Agencies can optimize the performance of their IT systems and applications by taking a comprehensive approach to collecting and analyzing data. Artificial intelligence, and a unified data platform, can help agencies maximize those observability efforts.
Mismanaged data can lead to poor decision-making, loss of trust, increased risk and other fallout, and artificial intelligence has made data use more complicated. Fast, secure, energy-efficient data storage, however, helps agencies manage what they have.
In the journey toward building more equitable and inclusive AI systems, diversity is not just a buzzword — it’s a fundamental principle that must be embraced at every stage of development and implementation.
RPA has been a dominate force in automating and enhancing digital efficiency in government operations, yet the lure of AI threatens its continued use and expansion.
Civic tech is a vital way to improve constituent trust, and there’s a lot of potential for it to develop and grow.
Dive into the heart of MLOps, where data science meets DevOps, ensuring seamless integration of machine learning models into production. Discover the essential practices and tools for automating, monitoring, and managing the entire ML lifecycle.
This CX CoP recap covers how digital forms are changing agencies.
Agencies are making greater use of artificial intelligence (AI), or at least preparing to. But the skills required to work successfully with AI are far more than simply technical — often they’re unrelated to IT. Here are AI skills agencies should look for as they develop their workforces and recruit new talent.
As agencies handle massive amounts of data, they’ve lost the ability to easily access it. Learn how integration platform as a service (iPaaS) can help.
Recent advances have made it deceptively easy to build artificial intelligence (AI)-driven applications. But that doesn’t mean that testing AI-based software should be quick as well. Testing should be thorough, and performed by independent teams.
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