Health and human services organisations (by design human-focused) are poised at a crossroads as artificial intelligence (AI) transforms industries. They will be forced to find a means to reconcile the practical and ethical hurdles with employing newfangled technology. Deepika Rikhi a prominent advocate of AI governance offers valuable insights into the problems to be solved. Her strategies aim to develop a unified framework tailored to the requirements of health and human services agencies so that these agencies can deploy AI responsibly and consider their organisational realities.   The foundation of AI governance is to develop a standard and precise definition of AI particularly about other technologies such as Robotic Process Automation. Deepika Rikhi indicates the need to do this with stakeholders regarding a common language. AI involves machine learning NLP and predictive analytics—technology beyond mere automation to offer adaptive and intelligent decision-making capabilities.   Businesses will know which AI applications to adopt by clearly defining these distinctions. For example predictive analytics can forecast service needs and natural language processing can ease case management. This degree of clarity helps teams align and ensures that AI investments are impactful and worthwhile.   As applied to artificial intelligence successful governance begins with the development of principles that will guide AI adoption. Such principles must align with the agencys mission in that the technology must support those objectives and not undermine them. Deepika suggests a participatory model where members unite to constitute a multidisciplinary team across organisations with the authority to develop such principles.   This inclusive process assists agencies in developing a shared commitment to core values like fairness transparency and accountability. For instance fairness principles can inform the design and deployment of AI tools to ensure that predictive models do not inadvertently worsen bias or leave out marginalised groups. Therefore governance principles act as a standard for all stages of AI implementation from conception to evaluation.   To make a concrete difference governing principles need to be translated into an operational framework. Deepika calls for frameworks that are transparent actionable and linked to project deliverables. Governing principle mapping to specific project steps ensures that groups are on track and accountable.   Think of the concepts of fairness and neutrality. In practice the target variables can be included in initiating the project assessing related risks and formulating mitigation strategies. By including such checks within the project life cycle agencies can address anticipated ethical or operational pitfalls ahead of time.   Most health and human services agencies are decentralised and different subunits are independent. Therefore fragmentation may pose a critical challenge to concerted AI regulation. Deepika emphasises the necessity of building consensus among such subunits through workshops and interdepartmental meetings.   The most important stakeholders are program operations policy implementation and infrastructure staff. They must work together and adopt consistent governance practices. By giving each subunit a shared framework this collaboration avoids duplication and enhances the success of all AI projects.   AI governance is not just about technology—its about aligning innovation with purpose.. By emphasising inclusivity transparency and practicality states Rikhi agencies can ensure that their AI initiatives serve the people theyd prefer to help. Deepika Rikhis commentary on AI governance gives health and human services agencies a clear roadmap to technology adoption dynamics.. In her article Navigating AI Governance in Health & Human Services: Principles and Implementation Strategy she details her vision which underscores the potential for transformation that AI has when it is addressed by thoughtful principle-guided governance. By defining AI clearly setting governance principles and promoting collaboration among subunits such organisations can leverage AI to enhance service delivery in a way that remains faithful to their core mission. Her idea illustrates the redemptive capacity of AI when framed by principled governance.