We rigorously test software upgrades in a staging environment before going live, yet we expect humans to adopt new skills immediately after a training session. Employees need safe spaces to practice new behaviors, like communication, through repetition.
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For door-to-door sales, training must approximate field conditions. Install freestanding doors for reps to physically knock, practice scripts, and even run between them to build muscle memory and desensitize them to the real environment, including aggressive role-playing.
The biggest resistance to adopting AI coding tools in large companies isn't security or technical limitations, but the challenge of teaching teams new workflows. Success requires not just providing the tool, but actively training people to change their daily habits to leverage it effectively.
True AI adoption requires more than technical know-how. Salesforce's internal training mandates proficiency in Agent skills (AI literacy), Human skills (adaptability, EQ), and Business skills (problem-solving, storytelling), recognizing that technology is only one part of the transformation.
Organizations fail when they push teams directly into using AI for business outcomes ("architect mode"). Instead, they must first provide dedicated time and resources for unstructured play ("sandbox mode"). This experimentation phase is essential for building the skills and comfort needed to apply AI effectively to strategic goals.
Forcing reps to perform in front of the entire C-suite creates a critical, high-pressure environment that is counterproductive to learning. Successful enablement requires a phased approach with pre-training and post-event reinforcement using real-world customer calls, not just high-stakes internal role-plays.
Standalone training often fails to translate into practice. Coaching acts as a powerful accelerator when paired with a specific learning experience, driving up the implementation of new skills and behaviors by 400% and accelerating adoption up to four times faster.
When introducing a new skill like user interviews, initially focus on quantity over quality. Creating a competition for the "most interviews" helps people put in the reps needed to build muscle memory. This vanity metric should be temporary and replaced with quality-focused measures once the habit is formed.
To accelerate growth for talented individuals, give them responsibility where their failure rate is between one-third and two-thirds. Most corporate roles are over-scaffolded with a near-zero chance of failure, which stifles learning. High potential for failure is a feature, not a bug.
Employees hesitate to use new AI tools for fear of looking foolish or getting fired for misuse. Successful adoption depends less on training courses and more on creating a safe environment with clear guardrails that encourages experimentation without penalty.
A rehearsal is like a friendly match—a final check. Training is the practice that builds core skills: developing the storyline in managers' own words, coordinating team interaction, and mastering Q&A. Training allows for pausing, analyzing, and iterating on delivery.
