“Your judgment, that's your main job,” says Dan Chuparkoff, a technology executive with more than 30 years of experience across companies including Google, McKinsey, and Atlassian. “As you start bringing AI tools in, it's still your responsibility to make sure you're the one with the judgment.”

Chuparkoff, who led an engaging AI-focused keynote at The Vision Council Executive Summit in January, sat down with EB to dive deeper into how eyecare professionals can successfully implement AI tools in practice. Here, we share key takeaways from the conversation.

Step 1: Adoption

For many eyecare professionals, incorporating AI into workflows may seem like a daunting task. To alleviate the unease, Chuparkoff offers a simple suggestion: play.

“Some people are trying to wait for the green light from the world that says, ‘Oh, now here's how you [use AI].' But the world doesn't know what your job is and what you're trying to achieve,” he shares. “It's really important at first for organizations to create a little sandbox for people to play in, a way for people to start doing experiments so that your own employees can start thinking of ways that it can work to solve your problems. The sandbox to play in is the first step for adoption.”

Ask team members questions like:

• Which AI platforms have you tried already? What worked and what did not?

• What’s one business task that you’d be excited to try with an AI tool?

• Which individuals will spearhead AI’s incorporation into the practice?

Step 2: Implementation

After team members are comfortable with using AI tools, have a thoughtful conversation about where they can add value to the eyecare business.

Ask team members questions like:

• Which tasks or workflows are a priority for incorporating AI tools in the next 30 to 60 days?

• What business guidelines or best practices can be put into place to ensure proper usage?

• How can we properly document and share use cases across the team?

As Chuparkoff explains, AI outputs reflect average, widely available information—not nuanced expertise.

“It’s not the most creative or the most unique…it might not even be the best,” he says, describing AI as producing a “C-plus answer from the stuff we put on the internet.” This distinction is critical for eyecare pros (and health care professionals overall), whose work relies on precision and experience.

For this reason, AI can be implemented to assist with the tasks that may fall outside of an individual’s core expertise, such as admin workflows, assistance with patient email communication, or operational tasks, while remaining guided by a leader’s judgment.

Step 3: Checking Your Perception

Once AI tools are implemented in the practice, it is necessary to avoid treating them as fully autonomous systems while maintaining an ongoing refinement of associated processes.

An easy way to conceptualize this: Treat AI like an intern, not a copilot.

“I don't like the fact that Microsoft used ‘Copilot’ to name their AI because that's creating this picture where you are flying a plane and next to you there's a copilot that also can fly the plane,” Chuparkoff warns. “That's the wrong metaphor because AI is not a peer sitting next to you doing all the same work.”

Instead of a passive incorporation, consider holding weekly check-ins with team members to review AI-related “wins” and shortcomings. Conduct weekly and annual evaluations of AI use as you would for an employee.

Ask team members questions like:

• Are there any successful AI prompts you’d like to share?

• What tasks have you been able to complete faster using AI? Which tasks have taken longer when using it?

• What additional training or resources would help you use AI more effectively?

As Chuparkoff shares, “You're always the manager of your AI intern.”