The panel weighed the creative and ethical trade-offs of using AI in advertising versus investing in human creativity. Mike warned against “learning the hard way” by hollowing out the industry, noting we’ve already seen declining ad effectiveness as spend shifted to social. Instead of ideology, he urged controlled A/B tests to quantify trade-offs (e.g., cheaper AI output vs. effectiveness loss), and advised brands to mine their historical media mix and outcomes, then run geo-split experiments tied to business metrics like sales or memory.

Dr Lollie argued creativity requires human origin and friction—AI stitches data and fills gaps with “acceptable” answers, which risks devaluing meaning and purpose. Short-term savings may create long-term costs in connectedness, culture, and work with purpose. She also highlighted a swing toward local, authentic content and Gen Z’s forensic demand for alignment between values and actions; brands should be transparent about AI use and build cultures people want to join.

Richard shared behavioural evidence that identical work rates lower when labelled “AI-generated” (the labor-illusion: perceived effort boosts quality). If AI speeds delivery, agencies must signal the human expertise and setup behind the process to avoid price/value erosion. On attention, he reiterated that multiple persuasive routes exist, but humour is underused and lifts noticeability, trust and value via the halo effect. “Annoying” ads can drive memory, but often trade off likability, which carries a financial cost.

Across the panel, the consensus: use AI deliberately and transparently, protect the creative craft, prove value with experiments and data, and lean into authentic, human-centred ideas—especially humour and local storytelling.

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