The fields of human-robot collaboration, artificial intelligence, and human-AI collaboration are converging towards a common goal: developing systems that can effectively collaborate with humans and enhance their capabilities. A key theme emerging from recent research is the importance of adaptive, context-aware communication and personalized interaction. Noteworthy studies have found that verbal communication can be more effective than non-verbal cues in high-stakes environments, and that multimodal strategies are essential for effective group conversation design. The development of AI systems that can explain their reasoning and decisions in human-understandable ways is also gaining traction, with applications in areas such as biodiversity monitoring and conservation. Furthermore, researchers are exploring the complex relationships between trust, knowledge transfer, and cooperation between humans and AI, with a focus on developing more effective and efficient collaboration frameworks. The use of AI-powered tools, such as chatbots and large language models, is being examined in various contexts, including education, family life, and mental health. Overall, the field is moving towards more human-centric, transparent, and explainable AI solutions that prioritize user well-being and agency.