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.
Business leaders often assume their teams are independently adopting AI. In reality, employees are hesitant to admit they don't know how to use it effectively and are waiting for formal training and a clear strategy. The responsibility falls on leadership to initiate AI education.
To prepare for a future of human-AI collaboration, technology adoption is not enough. Leaders must actively build AI fluency within their teams by personally engaging with the tools. This hands-on approach models curiosity and confidence, creating a culture where it's safe to experiment, learn, and even fail with new technology.
The best test of knowledge is the ability to teach it. By having employees explain a new AI tool or workflow to their peers, they are forced to solidify their own understanding and identify knowledge gaps. This process turns passive learning into active expertise.
While tracking business outcomes is vital, the most predictive KPI for successful AI transformation is an "AI Fluency Score." This tracks team members' participation in activities like training and tool usage. This leading indicator of adoption is directly correlated with downstream business results.
To make AI adoption tangible, Zapier built rubrics defining "AI fluency" for different roles and seniority levels. By making these skills a measurable part of performance reviews and rewards, you create clear incentives for employees to invest their time in developing them, as behavior follows what gets measured.
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.
To ensure AI adoption is a core competency, formally integrate it into your team's operating system. Webflow is redoing its career ladder to make AI fluency a requirement for advancement, expecting team members not just to use tools but to lead, own, and push the boundaries of AI in their work.
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.
The key to leveraging AI in sales isn't just about learning new tools. It's about embedding AI into the company's culture, making it a natural part of every process from forecasting to customer success. This cultural integration is what unlocks its full potential, moving beyond simple technical usage.
The most successful companies are those that fundamentally re-architect their culture and workflows around AI. This goes beyond implementing tools; it involves a top-down mandate to prepare the entire organization for future, more powerful AI, as exemplified by AppLovin's aggressive adoption strategy.