There have always been new technologies with the potential to change the way we work, but AI’s ability to upend business habits seems more radical.
Unsurprisingly, some organizations reacted by pretending the technology didn’t exist. of Northwestern Liz Gerber he has also seen the other end.
“I hear, ‘everyone does it. If we don’t, we will be left behind.’ And that kind of anxious thinking doesn’t allow people to really think about what the business case is,” said Gerber, a professor of mechanical engineering and communication studies at Northwestern.
Gerber, who has researched and consulted on innovation for years, says a better approach to how to integrate AI into an organization is already familiar to most leaders: the product development process.
He talked about it at a recent The Insightful Leader Live event together Hatim Rahmanassociate professor of Management and Organizations at Kellogg. The two shared tips for navigating the more difficult parts of the product development process for AI tools in particular.
Here are some highlights from their discussion.
“What is your ultimate goal?”
Why should the artificial intelligence product exist in the world? What gap does it fill, either for potential customers or within your company?
A comprehensive answer will save you trouble, says Rahman, who offers the example of adopting large language models without sufficient foresight.
“We’ve known for a long time that we have too many emails and too much information. And so we just say, ‘we can use [AI] to create more content, more information,” maybe that makes sense. But for many organizations, you really need less email generation and less overall information,” says Rahman.
Instead, Rahman gave an example of a hospital system developing an AI-powered ultrasound scanner to improve pregnancy outcomes, especially in countries with sparse access to clinical care. The AI model was originally designed so that anyone using a portable ultrasound scanner could scan the fetus and learn relevant information such as the due date.
From a product development perspective, the need for the device was pretty clear: to help pregnant patients with limited resources decide whether the extra care was worth the cost.
“How does this fit into existing processes?”
Gerber and Rahman recommend that companies consider not only the end goal of an AI tool, but also how it will be adopted into people’s workflow. After all, AI usually works best alongside humans.
“What are the jobs people need to do, want to do, and are good at?” Gerber asks. “Slowing down and developing cognitive models of what people are doing is critical, as opposed to assuming AI will take over.”
This question is even more critical because not everyone will be excited about the addition of artificial intelligence. Gerber gave another example from a hospital setting: a hypothetical AI tool that would help hospitals handle the spread of infection. The tool would need data to work, specifically data about who had interacted with whom. But not everyone who works in a hospital will necessarily want to be monitored. They may feel scrutinizing and mistrustful.
In other cases, people may be eager enough to adopt a new tool — but doing so can disrupt their workflow in hard-to-predict ways. In the case of the AI ultrasound detector, for example, the hospital system soon realized that standard procedures—like a nurse stopping to show the patient if the baby was doing something interesting—would really interfere with data collection. In order to get usable data from the scans, they will need to retrain their staff on how to use the ultrasound probe.
In other words, companies would be wise to remember that any potential AI tool will exist in a complex ecosystem of complex human beings, habits, and processes—and plan accordingly.
“What will you do when things go wrong?”
Speaking of planning: the researchers also discussed the importance of developing a plan for how organizations would react when (not if) the new technology launch failed.
Gerber shared an anecdote from a company that often developed new software. “When they developed the software,” he explained, “they gave everybody a punching bag. Like, literally a punching bag to put on their desk. … They’re already assuming that people are going to be frustrated with it … and they want to have a close feedback loop with those people so they can fix it as soon as possible.”
You can learn more by watching the rest of Gerber and Rahman’s webinar here.
