Policy & Practice | Summer 2025

caseworkers to focus on critical and high-priority cases. By leveraging AI’s ability to quickly analyze vast amounts of data, agencies can priori tize new reports of child abuse and neglect more efficiently, ensuring urgent cases receive immediate atten tion. This efficiency saves time and enables effective interventions to protect children at risk. Furthermore, the reduction in repetitive and administrative tasks helps alleviate caseworker burnout, improves job satisfaction, and enhances overall workforce well-being. Reducing Human Error One of the significant advantages of AI in child welfare is its potential to reduce human error and bias. AI systems can process and cross-refer ence data with precision, identifying patterns and risks that may be over looked. Incorporating policy, statute, and legislation into AI model learning supports more consistent application, rather than varied interpretations by different caseworkers. AI systems are less influenced by subjective judg ments and personal biases, thereby promoting fairness and consistency when informing human decision making. This capability enhances the accuracy of screening decisions, contributing to improved experiences with the system and better outcomes for children and families. Identifying Patterns of Risk AI-powered tools can play a sig nificant role in continuous quality improvement in child welfare practice. These tools can assist in identifying patterns of risk that might otherwise go unnoticed. By analyzing historical data and detecting trends, AI can flag potential issues before they escalate. Furthermore, AI can provide detailed feedback and insights based on real-time data, allowing agencies to continually refine and improve their processes. This proactive approach to risk management is invaluable in safe guarding children and ensuring timely interventions while also fostering an environment of ongoing enhancement and adaptation in child welfare services.

Training and Adaptation for Caseworkers The successful integration of AI tools depends not only on providing caseworkers with comprehensive training but also on effective orga nizational change management. Educational programs are indis pensable in helping caseworkers understand how to interpret AI rec ommendations and use the system effectively. Training should emphasize that AI is designed to enhance, not replace, professional judgment. However, training alone is insuf ficient. Organizational change management plays a critical role in ensuring that caseworkers embrace and adapt to AI-assisted workflows. This involves creating a supportive environment that encourages con tinuous learning, flexibility, and collaboration. Change management strategies should include clear com munication about the benefits and goals of AI integration, as well as address any concerns or resistance. By coupling training with robust organizational change management, agencies can ensure a smoother tran sition, foster acceptance, and fully leverage the tool’s benefits. Ongoing education, support, and a culture of innovation are essential for

caseworkers to adapt effectively and maximize the potential of AI tools in enhancing child welfare services. Call to Action The integration of AI-powered intake tools into child welfare services offers transformative potential for how agencies engage with the public and families. This journey requires careful steps. By embracing innovation, child welfare agencies can significantly improve their ability to safeguard children and provide timely interven tions. It is crucial to commit to ongoing education, support, and a culture of continuous improvement to maximize the benefits of AI tools. This call to action urges child welfare agencies to prioritize these key areas, ensuring a smoother transition, fostering acceptance, and ultimately enhancing the overall effectiveness and safety of child welfare services. The commitment to innovation, transparency, and human-centered practices will be instrumental in creating a more efficient and protective system for children and families. Paige Rosemond , MSW, is the Director of Innovation and NM Impact Project Executive at RedMane Technology LLC.

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Summer 2025 Policy & Practice