Presented by AWS Marketplace
Speaker: Ravi Raghava, CTO for the Civilian Business Group, SAIC
Ravi Raghava outlines how Generative AI is driving efficiencies across federal operations. From streamlining citizen services to automating complex workflows, AI offers transformative potential for government agencies. Raghava shares specific examples, such as accelerated claims processing and application development, as key areas where AI is making an impact.
He also discusses the importance of modular procurement approaches, such as Other Transaction Authorities (OTAs) and challenge-based acquisitions, to reduce procurement timelines and foster innovation. These agile contracting mechanisms enable faster experimentation and deployment of AI solutions.
Ethics, fairness, and security remain top priorities for Raghava. He advocates for a comprehensive framework to ensure responsible AI use, addressing unintended biases and ethical considerations while driving mission outcomes.
Key Takeaways:
- Generative AI accelerates citizen-focused services like claims processing and records management.
- Modular contracting options like OTAs and challenge-based acquisitions can speed AI adoption.
- Ethical AI frameworks must address fairness, efficacy, and unintended biases.
This interview appeared in the program Speed to Mission: Accelerate GenAI Adoption Through Procurement Innovation which was released on February 4, 2025. Generative Artificial Intelligence (GenAI) is poised to revolutionize operations across federal agencies, from enhancing citizen services to bolstering national security. However, the rapid pace of AI advancements presents challenges, especially in procurement and implementation. In this special program, recorded live at AWS: Reinvent in Las Vegas, host Francis Rose engages with government and industry leaders to uncover how agencies are navigating these complexities. The program sheds light on innovative procurement methods, critical mission outcomes, and the collaborative efforts shaping AI’s future in the federal space.