Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/5133
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dc.contributor.authorRyan Novak, Justin Raines-
dc.contributor.authorChristopher R. Barlow, Kevin M. Forbes-
dc.contributor.authorRachel T. Giachinta, Jay Kim-
dc.contributor.authorZachary G. Levenson, Stephen W. Roe-
dc.date.accessioned2024-06-03T13:45:11Z-
dc.date.available2024-06-03T13:45:11Z-
dc.date.issued2024-05-01-
dc.identifier.citationAPAen_US
dc.identifier.urihttps://dair.nps.edu/handle/123456789/5133-
dc.descriptionSYM Paperen_US
dc.description.abstractThe extraordinary advancement of Artificial intelligence (AI) technology emerges at a critical juncture in which the Federal acquisition workforce is ill-equipped to meet the sky rocketing demand for products and services, alike. AI poses the opportunity to overcome data-intensive, laborious tasks and expedite the speed in which acquisition professionals operate; potential benefits may increase efficiency, enhance transparency, and reduce workload. While the use of AI across the Federal Government differs between agencies, the significance and scrutiny of Government Acquisition makes implementing AI across the acquisition process uniquely challenging. This paper will explore the current state of AI; who (i.e., which agencies) and how AI currently supports the acquisition process across the Federal Government. Next, the future state of AI and anticipated applications for the acquisition community will be discussed…think the future, think the next generation of Acquisition! This will be developed through strategic exploration across thought leaders, academic research, and working within our own AI model for acquisition. Next, we will discuss how the risks of this new technology -- new tools and novel concepts -- introduce both procedural, ethical, and operational risks that must be taken into consideration. Finally, we will offer a set of recommendations on how best to implement AI in the acquisition process as well as a list of best practices to maximize utility, mitigate risks, and ensure the acquisition workforce is well positioned to embrace the benefits and efficiencies of integrating AI capabilities.en_US
dc.description.sponsorshipARPen_US
dc.language.isoen_USen_US
dc.publisherAcquisition Research Programen_US
dc.relation.ispartofseriesAcquisition Management;SYM-AM-24-070-
dc.subjectArtificial Intelligence (AI)en_US
dc.subjectGenerative AIen_US
dc.subjectNeural Networksen_US
dc.subjectComputer Visionen_US
dc.subjectRoboticsen_US
dc.subjectMaching Learningen_US
dc.subjectAutomationen_US
dc.subjectReinforcement Learningen_US
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectNatural Language Generation (NLG)en_US
dc.titleEnhancing Acquisition Outcomes through Leveraging of Artificial Intelligenceen_US
dc.typeTechnical Reporten_US
Appears in Collections:Annual Acquisition Research Symposium Proceedings & Presentations

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