The Carnegie Mellon University Software Engineering Institute (CMU SEI) invites you to AI Acquisition Bootcamp, a workshop is for people who conduct software acquisition for government, industry, and academic organizations, and who are beginning to procure artificial intelligence (AI) and AI-enabled systems. AI systems provide value and can be exceedingly helpful in the right situation. Current acquisition guidance provides a strong foundation but are not sufficient to identify and effectively assess AI systems such as large language models (LLMs).

Acquisition teams are faced with concerns from leadership of falling behind and ensuring the organization is prepared for the future. Meanwhile end-users have come to expect well-designed systems that are effective and trustworthy. Meeting these competing needs is a major challenge for procurement. In this workshop participants will learn to:

• Identify use cases and applications that are AI-ready
• Assess AI system capabilities
• Enable operational experimentation
• Prepare for effective continuity of capabilities

The facilitators will present emerging practices for procuring AI and AI-enabled systems, including generative AI, which will help acquisition professionals to answer questions such as:

• Does the system adequately address the need?
• Will the system improve the status quo?
• What is the overall cost of ownership?
• What mechanisms are available for testing the system?
• How can we track our progress and measure impact?

The facilitators will introduce actionable guidance and a streamlined approach to support teams in quickly and effectively identifying, assessing, and procuring the best AI systems while reducing risks associated with these major investments. This expedited acquisition approach will result in improved system identification, earlier operationalization, and the effective continuity of capabilities with trustworthy systems that improve human effectiveness.

Workshop Topics

• AI vs. traditional software acquisition
• Assessing AI system capabilities
• Enabling operational experimentation
• Cost of Ownership (training, monitoring, and testing)
• Preparing for continuity of capabilities (continuous monitoring)