By 2025, significant changes in AI are anticipated, with an emphasis on collaborative AI systems, where specialized agents work together under human guidance. These multi-agent systems are expected to address complex issues in fields like health, education, and finance. New approaches to human-AI collaboration will emerge, alongside increased demands for demonstrating AI's real-world benefits. However, the rise of generative AI may lead to more sophisticated scams, while U. S. regulation could weaken, potentially leading to a patchwork regulatory landscape influenced by states and international players. The deployment of AI agents is expanding beyond research to practical applications, such as interfaces that automate tasks on computers. Despite the promise of these tools, concerns remain about potential risks.

Meanwhile, large AI models are improving more slowly, with debates on whether AI development is plateauing. AI's role in scams, particularly audio deepfakes, may grow, and consumer protection might weaken under a new administration. Organizations will need to enhance public education about such threats, especially for non-English speakers. Complex AI systems resembling "general contractors" will emerge, combining varied AI specialties for problem-solving in simulations, health, finance, and education. In education, there will be a focus on multimodal AI models, necessitating critical evaluation of what genuinely enhances learning. In healthcare, developers must validate AI's claimed benefits, with a shift towards transparent benchmark standards becoming mainstream. High-impact applications will use AI teams with diverse expertise, leading to more effective solutions. Finally, the paradigm of human-AI collaboration will evolve, emphasizing the importance of optimizing human-AI partnerships for collective intelligence and assessing associated risks. As AI capabilities grow, so too will the need for comprehensive risk assessment strategies.