iab Conference Day: New Rules of the Game in the AI Era
The agenda at the iab Conference Day in Vienna featured pressing issues in the digital economy. A central topic of discussion: the use of artificial intelligence. We look back at the panel discussion on fairness and new business models in the AI era and explain why old billing structures no longer work.
Our Director of Media & Campaigns, Iris Handlsberger, discussed at the iab Conference Day how AI is changing the way agency performance is evaluated. Together with Anna Benda (Achtzehn Grad), Stefanie Winkler-Schloffer (A1), and Andreas Vretscha (WPP Media), she shed light on the current discrepancy between expected efficiency and the often invisible groundwork involved in AI projects. The panel’s clear conclusion: Technological progress requires a shift in thinking on both sides, as traditional hourly-rate models tend to penalize rather than encourage innovation in practice.
Photo recap of the panel at the iab Conference Day, Photo credit: Katharina Schiffl
Fair performance, invisible work – renegotiating value, price and quality in the AI era
AI makes everything faster – so it must become cheaper? This misconception persists stubbornly in the market. Many clients’ expectations ignore the strategic and technical groundwork that is essential for successful AI projects. Iris argued clearly in the panel discussion moderated by Julia Eisner: “Those who penalize efficiency with lower hourly rates stifle all innovation.” Traditional hourly billing rewards slowness and stifles technological progress.
At the same time, digital agencies must also adapt their approach. Even the best AI cannot deliver results without a deep, strategic, and holistic understanding of the clients. In the AI era, fairness therefore requires effort from both sides: agencies must make their business models future-proof, while clients must recognize the value of this new, highly skilled work.
Technological progress also gives e-dialog a strategic edge as an agency. The use of AI brings individual units closer together and promotes cross-departmental collaboration. Nevertheless, humans remain indispensable in the curation process: systems must always be critically scrutinized, as machines simply do not understand human traits such as humor, empathy, and cultural understanding.