
November 11 @ 2:00 pm – 2:40 pm
This live webinar is in partnership with:
Julian Cole of Qualzy shares three real-world examples of what AI can and can’t do in qualitative research, and where people still matter.
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It feels like AI is everywhere in research now. Yet there are some things it just can’t replace. Join Julian Cole from Qualzy for three real-world examples that demonstrate what cutting-edge AI can do, and what it can’t.
Most researchers by now have used AI enough to feel both empowered and fearful. Work that used to be hard and laborious has become almost trivially easy, while the ongoing encroachment of AI into all aspects of research begs the question of where people fit in. Does AI just make research more efficient, or is there a point where it replaces researchers, and possibly even the people they talk to?
To help answer this, the session looks at three areas of research where AI has brought a lot of change: long-term communities, multi-day qualitative studies, and live interviews and groups. It explores how state-of-the-art AI and researchers work hand in hand to improve what can be accomplished. While researchers need AI more and more to keep competing in a world of shrinking budgets and growing expectations, the session also shows the areas where humans still add value that AI cannot replace… at least not without raising the question of whether the result is real research at all.
Key takeaways:
- An understanding of the importance of cutting-edge AI in long-term communities, multi-day studies, and live interviews and groups, in a world where budgets are falling and expectations are rising.
- Real-world examples that prove two things can be true at once: AI can make the research process faster, cheaper and arguably better… but at the same time, AI can’t do “real research” all by itself.
- Why “better”, in particular, can’t be achieved without the continuing involvement of humans — with practical examples of where real research still requires real people and, by extension, real researchers.



