Joel argues that traditional agency-led creative processes are becoming obsolete as AI ad factories produce ads at scale. He cites a retail brand that resisted automation and lost market share to faster competitors using automated production and targeting.
Todd argues that brand managers who stick to traditional campaigns miss how demand works as a network of variables that affect each other. Adaptive AI advertising surfaces those feedback loops and supports continuous learning over one-variable-at-a-time seasonal optimization.
Todd argues that marketers who adopt AI ad tools without validating their impact create blind spots in customer insights. He says human oversight is still needed to interpret AI outputs, and that he and Jeff Greenfield have concrete examples to share.
Todd argues that sophisticated AI ad tools are stalling because of algorithmic complexity and steep learning curves. Over-reliance on AI risks campaigns that lack human touch, so data must be paired with creativity and strategic integration.
Todd argues that AI has become its own media channel, pulling budget from performance channels. With a third of ad spend already concentrated on about ten platforms, Todd warns against chasing hype and urges optimizing existing platforms and prioritizing actionable metrics.