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.

Formal AI competency frameworks are still emerging. In their place, innovative companies are assessing employee AI skills with concrete, activity-based targets like "build three custom GPTs for your role" or completing specific certifications, directly linking these achievements to performance reviews.

Webflow accelerates AI tool adoption using company-wide "Builder Days." This combines a top-down executive mandate (e.g., "no meetings without a prototype") with bottoms-up enablement, including tool access, support channels, and prizes. The goal is to move the entire organization up the adoption curve, not just early adopters.

Companies once hired siloed 'digital experts,' a role that became obsolete as digital skills became universal. To avoid repeating this with AI, integrate technologists into current teams and upskill existing members rather than creating an isolated AI function that will fail to scale.

To build an AI-native team, shift the hiring process from reviewing resumes to evaluating portfolios of work. Ask candidates to demonstrate what they've built with AI, their favorite prompt techniques, and apps they wish they could create. This reveals practical skill over credentialism.

To accelerate company-wide skill development, Shopify's CEO mandated that learning and utilizing AI become a formal component of employee performance evaluations. This top-down directive ensured rapid, broad adoption and transformed the company's culture to be 'AI forward,' giving them a competitive edge.

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.

To transform a product organization, first provide universal access to AI tools. Second, support teams with training and 'builder days' led by internal champions. Finally, embed AI proficiency into career ladders to create lasting incentives and institutionalize the change.

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.