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.

Exceptional people in flawed systems will produce subpar results. Before focusing on individual performance, leaders must ensure the underlying systems are reliable and resilient. As shown by the Southwest Airlines software meltdown, blaming employees for systemic failures masks the root cause and prevents meaningful improvement.

Leaders often feel they must have all the answers, which stifles team contribution. A better approach is to hire domain experts smarter than you, actively listen to their ideas, and empower them. This creates a culture where everyone learns and the entire company's performance rises.

The "attitude vs. aptitude" debate is flawed. Instead, hire the person with the smallest skill deficiency relative to the role's requirements. For a cashier, attitude is the harder skill to train. For an AI researcher, technical aptitude is. The key question is always: is it worth our resources to train this specific gap?

Leaders often avoid sharing negative news to "not scare the children." However, this creates an information vacuum that teams will fill with the "darkest ideas available" from other sources. Leaders must compete with misinformation by providing clear, honest context, even when it's difficult.

A project's success equals its technical quality multiplied by team acceptance. Technologists often fail by engineering perfect solutions that nobody buys into or owns. An 80%-correct solution fiercely defended by the team will always outperform a "perfect" one that is ignored.

Many leaders are candid in broad strokes but fail to have direct, difficult conversations with individuals they personally like. This avoidance stems from a desire not to hurt feelings but inevitably leads to underperformance and greater problems down the line.

Instead of faking expertise, openly admitting ignorance about technical details builds trust and empowers specialists. This allows you to focus on the 'what' and 'why' of the user experience, giving engineers and designers the autonomy to own the 'how', which fosters a more collaborative and effective environment.

Complete transparency can create panic and demotivation. A leader's role is to filter harsh realities, like potential layoffs, and deliver an authentic message that is both realistic and optimistic enough for the team to absorb productively, rather than sharing every fear.