Reputation management is a critical component to business success the world over, so why are government agencies failing to manage their own reputation?
The terms ‘automation, ‘artificial intelligence,’ and ‘machine learning’ are hot topics in a lot of government technology conversations. These terms are often used interchangeably and sometimes incorrectly, which can be confusing. Let’s take a look at what this tech jargon means.
Government IT departments are facing the exact challenge of when, what and how to upgrade, as their applications become growingly outmoded and user experience suffers.
When the military is able to properly ingest, sort, store and analyze data about its equipment and vehicles, it can predict everything from machine failure to maintenance needs before breakdowns happen, saving effort, time, money and possibly lives.
RPA features software bots handling easy, rules-based activities that might traditionally fall into the “busy work” category.
Across the board, government agencies are looking to implement tools that can increase productivity in any way possible. Artificial Intelligence (AI) has found its way to the top of the list, with many agencies looking to incorporate it to improve the work that their staff is able to do.
Using artificial intelligence in government agencies is changing engagement models.
While the pace of technological advancement is exiting, it poses challenges for government. We are constantly having to evolve to meet citizens’ expectations, making the “future of financial management” a moving target.
Algorithms are the set of rules for solving a problem in a finite number of steps, and they are also a hot topic in the technology world.
While AI provides significant advantages, it can be challenging to adopt without the right computing and development resources to enable it. Many government agencies, however, still struggle with legacy and outdated IT infrastructures. That’s why a trusted and robust cloud infrastructure is a critical component of the DoD’s journey to AI and machine learning.