Aligning Artificial Intelligence and Digital Transformation for Government

Data classification, data center capacity, data integrity and data storage are all key challenges that government CIOs are facing when embracing the new frontier of Artificial Intelligence (AI).

It is critical to focus on how AI can lead to true digital transformation, as well as the ability embrace exploration to solve these critical mission challenges. In addition, AI is poised to augment workloads to free up government employees to focus on more important work, while also not replacing employees. 

These were some of the key themes of the recent “AI for Government Summit: Taking the Lead in a New Era” event, hosted by FedInsider earlier this month. The event featured insights from key government leaders from the Department of Homeland Security, the Department of Energy, and the Department of Labor. Industry speakers from NVIDIA, AWS, Google Public Sector and OpenAI were also on hand at the event.

Alex Spithas, Director, Project Integration at Makpar; and Nick Sibley, Director, Agile at Makpar, both attended the event, and came back with many learnings worthy of sharing.

Modernizing the Data Center – AI Infrastructure

Featuring executives from the National Telecommunications and Information Administration, as well as NVIDIA, this session highlighted how introducing AI into data center modernization presents many new considerations. Here are some insights from the panel:

  • AI is good at pattern recognition, but we need to make data inference the new standard to have data be more contextual and operational.

  • Data center capacity is one of the biggest inhibitors of growth in AI.

  • Industry must play a key role in helping government get their data infrastructure ready for AI.

  • The overall focus of data center modernization should be less about the technology, and more about digital transformation overall.

  • Data security and classification remain a challenge.

Cybersecurity and AI – Safeguarding the Government

Featuring executives from the Department of Energy, as well as Google Public Sector and HPE,

this panel discussed how AI can help ensure data privacy, protect critical infrastructure through threat detection and prevention, predictive analysis, and real-time monitoring. Here are some insights from the panel:

  • Most agency CIOs are concerned about data confidentiality, but less so with regards to data integrity and poisoning the data. The priority is threats coming in over the threats coming out from the data.

  • Many agency leaders are less scared of Generative AI, but are more concerned about what comes after, which could be more quantum focused.

  • Agencies such as U.S. Citizenship and Immigration Services are using a risk-based approach to how they were automating data.

Other insights from the event were around how AI requires high-speed data lakes, and how the supply chain cannot support the coming power surge from AI. To date, companies like NVIDIA have helped pilot these efforts in underpopulated areas of the U.S. But this challenge will persist in the future.

When it comes to AI use cases, the Department of Homeland Security plans on using AI to speed up the immigration process, which often involves hundreds of different records. Ultimately, this will require vast amounts of data storage and access. In addition, Army chaplains are using Generative AI to write their sermons, which frees them up to focus on the spiritual needs of their communities. 

It is clear that government and industry leaders are addressing key challenges for bringing AI to life in the federal arena. By aligning AI with digital transformation efforts, it will be possible for government to safely and effectively make AI a critical foundation for mission success.

Makpar offers the following AI informational resources to help agencies fully embrace AI for mission success:

If you would like to learn more about how Makpar can help your agency develop the most comprehensive AI solutions for enhancing mission success, please contact us here.   

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