Many marketing teams haven't adapted their organizational design for the internet era, which demands disciplines like experience design. They cling to the 'art and copy' model from the 1950s, making them unprepared for the systemic, synthetic challenges of the AI era.

As users delegate purchasing and research to AI agents, brands will lose control over the buyer's journey. Websites must be optimized for agent-to-agent communication, not just human interaction, as AI assistants will find, compare, and even purchase products autonomously.

Adopting AI without a unified marketing foundation amplifies existing silos and disconnected workflows, leading to more fragmented content and irrelevant personalization. The solution is to fix the underlying operating model and data context before scaling with AI.

Structuring marketing teams in channel-specific silos forces them to optimize for internal structures rather than the fluid, non-linear path customers actually take. This creates a fragmented view of performance, leading to wasted effort and missed opportunities.

The traditional buyer journey is being upended as users turn to AI search for direct, synthesized answers, bypassing top-of-funnel discovery on brand websites. The marketing focus must shift from traditional SEO to a new discipline of influencing AI recommendation engines to ensure brand inclusion.

In unobservable channels like AI platforms, traditional attribution is impossible. The first credible signal of success is simply showing up. Leaders should conduct a "visibility audit" by systematically prompting AI with customer queries to track if—and how accurately—their brand appears. This is more urgent than measuring conversion.

Success in AI search requires a unified effort from PR, social, SEO, and brand teams. Most companies fail because these teams operate independently with separate metrics, preventing the holistic, multi-platform presence that LLMs reward and use for training.

When customers use AI for product discovery, brands lose visibility into crucial pre-purchase behavior like comparison shopping. This interaction data becomes siloed within the third-party AI platform, creating a new blind spot that makes it difficult to measure marketing impact or understand the customer journey.

AI will fragment the customer journey across countless platforms, moving purchases away from brand-owned websites. Retailers must build systems to manage inventory and product information across this decentralized landscape, not just focus on perfecting their own site experience.