Socially constructed artificial intelligence (AI) systems have the potential to reinforce human biases and sustain biased behaviors, creating new social risks and challenges. Tackling gender bias in AI requires a multi-faceted approach and proactive measures throughout the entire AI development and application lifecycle. Addressing gender bias in AI through its causes, types, and mitigation strategies, the paper contributes to a deeper understanding and sensitization of diverse social groups in a digital society. By adopting different suggested mitigating strategies, AI stakeholders can work towards building a fairer, more inclusive, and more respectful gender-diverse future AI.