T he use of AI in both the private and public sectors is a game changer. AI can help teams rapidly analyze vast amounts of data, enabling insights that can save significant time and resources. Businesses use AI to optimize enterprise resource systems, automate routine tasks, forecast consumer demand and behavior, and even innovate new products and services.
agement, predictive models can assess supplier reliability and anticipate disrup- tions, allowing for better contingency planning. For cost estimation and life- cycle management, analytics can provide accurate cost predictions and forecast maintenance needs, leading to proactive planning and cost savings. Performance optimization is achieved by predicting contractor performance and optimizing operations to reduce downtime. It also supports talent and workforce planning by forecasting skill requirements and contractor staffing needs. Strategic de- cision support is enhanced through sce- nario planning and investment prioritiza- tion, while technology development and innovation forecasting help to identify emerging technologies. One of the key themes from this answer is forecasting future DoD needs in a proactive manner, using data to make informed decisions and optimize performance. This indicates two important benefits to acquisition strategy development. The acquisi- tion strategy must consider future events well beyond the initial con- tracting action since it establishes a framework for the full system life cycle over many years, and even de- cades. Predicting trends and future
Likewise, government agencies use AI to strengthen cybersecurity, ac- celerate data analysis, and even help commanders accelerate operational execution. While various uses of AI in acquisition are still being explored, there is little debate on the benefits. Before getting into AI and acqui- sition strategy development, let’s briefly review the two types of AI (predictive and generative) and how we might apply them. Predictive AI Also known as predictive analyt- ics, predictive AI employs machine learning to incorporate vast amounts of data and has been used for applica- tions like insurance underwriting for centuries, even by Lloyd’s of London in the late 1600s. In today’s environment, machine learning software develops a predic- tive model that finds patterns in the data and uses these patterns to make predictions. The model can also iden- tify data anomalies that can be useful for applications like cybersecurity and risk mitigations. The typical business case involves using the AI-generated predictions to support business de- cisions that drive results such as in- creased sales and profits, additional customers, new products, and other business goals. Using predictive AI in acquisi- tion can take many forms. The fol- lowing is a summary of ChatGPT’s and Microsoft Co-Pilot’s response to the question, “In what ways could predictive analytics be used in defense acquisition?” Predictive analytics can significantly enhance defense acquisition in several ways. It can improve demand forecasting and budgeting by predicting costs and anticipating future needs, thus helping to set accurate budgets and allocate funds efficiently. In supply chain risk man-
scenarios can add great value as Inte- grated Product Teams (IPTs) consider what elements should be tailored to the strategy to position the program for future success. The second benefit is derived from data-driven strategy decisions. Leveraging AI to rapidly analyze vast amounts of data enables IPTs to gain insights and patterns that may not be readily apparent without using the tool. AI can also save time and resources previously used on manual work or analytical methods. Using AI in support of an acqui- sition strategy can result in data- informed decisions, accelerated ac- quisition cycle time, saved resources, and help deliver greater value to the Warfighter. For example, an IPT is assessing long-term sustainment as part of the acquisition strategy for a new weapon system. The ma- chine learning models expand the dimension of market research from the current state to what is com- ing, enabling informed decisions on current and future requirements. By
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