AI tools empower cross-functional work (e.g., PMs coding), creating temporary role confusion. However, Netflix's CPTO argues this fluidity accelerates prototyping without replacing the deep, scarce expertise of specialized roles. The core craft of engineering, design, and data science remains essential for quality and scale.

Effective AI adoption requires more than technical skill; it requires a 'pilot mindset'. This involves cultivating high agency (a sense of ownership and control) and high optimism about the technology's potential. Organizations should offer mindset training alongside tool training to foster curiosity and confident experimentation.

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.

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.

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.

For roles leveraging new technologies like AI, where tools are nascent and constantly changing, competency is a fleeting metric. Instead, hire for curiosity. A curious mind will adapt, learn, and master new tools as they emerge, making them a more valuable long-term asset.

Netflix's CPTO observes that the value of narrow, deep specialization is declining. While still crucial for certain niche technologies, the preference is shifting toward adaptable generalists who can work across functions and stacks. The modern mindset is "I can learn that quickly" rather than sticking to one expertise.

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.

Recognizing that providing tools is insufficient, LinkedIn is making "AI agency and fluency" a core part of its performance evaluation and calibration process. This formalizes the expectation that employees must actively use AI tools to succeed, moving adoption from voluntary to a career necessity.