Leading Your Team Through the AI Transformation

Moderated by Daniela Busse and Jocelyn Landau
December 12, 2025

Companies’ rapid adoption of AI tools to augment and/or reduce their UX workforces has been one of the most impactful challenges for the field of User Experience in the past several decades. What has long been the triad of roles in product development–Product, UX, and Engineering—are all being significantly impacted by the adoption of AI and companies’ eagerness to reduce costs by reducing headcount.  For UX departments, this is exacerbated by the fact that UX research is already commonly under-resourced.  How do UX leaders try to succeed under these new circumstances?

Leading Your Team Through the AI Transformation was the topic of the Research Leaders Forum, co-led by Janice Rohn and Jocelyn Landau, on December 12, 2025.  This event featured Daniela Busse as the moderator, Jess Holbrook (Head of UX Research at Microsoft AI), Katharine Norwood (Research Lead at Google), and Harsha Vemulapalli (Director of Experience Design and Research at Siemens) as panelists.

The session was very well-attended, and this summary is for both the attendees and the wider UX community so that all may benefit from the discussions of the forum.  In addition to statements by the panelists, there was a moderated question and answer session and also breakout rooms by topics, led by the panelists and session leaders. 

AI-Adoption Challenges for Leaders and Researchers:

• Feeling like they are not keeping up with the new technologies and how to integrate them
• Anxiety about AI moving so fast and seeing the gaps between humans and AI
• Reduction in headcount
• Inability to hire for important roles
• The need to demonstrate to upper management that the team is becoming more efficient
• Concerns about data privacy when using AI tools

Solutions discussed included:

• The importance of experimenting with the tools to understand their benefits and limitations
• Educating management about those benefits and limitations  
• Reframing the problem for new solution spaces
• Budget for and ensure there is an efficient procurement process to encourage experimentation with AI tools
• Great UX is based on empathy, which is hard for non-humans to replicate—this is important to communicate to upper management
• Don’t need to integrate AI everywhere at the same time.  Select areas that may produce the largest ROI, and start with those.
• Track how long tasks take when performed manually vs. when performed with AI, and then the time for humans to check and correct the results.  Communicate those to management so that they understand the true ROI.
• Encourage your team to test and use AI tools, including making this part of their goals and objectives.
• Important to educate upper management about all of AI’s operational costs, including human oversight for accuracy, legal exposure, security risks, and more.
• At Microsoft, they have updated their career guide to help employees with their expectations
• At Siemens, UX Research created a research chatbot that is only accessible to the researchers, so that they can be more efficient and provide oversight, without unleashing the ability to produce inaccurate data to the wider company
• At Siemens, which is a German-based company, the culture is to retrain people rather than to lay them off, which differs from the US.

How to Lead AI Adoption as an Insights Leader:

• Experiment with and adopt the AI tools as useful—embrace them and be knowledgeable about what is helpful and what needs human oversight
• Understand that the traditional roles are compressing even beyond what we previously thought of as generalists
• Proactively optimize based on AI integration, while educating upper management about the true costs of AI and which tasks absolutely need to be human-powered
• As always, foster an environment that embraces change, curiosity, and a focus on continuous process improvement for your team.