Those safeguards are not an argument for slowing AI down. They are what allow adoption to proceed with confidence. People should be encouraged to push back when their judgment says the output is wrong. Human challenges belong within formal governance. A decade ago, we were laying the groundwork by automating wells, integrating data and building digital infrastructure. Today, we are using those investments to create an AI-enabled business that makes faster, smarter decisions. The next step is not to make human judgments disappear. It is to make that judgment more informed and effective. Business leaders should therefore be both AI optimists and AI sceptics, empowering teams to deploy these tools to solve complex problems while building the security and validation needed to support decentralized innovation and strengthen institutional trust in AI. Put simply, we must place governance and accountability at the foundation, build skills alongside the rollout, and give people the confidence to challenge outputs based on professional experience. Trust in AI means knowing where responsibility lies and having the skills, safeguards and governance in place to expand its use with confidence.