The greatest leverage from AI comes not from accelerating individual tasks, but from improving information flow between teams. Use AI to create a "common brain"—a central repository of project knowledge and goals—to ensure alignment and drive efficiency at critical handoff points.
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The next wave of AI productivity won't come from crafting the perfect prompt. Instead, professionals must adopt a manager's mindset: defining outcomes, assembling AI agent teams, providing context, and reviewing their work, transforming everyone into an "agent orchestrator."
The most significant productivity gains come from applying AI to every stage of development, including research, planning, product marketing, and status updates. Limiting AI to just code generation misses the larger opportunity to automate the entire engineering process.
AI curiosity involves individuals testing tools in isolation. AI fluency is a collective capability where teams share a common language, integrated workflows, and a foundational understanding of how AI drives strategy. This fluency is built through consistent, shared learning and processes.
Early AI adoption by PMs is often a 'single-player' activity. The next step is a 'multiplayer' experience where the entire team operates from a shared AI knowledge base, which breaks down silos by automatically signaling dependencies and overlapping work.
Shift your view of AI from a passive chatbot to an active knowledge-capture system. The greatest value comes from AI designed to prompt team members for their unique insights, then storing and attributing that information. This transforms fleeting tribal knowledge into a permanent, searchable organizational asset.
A simple, on-premise AI can act as a "buddy" by reading internal documents that employees are too busy for. It can then offer contextual suggestions, like how other teams approach a task, to foster cross-functional awareness and improve company culture, especially for remote and distributed teams.
The greatest value of AI isn't just automating tasks within your current process. Leaders should use AI to fundamentally question the workflow itself, asking it to suggest entirely new, more efficient, and innovative ways to achieve business goals.
Today, most AI use is siloed, with individuals prompting alone. The real value is unlocked when AI becomes a team sport, with specialists building systems that are shared, iterated upon, and used collaboratively across the entire organization.
Apply the collaborative, iterative model of AI pair programming to all knowledge work, including writing, strategy, and planning. This shifts the dynamic from a simple command-and-response tool to a constant thought partner, improving the quality and speed of all your work.
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.
