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?
For Matthew Tate, who oversees Allstate’s AI Technology Strategy, he was initially concerned that employees would balk at the notion of using a technology that might threaten their standing at the company. Allstate deployed IPsoft’s digital colleague Amelia to help agents during phone calls with customers. Allstate agents type questions to Amelia, who provides account and product information, which agents can feed back to the customers.
“You could imagine that we’re introducing this Artificial Intelligence to users who are call-takers, and they’re first reaction is ‘She’s going to take my job,’” Tate said. “So we spent a lot of time with change management, and they very quickly realized that Amelia was a partner and an asset that they could adopt because she helped every day make their job easier.”
For Jon Eisenstein, Chief Information Office 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.
“What I would say about that group of [resistant] people is the faster you can find a way to get rid of them, the better you are,” said Eisenstein. “I know that may sound controversial, especially to some of our European colleagues, but really, [they] end up being an organizational bottleneck, a boat anchor, a cancer, whatever you want to call them. They don’t end up doing good things for the overall progress of the program.”
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.
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 spend a lot of time thinking about all the possible technologies that could possibly be better tomorrow, but if you don’t start today, you’re rapidly losing what you could learn.
— Matthew Tate, Allstate
“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.
“When we were first on this journey three years ago, we wanted to spend a lot of time planning and thinking about where we were going to go with this technology,” said Tate. “We knew it was something that we felt like was disruptive and that we should start doing. You know, you can spend a lot of time thinking about all the possible technologies that could possibly be better tomorrow, but if you don’t start today, you’re rapidly losing what you could learn, and the idea of reskilling those employees. If you never start, you never know what skills they’re really going to need. So you’re doing a disservice to your organization by waiting.”
“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, 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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