Attitudes about work have changed, due in large part to advances in technology. Thanks to the internet and cloud-native applications, individuals can work together virtually from anywhere, at any time. Government employees can be constantly connected to each other and their constituents.
A consequence of this transformation is that agencies can be inundated with work, without a commensurate increase in the financial and staff resources to handle large volumes of data. In order to be successful, agencies need newer, more agile ways of working.
To this end, machine learning has become a key driver of work transformation. Once reserved for specialized applications, machine learning is now incorporated in everyday applications as a standard feature. Here are a few of the ways machine learning is revolutionizing workplace transformation.
Machine Learning Reduces Learning Curves
Prior to the advent of machine learning, manipulating data in software applications meant going through a lengthy learning curve. It took new users time to master the tools designed to increase their productivity.
With machine learning, users can cut down that investment in time to benefit their agencies. This technology allows users to engage applications with natural language commands, instead of learning complex processes to draw information from multiple data sets. Users can simply type in a question and receive an answer. Applications using machine learning can understand the question and conduct the correct processes, simple or complex, in the background.
Machine Learning Saves Time and Encourages Productivity
Machine learning isn’t limited to automating processes associated with large volumes of data, it’s also used to increase productivity using ‘auto-suggestion’ technology. Through auto-suggestion, the application predicts the information a user is seeking and delivers it ahead of time. An example is when someone writes a text message and their phone guesses the word they’re typing.
Machine Learning Promotes Collaboration
Machine learning promises to provide a helping hand to subject matter experts, helping them solve problems without spending additional time mastering specific software applications.
Using this technology fosters innovation by making data more accessible to a larger number of end users. Machine learning coupled with identity access management promotes work transformation, creating agile environments where teams collaborate in more intuitive, seamless ways.
As work transformation evolves, it will undoubtedly be a major factor in improving efficiencies and unleashing creativity in future workforces.
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