ServiceNow is bringing enhanced machine-learning capabilities to its Now Platform for business process automation to help customers prevent outages, automatically route service requests, and predict and benchmark IT performance.
The AI capabilities will be offered through the upcoming Intelligent Automation Engine, announced at the company’s Knowledge conference in Orlando Tuesday. The move strengthens ServiceNow’s base in IT management while making further inroads into other areas of the enterprise.
The machine-learning capabilities will be brought into ServiceNow’s cloud services for security, customer service, and HR. The Intelligent Automation Engine’s algorithms are based on technology the company acquired through its purchase of DxContinuum in January.
One of a select group of native cloud vendors to hit the billion dollar revenue mark, ServiceNow has over the past 12 years made a name for itself in IT services management, and more recently has been bolstering its offerings for other areas of the enterprise.
“Customer service and HR are areas that are ripe for automation,” outside the IT department, noted Allan Leinwand, ServiceNow’s CTO. “Businesses spend a lot of time on basic, mundane tasks like referring PTO (paid time off) requests to HR.”
ServiceNow’s new machine-learning capabilities center around the following areas:
–Outage prevention: Through anomaly detection techniques, the Intelligent Automation Engine identifies patterns and outlier instances that are likely to lead to an outage.The feature will be added to the third quarter release of ServiceNow’s platform, code-named Jakarta.
–Work categorization and routing: Based on past patterns, the Intelligent Automation Engine can categorize tasks, route them, and predict outcomes. The predictive intelligence capability will be brought into the company’s IT Service Managment offering first, and be incorporated into the fourth-quarter release of the Now Platform, code-named Kingston.
–Performance predictions: New algorithms will work with ServiceNow’s real-time Performance Analytics applications to help companies determine when they will reach performance goals, such as response time to help desk calls. This feature will be released in the fourth quarter.
In addition to the new features coming later this year, ServiceNow said it has already made the ability to evaluate performance against peers available in its Benchmarks application. This ability uses machine-learning techniques but is not based on the DxContinuum technology.
For benchmarking, ServiceNow uses data that its customers have agreed to share with other users of the the company’s products, on an anonymized basis, Leinwand said.
Deployment of ServiceNow applications can take four to six months for large installations at Fortune 1000 companies, and days or weeks at smaller companies, Leinwand added. Depending on the deployment, pricing can be based on number of administrators using the system or devices detected by the the system.
In addition to DxContinuum, ServiceNow has acquired other companies over the past year, including IT security firm BrightPoint Security as well as cloud-management company ITapp.
“If we go out and buy another company, the first thing we do is rewrite that product so it sits on the platform. This isn’t now and is never going to be a mismatch of multiple products and multiple companies tied together with replication and on loose integrations,” ServiceNow Chief Strategy Officer Dave Wright said in an interview last year. “This is a single system of record sitting on a single platform and that is the biggest differentiation we have.”
The company appears to be positioning itself to stay at the forefront of a burgeoning field. Corporate leaders feel under pressure to expand business-process automation as workloads increase and the volume of data sucked up by cloud apps grows.
In a survey commissioned by ServiceNow and unveiled at the Knowledge conference, almost half (46 percent) of the 1,850 respondents said they will need greater automation to deal with the volume of tasks being generated in their companies. Eighty-six percent of the respondents said they would need to increase automation by 2020.
Seventy-eight percent of the respondents said that data from mobile devices and IoT contributes work overload. The survey was conducted by Lawless Research in Australia, France, Germany, Mexico, Singapore, the U.S. and the U.K.