DWS 2018: AI Adoption Myths and Imperatives

4 minute read

Paul Daugherty, Chief Technology and Innovation Officer at Accenture, breaks down the myths and challenges associated with AI adoption for global businesses. Read this article to find out if your business is prepared for what Daugherty calls “The Age of Human Empowerment.”

IPsoft Digital Workforce Summit“We're entering an age that's about human empowerment,” said Paul Daugherty, Chief Technology and Innovation Officer at Accenture, during his keynote address at the Digital Workforce Summit 2018. Daugherty is the co-author of Human + Machine: Reimagining Work in the Age of AI, which focuses on the notion that as humans and AI collaborate closely, work processes will become more fluid and adaptive, enabling companies to change them, or reimagine them, on the fly. “It's an age where we're going to enhance humanity and our ability to deal with the way we work and live.”

Daugherty stressed that human empowerment won’t be achieved simply by automating labor. Instead, he said, humans must find a way to put “the machine and AI technology together with the human” to augment human capability. In order to accomplish this endeavor, several myths, imperatives, and challenges must be overcome, he said.

The Myths About AI

“The first myth is that the robots are coming for us,” he said. “We don't believe that's true, we don't believe we need to worry about that in the next few human generations…I think the concerns about this in the popular media, are really unfortunate and distracting a lot of people,” Daugherty said.

We feel very strongly about this topic at IPsoft. Our digital colleague Amelia is trained to perform according to a business’ strict processes, following all standards and policies in place. Although she can learn new processes over time through her interactions with human colleagues, Amelia is designed to make life and business better, not create a world where AI is “coming for us.”

Machines will automate a lot of current jobs, machines will make things more efficient, and we'll have a lot of job loss because of AI, but with that machines will create many new jobs.

— Paul Daugherty, Accenture

The second myth Daugherty addressed is the notion that machines will take most human jobs. “We simply don't believe this is true,” he said. “Machines will automate a lot of current jobs, machines will make things more efficient, and we'll have a lot of job loss because of AI, but with that machines will create many new jobs.”

IPsoft has addressed this concern in many of our blog posts and public presentations by our executives. Based on analyst research, AI is projected to increase labor productivity by up to 40%, starting with the customer service industry where 38% of businesses expect AI to provide massive improvements. More than just bottom-line value, AI will simplify how we interact with technology by providing more humanlike interfaces, interactions and services.

Daugherty said the real challenge won’t be finding new jobs to replace old jobs, it will be an issue of teaching workers new skills to fill the new positions. “In the US alone we have 6.5 million people unemployed right now. We have 6 million open jobs, almost enough [to fill the number of job openings], and that's already at a high employment level. We created 220,000 jobs in the job report this month. Last month in was 170,000. The month before, 240,000. We're creating plenty of jobs, the issue is getting the people that are impacted and unseated from their jobs skilled in the right way for the new jobs.”

IPsoft’s view is that AI platforms such as Amelia are going to serve as collaborative solutions to help make work more efficient and creative, as opposed to roles that are catered to handling rote processes. We believe humans and machines will work side-by-side to deliver faster outcomes backed by deep intelligence and historical perspective.

The final myth Daugherty addressed is the idea that companies will be able to tack AI onto existing platforms and strategies and conduct business as usual. “We believe that you need to fundamentally rethink how you apply technology to your business if you really want to get the value of AI,” he said.

The Imperatives of AI Adoption

To dispel the third myth, Daugherty said companies will need to re-imagine their business in order to align it with technology, and maximize output and return-on-investment. He said the focus should be on “creating dynamic, agile, adaptive business processes,” with roles that don’t “have a single job description” but offer “dynamic personalized” tasks “adapted to the individual worker.”

Daugherty said the labor force must be properly prepared to take on AI-based tasks. “If you're trying to take the people in jobs today and get them to do the work tomorrow, you're doing the wrong thing,” he said. “You need to think about the new approach to work and the new way jobs look.”

In his view there are two types of jobs for which companies need to prepare: trainers and explainers. Trainers will focus on designing and adapting the personality of virtual agents to represent the norms, behaviors and values of a company. Explainers will work to examine how machines perform and try to detail if the underlying algorithms performed as designed. “When the Uber car hit the pedestrian in Tempe [Ariz.], who figured out what happened and what needed to be changed?” he asked.

Ultimately, it’s a corporation’s responsibility for implementing responsible code around the application of AI. “You need to think about the accountability for the algorithms that you're developing because the companies that try to claim that something went wrong and it was AI's fault aren't going to do very well [in the public and the media],” he said. “A human at the end of the day is accountable for anything that happens in your organization. Understanding the accountability and how you design that in is critical.”

Organizations will need to be transparent in what they’re doing with AI, how the technology works, and what went wrong in the event of an accident. Daugherty recommends companies institute a “Chief AI Officer” to manage these issues and ensure transparency in all use cases.


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