Cognitive Computing Energizes the Enterprise

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This is in line with research from an Aberdeen Group study commissioned by Inbenta, which found that companies incorporating cognitive technologies to support customer service interactions have seen an 81 percent improvement in employee engagement rates.

“There’s been a lot of conversation about virtual agents and artificial intelligence eliminating jobs, but what we actually saw is like any other tool: It’s going to be valuable in improving [agents’] performance and their interest and satisfaction while working,” says John Forrester, Inbenta’s chief marketing officer. “Instead of dealing with repetitive, boring questions that customers might have, they’d be dealing with something that’s more in-depth and engaging.”

While customer service jobs tend to have higher turnover rates than other fields, technology can help businesses with retention, as employees are likely to be more enthusiastic and eager to learn new skills and tackle greater challenges.


Behind the scenes, cognitive automation can be useful as well. Robotic process automation (RPA) can learn routine tasks that service agents repeat throughout the day.

“Robotic process automation has been around for about 15 or 20 years, but it’s primarily been rules-based, where somebody programs the rules for the agent,” Schubmehl says. “Now we’re getting to the point where you can have AI sitting there, watching the person doing the work, and then essentially developing the script automatically that the robot should act according to.”

That’s a relatively new area, but a hot one. Technology vendors like Pegasystems, WorkFusion, NICE, Automation Anywhere, and BluePrism are all adding RPA capabilities to their tool sets. “I think we’ll see that happen more frequently in 2017 and probably 2018,” Schubmehl predicts.

And while the call center might be the most obvious area and the one that most companies will want to look at first, sales professionals can also benefit from tools that simplify otherwise tedious processes, thus freeing them to tend to other parts of their jobs. Schubmehl points to Conversica as one vendor leveraging AI to simulate human voices and carry out conversations in place of sales reps, keeping leads warm so that when they turn hot again, they can be routed to a live salesperson.

In marketing, AI technologies can be used to learn customer preferences and identify the offers, images, and deals that are most likely to appeal to customers and to identify whether they should be sent via email or other channels and devices.


Goetz recommends getting started by testing and creating proofs of concepts. She says that companies in retail, consumer packaged goods, or manufacturing have a number of consumable applications from which to choose. A pilot can cost $50,000 to $100,000; implementation could range from $500,000 to $1 million, she says, but the proof of concept has already been given in many cases, leading to return on investment as high as 20 percent or 25 percent.

“Many organizations right now are doing piloting and testing and really working out to see the feasibility, and that entry point tends to be very low,” Goetz says.

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