After AI system owners and developers have used a self-assessment to identify inherent AI risks and make informed design decisions, and after they consulted technical playbooks to understand at a granular level what actions to take, they will require software tools to improve upon their AI systems. These tools can be open source or acquired solutions and are designed to address risk areas like fairness, explainability, and robustness. As organizations weigh the costs and benefits of building vs. buying solutions they will require a comprehensive understanding of the software landscape including real costs, customization, and the levels or proficiency required to effectively leverage the tools.