To overcome the fear of new AI technology, block out dedicated, unstructured "playtime" in your calendar. This low-pressure approach encourages experimentation, helping you build the essential skill of quickly learning and applying new tools without being afraid to fail.

Merely buying AI tools (10% of budget) and managing execution (20%) is insufficient for ROI. Former Microsoft and Google exec Priyanka Vergadia advises dedicating 70% of the budget to upskilling employees. This focus on education is critical for building a true 'AI habit' and moving beyond experimentation to production.

Simply buying an AI tool is insufficient for understanding its potential or deriving value. Leaders feeling behind in AI must actively participate in the deployment process—training the model, handling errors, and iterating daily. Passive ownership and delegation yield zero learning.

In the AI era, leaders' decades-old intuitions may be wrong. To lead effectively, they must become practitioners again, actively learning and using AI daily. The CEO of Rackspace blocks out 4-6 a.m. for "catching up with AI," demonstrating the required commitment to rebuild foundational knowledge.

To effectively learn AI, one must make a conscious mindset shift. This involves consistently attempting to solve problems with AI first, even small ones. This discipline integrates the tool into daily workflows and builds practical expertise faster than sporadic, large-scale projects.

Instead of passively learning about AI, executives should actively deploy a simple agentic product. This hands-on experience of training and QA provides far more valuable, practical knowledge than any course or subscription, putting you ahead of 90% of peers.

Leaders getting hands-on with AI development should expect a slow start. The first few weeks may feel flat with minimal progress. However, once foundational concepts click, the learning and productivity curve becomes exponential, leading to rapid, transformative advancement.

The primary obstacle preventing users from getting more value from AI is a lack of time for learning and experimentation. This outweighs other factors like corporate policy or access to tools, suggesting that dedicated learning time is the most critical investment for organizations seeking AI mastery.

Becoming an expert in AI agents is not a sporadic effort but a deliberate, daily practice. The advantage goes to those who commit to learning the new paradigm, similar to how early, dedicated adopters of Google AdWords built massive e-commerce businesses while competitors stuck to traditional methods.