A recent HBR article stressed that, in order to reap the benefits of artificial intelligence (AI), organizations must be mindful of how they introduce the technology to those who will be working most closely with it. According to the authors, “Accenture has found that when companies make it clear that they are using AI to help people rather than replace them, they significantly outperform companies that don’t set that objective (or are unclear about their AI goals) along most dimensions of managerial productivity—notably speed, scalability, and effectiveness of decision-making.”

To set AI up for success, they believe companies should follow a four-phased approach to implementing the technology.

Phase 1: The Assistant

The first phase is very similar to onboarding a new human assistant. After the new hire has been taught a few fundamental rules and procedures, he is capable of assuming basic but time-consuming tasks (i.e., filing online forms or summarizing documents), enabling the trainer to focus on other more strategic aspects of the job. Positioning the technology in this light can help assuage the perennial “AI is robbing jobs!” fears, and also help human employees feel more in control of the technology. The authors write, “It should not be a stretch for managers to work with AI in this way. We already do so in our personal lives, when we allow the autocomplete function to prefill forms for us online.”

Phase 2: The Monitor

Setting up the system to provide real-time feedback is the second phase of implementation. As the HBR article puts it, “AI is very helpful during high-volume decision making, when humans may be tired.” Of course, the technology isn’t always accurate—something we’ve written about before here at the APEX of Innovation. The HBR piece elaborates, “Often its suggestions don’t take into account some reliable private information to which the human decision maker has access, so the AI might steer an employee off course rather than simply correct for behavioral biases.” The authors stress AI should be like a dialogue, in which any override is explained by an employee so that the system learns from human intelligence and experience. Not only does this improve the usefulness of the technology, it also gives employees autonomy.

Phase 3: The Coach

The challenges with providing performance feedback have been well documented, but this is a problem AI could address. The third phase involves deploying AI systems to identify key behaviors that impact performance and provide personalized feedback to help employees change these behaviors over time. Of course, such an implementation could easily play into people’s “man vs. machine” fears, and the HBR piece stresses that employees must be involved in the design and roll out to lessen the likelihood of such issues.

Phase 4: The Teammate

As the authors put it, “In the final phase of the AI implementation journey (which to our knowledge no organization has yet adopted), companies would develop a coupled network of humans and machines in which both contribute expertise.” They acknowledge that a number of challenges must be overcome in order for this phase to truly be a possibility, but stress that it is certainly something we will see as the technology matures.

For more on these phases and the considerations that accompany each step, check out the piece in its entirety here.