Educating workplaces about AI will lead to better outcomes, say business leaders

One of the biggest hurdles to adopting AI is demystifying the technology and shifting its narrative to being a learnable tool. “This is well within your reach,” said Matt Baker, the senior vice president of AI enablement at Dell Technologies. “And that big ecosystem is something that is approachable today.”

Baker described AI’s “embarrassment of riches.” The market has exploded with new AI systems in the past year that tackle many different processes from task management to generative writing with competence. But with almost limitless applications, refining the use cases of AI will be the key to guiding its future in the workplace.

“We are so early in this phase of this really tremendous new technology that it’s important to keep an open mind and also to just see what works and what doesn’t work,” said Dr. Mozziyar Etemadi, the medical director of advanced technologies at Northwestern Medicine. “The last thing we want is for this to create just another big vendor lock-in piece of software that everyone has to use and nobody likes using.”

Baker and Etemadi were joined by Peter Miscovich, the global consulting practice lead, future of work for JLL. Miscovich said the biggest hurdle in AI adoption is figuring out exactly how to use the tech. “The need for training and change management and education could not be greater. I think I use generative AI every day, and it’s taken me a year to become comfortable with that intervention and interface,” he said.

At Dell, Baker’s team has made education a core aspect of their AI adoption. “We have an entire educational pillar of what we’re doing to ensure that we move our team members through that process so that they understand the technology,” he said. “It’s going to lead to better outcomes for them and ultimately and more importantly, better outcomes for our customers.”

The panel also warned against a timid approach to AI. Demystifying the technology requires fully embracing AI’s capabilities. For Dr. Mozziyar, that comes down to the design of the AI itself. “People should design the AI to kind of interact as close as you would interact with a person in a similar role,” he said.

Baker added that building new systems around AI, rather than plugging AI into existing workflows, is crucial: “If it’s a garbage process to begin with, you get a garbage outcome.”

There should be intentionality behind these systems as well, Baker continued. “There’s a framework for thinking through how you develop your own approach to that so that it’s tailored to your company, your business, your organization,” he said.

“We’re very strong believers in use-case diagnostics,” said Miscovich of his team’s approach to configuring better ways to use AI. He explained that they first evaluate “how current processes are organized” before figuring out how generative AI can help make those processes “much more efficient and much more effective.”

JLL recently launched multiple AI initiatives, including an HVAC energy-optimization platform to help reduce energy and service costs, and JLL GPT, a generative AI project built for the commercial-real-estate industry.

For Dr. Mozziyar, AI’s greatest potential in the medical field is its ability to assess patients’ conditions. His team is currently using AI tools that can analyze texts of patient appointments to find issues to follow up on. They’re also using an in-house AI assistant that helps radiologists catch critical issues.

“We want the interaction with AI, or the use of AI, to paradoxically remove the barriers between, in our case physician and the computer,” said Dr. Mozziyar. “Ideally it’s just you and the patient.”

But as the AI landscape accelerates and more companies begin adoption, Baker said that those who get on board now will reap the greatest rewards. “Run your own race, understand how it best applies, but understand it is a race,” he said. “So get started.”