Proactive—even predictive—IT delivery is no longer a fantasy. Find out why AIOps is the key Sponsored by servicenow
That’s me, debugging assembler language and burning the compiled code into ROMs. Compiling the code alone seemed like it took forever, the process of burning the ROM and then testing took even longer. Yes, In those days, the idea that artificial intelligence would be able to have a conversation with a user or fix an issue without human help was solidly in the realm of science fiction.
At ServiceNow, machine learning and the intelligence in the Now Platform make it possible for an employee to submit an issue directly to a virtual agent where it can be resolved sans human engagement. This minimizes the number of issues coming from employees. AIOps also allows us to proactively—even predictively—identify issues so they can be fixed before employees know there was a problem. That is the epitome of proactive IT support.
It does this by correlating many different data points, such as persona, time, location, service, and application, to better understand the impact of an incident. For example, if finance complains that an ERP system is down, machine learning can automatically ensure this becomes a top priority. This approach is much more effective than depending on employee input about the impact, which can be subjective.
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