Cognitive Computing Energizes the Enterprise

In many cases, all of this can happen behind the scenes, unseen by the customer. “The customer doesn’t necessarily know that this is happening,” Goetz points out. In many cases, too, the agent can train the machine, increasing the likelihood that the recommendations it makes are better and smarter over time.

Vince Jeffs, director of strategy and product marketing at Pegasystems, stresses the importance of the instant feedback loop in teaching intelligent assistants. There are plenty of cases where machines can’t quite solve these problems yet, he says, noting that some cases still have to be escalated to humans. “But they can be assisted by these machines, and the agents can guide the machine on whether or not its recommendations were good or not.”

WHAT CAN COMPANIES EXPECT?

While the buzz might signal something that is still quite a ways into the future, a reality in which many customer interactions are completed by machines is not that far off. Most companies—or at least those that don’t have astronomical budgets—shouldn’t expect a very high level of sophistication just yet. But there are many tools they can implement to save their employees time on routine tasks.

Customer support is a common area of investment, experts agree. A number of technologies can help “reduce the strain” on call centers as more people contact them for help and advice.

“If you can have an automated agent that is able to answer 50 percent to 60 percent of the questions in a timely way, provide good responses to customers, and doesn’t make them upset, that’s a win-win for everybody,” says Dave Schubmehl, a research director at IDC covering AI and cognitive systems.

Schubmehl points to Autodesk’s use of IBM Watson’s Conversation tool to develop a digital concierge as an example of a company that got it right. The agent, referred to as “Otto,” can handle 60 percent of web-based customer service inquiries. Autodesk improved support ticket resolution time by 99 percent and significantly upped customer satisfaction.

According to Schubmehl, to make it work, the company had to organize its knowledge base. The system was trained to handle common customer and partner issues, including resetting passwords or rebooting a program after it failed. More difficult cases that weren’t covered by the knowledge base could get handed off to a live agent.

“It is important we provide our customers with consistent quality paired with the shortest response and resolution time,” said Gregg Spratto, vice president of operations at Autodesk, in a statement. “Our collaboration with IBM Watson allows us to expand the Otto concierge service and deliver prompt, effective, and authentic engagement to our customers.”

Goetz mentions a similar case involving a company that sells insurance through employers and sees its heaviest traffic during open enrollment periods. In the past the firm had to train temporary staff members to handle those kinds of calls and answer questions about insurance types and policies. “The quality of customer service would significantly decrease, and it was inconsistent in terms of how customers were supported,” Goetz says. Furthermore, since they were contracted employees, the temporary agents were not as invested in their jobs as full-time employees. With IBM Watson, the company was able to move to first- and second-tier support levels when volumes peaked, pushing the more sophisticated cases to live agents.

Another major benefit of automation through intelligence is in reducing the “grunt work” and freeing people up to do more interesting work that requires more complex skill sets and critical thinking, according to Schubmehl. After all, it can get depressing just helping one customer after another recover passwords or log in to their accounts all day.