DWS 2018: AI Deployment Surprises and Strategy

By Juan Martinez, Senior Writer
June 22, 2018 • 3 minute read

Panelists from Fannie Mae, and PriceWaterhouseCoopers (PwC) discussed the initial challenges of implementing an AI system and the ways to get employees invested in new solutions. Read this article to learn more.

Deploying an AI system can be a complex process. Determining the technical, cultural and philosophical approaches to building out your AI initiative is crucial to any organization.

This was the theme discussed during the Digital Operations panel at The Digital Workforce Summit 2018. Led by Jonathan Crane, IPsoft’s Chief Commercial Officer, the discussion began with a question posed to the panelists: What surprising outcomes did you encounter during your AI deployment?

Jon Eisenstein, PwC

For Jon Eisenstein, Chief Information Officer of New Global Ventures for PwC, the positive reception to new technology was not unanimous. He said his employees were broken into three groups: those who were willing to experiment with new solutions, those who were hesitant, and those who were outright resistant.

He added that companies should find a way to empower the group that’s most eager to try new technologies. If the eager group is empowered, companies will quickly find that the hesitant group will get excited about the technology as well, he said.

“It's going to disrupt every industry. I mean, we were talking about a couple of industries, but you can come up with a dozen different ways that it's going to affect every industry." Eisenstein said. "That's not a bad thing. It just frees us up to be able to do high order tasks. So, it's really more of a matter of just getting started. Grab the reins and go. I mean, it's kind of like prototyping something. You're going to get it wrong at the beginning. That's okay. Fail fast, learn from it and move on, but the longer you wait cogitating about it, the more time you leave somebody else to do the disruption for you.”

The conversation then pivoted to the kinds of training that companies need to employ when starting an AI implementation. Eisenstein recommended starting off with a simple project, such as robotic process automation (RPA), to give employees a basic overview of how automation can improve business processes.

“You can start with something like an RPA tool, and you can say let's take a screen recording, and let's see what you're doing, and let's let the bot do it,” he said. “Then they start to get the basic concepts of what it's like to let robotic automation… start to take the reins of the most mundane activities.”

The panelists agreed this approach was superior to trying to architect an entire AI ecosystem from scratch and then thrusting it onto one’s workforce.

“Rather than trying to architect the entire thing beginning to end, step into it, prototype it, fail fast, and keep trying,” said Eisenstein. “And then when [your employees] are hitting their heads against the wall on something, be like okay, here's a way we can solve it with a level of orchestration.”

Dawn Damico, Fannie Mae

Dawn Damico, VP of Digital Workforce and Platform Solutions at Fannie Mae, was in full agreement.

“For employees, we're training them in Lean techniques [and] Agile, and we're using that to promote this culture and mindset of continuous improvement and end-to-end process management, and leveraging visual management,” Damico said. “For an operations person, deep subject matter expertise used to trump everything else, and it doesn't anymore. So now, we want employees who have a breadth of experience and who have that mindset of continuous improvement and who can see end-to-end.”

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