Convincing users to adopt AI agents hinges on building trust through flawless execution. The key is creating a "lightbulb moment" where the agent works so perfectly it feels life-changing. This is more effective than any incentive, and advances in coding agents are now making such moments possible for general knowledge work.

Leaders must resist the temptation to deploy the most powerful AI model simply for a competitive edge. The primary strategic question for any AI initiative should be defining the necessary level of trustworthiness for its specific task and establishing who is accountable if it fails, before deployment begins.

To trust an agentic AI, users need to see its work, just as a manager would with a new intern. Design patterns like "stream of thought" (showing the AI reasoning) or "planning mode" (presenting an action plan before executing) make the AI's logic legible and give users a chance to intervene, building crucial trust.

Implementing trust isn't a massive, year-long project. It's about developing a "muscle" for small, consistent actions like adding a badge, clarifying data retention, or citing sources. These low-cost, high-value changes can be integrated into regular product development cycles.

As AI automates partnership functions, it risks creating impersonal distance. To succeed, organizations must counter this by proactively accelerating human trust. Implementing a shared framework, like a "trust index," creates a common language for trust-building at the same pace as technological change.

Many believe once trust is lost, it's gone forever. However, it can be rebuilt. The process requires transparently admitting the mistake and, crucially, following up with tangible actions that prove the organization has changed its ways. A mere apology is insufficient; you must 'walk the walk'.

For startups, trust is a fragile asset. Rather than viewing AI ethics as a compliance issue, founders should see it as a competitive advantage. Being transparent about data use and avoiding manipulative personalization builds brand loyalty that compounds faster and is more durable than short-term growth hacks.

Dr. Fei-Fei Li asserts that trust in the AI age remains a fundamentally human responsibility that operates on individual, community, and societal levels. It's not a technical feature to be coded but a social norm to be established. Entrepreneurs must build products and companies where human agency is the source of trust from day one.

To convince people of AI's utility, abstract arguments are ineffective. Instead, share personal anecdotes where AI provided critical help in high-stakes situations, such as a medical crisis. This demonstrates a strong 'revealed preference' that lands with more emotional and logical weight.