Forty-five percent of design teams that plan to grow intend to hire for the UX researcher role, according to Forrester’s State Of Design Survey, 2025 . This finding reinforces that as organizations grow, AI is augmenting — not eliminating — the need for human‑led research. AI experience designers also rank among the top five roles teams plan to add, reflecting the need for new AI-driven interaction patterns in newly identified use cases across enterprises.

How AI Is Empowering G-Research Software, Data, And Research Engineers

Design Teams Use Experience Research Repositories In Various Ways, Including AI Training We asked 220 design professionals about how their team uses experience research repositories. 59%: Help new team members ramp up on past research. 54%: Prevent duplicate research by making past insights discoverable. 54%: Centralize and organize research findings. 54%: Give cross-functional teams easy access to research insights. 52%: Use centralized insights to train our AI tools. 50%: Track what research has

AI is transforming how experience research is conducted — from planning to analysis — thanks to new tools like AI moderators. If you are a research vendor offering AI moderators or a researcher who has used AI-moderated interviews, I want to talk to you.

This is human intelligence plus artificial intelligence. In a market flooded with AI-generated slop, Forrester is clear about what we stand for: No slop: We deliver bold, proprietary ideas, data, and people. Forrester AI — the industry’s first and most advanced genAI tool — is trained exclusively on Forrester IP, not scraped or recycled ideas from the internet.

Before joining Forrester, I was a client, relying on its research, frameworks, and guidance to tackle critical priorities at both the enterprise and functional levels. With Forrester’s support, for instance, we adopted the Demand Waterfall to align marketing and sales, building a faster, more durable engine for revenue growth. Implementing the Forrester Campaign Framework united marketing efforts around shared goals and a common vocabulary.

Multiple, cross-disciplinary perspectives not only make our research stronger, but they also ensure that our insights fit together so leaders across functions can solve problems together. That’s how meaningful change takes place. Trust: The Differentiator In An AI World AI has a tremendously valuable role to play for us as a research firm. AI can help our clients quickly surface trusted insights from our research.

As AI reshapes how research is delivered and consumed, trust isn’t just important — it’s everything. In a world where speed and scale matter, the winners will be those who build AI on a foundation of integrity.

But it might be time to trade in that C-word for another — like curiosity — and capitalize on the candor of AI vendors to further enterprise and product security programs. Forrester clients who want to continue this discussion or dive into Forrester’s wide range of AI research can set up a guidance session or inquiry with us.

Here are my three takeaways: AI-supported research is real and serious. A year ago, for many researchers, the idea of using AI to conduct research was an interesting nice-to-have, and for some, it was out of the question due to concerns about privacy and biased data. But today, AI-supported research is real, and teams are actively seeking ways to understand the use cases and learn how to use AI in their research practices. Researchers’ expectations are not fully met.