Don't try to optimize your strongest departments with your first AI project. Instead, target 'layup roles'—areas where processes are broken or work isn't getting done. The bar for success is lower, making it easier to get a quick, impactful win.

A common mistake leaders make is buying powerful AI tools and forcing them into outdated processes, leading to failed pilots and wasted money. True transformation requires reimagining how people think, collaborate, and work *before* inserting revolutionary technology, not after.

Rushing to adopt AI tools without a clear strategy and established workflows leads to chaos, not efficiency. AI should be the fourth step in a system, used to strategically uplevel your team and enhance proven processes, rather than just creating more noise or automating a broken system.

A critical error in AI integration is automating existing, often clunky, processes. Instead, companies should use AI as an opportunity to fundamentally rethink and redesign workflows from the ground up to achieve the desired outcome in a more efficient and customer-centric way.

Instead of adding AI tools to existing workflows, Qualcomm is radically redesigning its marketing department. The new model places a foundational AI systems architecture at the core, with processes and people organized around it. This holistic approach aims for true transformation rather than incremental efficiency gains.

Before any AI is built, deep workflow discovery is critical. This involves partnering with subject matter experts to map cross-functional processes, data flows, and user needs. AI currently cannot uncover these essential nuances on its own, making this human-centric step non-negotiable for success.

To maximize AI's impact, don't just find isolated use cases for content or demand gen teams. Instead, map a core process like a campaign workflow and apply AI to augment each stage, from strategy and creation to localization and measurement. AI is workflow-native, not function-native.

Don't just plug AI into your current processes, as this often creates more complexity and inefficiency. The correct approach is to discard existing workflows and redesign them from the ground up, based on the new paradigms AI introduces, like skipping a product requirements document entirely.

Avoid paralysis of choice in the crowded AI tool market. Instead of chasing trends, identify the single most inefficient process in your marketing organization—in budget, time, or headcount—and apply a targeted, best-of-breed AI solution to solve that specific problem first.