(Originally published on Forbes)
Artificial intelligence, the technology buzzword du jour, is widely understood to have major implications for a broad range of business processes—most notably the people-centered activity of human capital management.
Too often, the management of people—whether at the HR level or manager level—suffers from overly bureaucratic processes. Managers have too many direct reports, in addition to having to do their “day jobs,” while HR pros must deal with regulatory and other compliance issues that pull them away from being more personal in their work. AI promises to help those pros automate their myriad mundane management tasks, freeing them to do a better job of relating to employees as people.
“The more AI augments our processes and extends our reach, the more we can apply the uniquely human capabilities that we bring to a situation—our judgment, our creativity, our empathy,” said Gretchen Alarcon, group vice president for Oracle’s HCM strategy, during a session at Oracle OpenWorld 2017. “In fact, I think the more we embrace AI and HCM, the more human we're going to become.”
The latest release of Oracle HCM Cloud includes several AI-based features. For example, the application lets job seekers interact with so-called chatbots to learn more about open positions and the employer’s recruiting process, or to get suggestions on other job opportunities. Another feature offers hiring managers recommendations for best-fit candidates. Another gives recruiters predictions on whether a candidate will accept a job offer.
Alarcon outlined a number of other scenarios in which artificial or adaptive intelligence eventually could help managers develop better connections with their employees, on both a professional and “human” level.
Possible future Oracle HCM Cloud capabilities now in the research stage include a chatbot that helps identify appropriate candidates for internal promotion; the use of natural language processing to turn text/screen-based performance reviews into more interactive exercises; and even the use of facial recognition software as an advanced management tool (more on that below).
In a video demonstration of the chatbot that helps identify people for promotion, it alerted a manager that the organization needed a leader for a specific project. After searching internal candidates, the system identified three potential fits, one of whom needed training. The manager approved the candidate, and the system sent a message to the woman offering her a promotion and asking her to complete an application to attend a training course. The system also asked the manager if it could send an updated project summary to the relevant team.
“The new productive is thinking about how to do things smarter, to have more targeted approaches and less wasted activity,” Alarcon said. “We're not talking about machines taking over the world. We're talking about how can we train processes to be more human-like, and consider more than just the binary decision tree.”
Improving the Performance Review
Performance reviews are a necessary part of most managers’ lives, but for many of them, it’s either a “creative writing exercise” or an exercise in cloning, “because you spend a lot of effort writing that first one, and you don't have any more time to write the other seven,” Alarcon said.
The process could be vastly improved with the use of natural language processing and the ability to have various types of data about the employee in one place. Natural language processing already exists in the publishing world, whereby AI-powered systems write basic news and sports stories.
The same technology could be applied to a performance review, Alarcon said, taking data from various sources and assembling it for a manager to review. The system could, for example, review data on an employee’s work and include a suggestion to give him more flex time because his child just started elementary school. Or it could recommend a new project based on his volunteering activities.
“We've talked for years about the value of having all this content together, and the ability to bring it together in one place,” Alarcon said. “If natural language processing programs could write the performance review, and give me suggestions about the employee as well, I could save a lot of time and go into the conversation much more prepared.”
When people think about the concept of a connected workforce, they envision being able to access the same information and communicate easily in real time. But what if we could access an employee’s mood as well?
Facial recognition technology could eventually do that, alerting an employee’s manager about an unsuccessful meeting or the perceived level of engagement he or she has on a project. Such a tool may seem “far out there,” Alarcon said, but customers have already asked about how to gauge the effectiveness or success of meetings. “It's not crazy town,” she said. “We are actually thinking about this right now.”
Another futuristic concept is location-based intelligence. Alarcon offered the example of a system that alerts a manager if an employee’s flight was delayed and asks if another employee should be assigned for his 9:00 a.m. meeting.
A History of Intelligence
Oracle’s HCM applications have long had automated, data-driven capabilities that could be viewed as “intelligent,” Alarcon noted. For example, the workforce predictions feature goes back to the first release of Oracle’s HCM suite. She called it “an early warning system that told you what could happen with your workforce, or the success rate of a reorganization, and left the decision to you.”
Since the application suite was first introduced, it has also been making recommendations on employees’ career development and potential mentors. Employees get suggestions about how to advance in their chosen track, or what jobs might be suitable in the future.
“Some of this may sound far out, but the data’s all there,” Alarcon said. “We just have to find a [better] way to bring it all together in such a way that you can actually interact with it.”
Although most company leaders see AI as “interesting and cool,” Alarcon said, they’re not sure if they’re ready for it yet.
“We're in the same situation with AI that we were with the cloud five years ago—we’re ready to explore it and we know it could be big, but we’re not sure how it will impact us,” she said. “It wasn’t a question of if you would move to the cloud, but when, and I think we're at that same point with adaptive intelligence.”