surfaced something the business didn't already know.

Research is no longer just landing in decks. It's being built into systems, eval frameworks, and knowledge layers that teams across the organization can use.

Path forward

The panelists returned to one idea again and again: the qualities that make a great researcher, curiosity, systems thinking, rigor, communication, human judgment, have not changed. What has changed is the form the work takes and the pace at which it has to land.

The shift is not about doing research faster. It is about moving research closer to the system, closer to the decision, and closer to the customer. That means investing in the layers where insight lives on: shared knowledge bases, eval frameworks, and governance embedded in the artifacts themselves. It also means holding a higher bar for what impact looks like, and giving teams the time, tools, and permission to build the new muscles.