Discovery Education's chief product officer says AI can free up employees to focus on complex tasks — but warns against being 'a hammer looking for a nail'

• Pete Weir, the chief product officer at Discovery Education, says AI can make mundane tasks easier.
• He says policies and guardrails can help empower employees exploring AI tools.
• This Q&A is part of the "CXO AI Playbook" series — straight talk from business leaders on how they're testing and using AI.

Discovery Education is a midsize learning-technology company with products designed to support teachers and students in kindergarten through 12th grade.

As the launch of ChatGPT supercharged conversations about innovation, the company created a policy for testing and using artificial intelligence. It's designed to help employees understand the limits of what they can do and what the company leaders' expectations are for them to learn and adopt new technology.

"Our employees are looking for guardrails," said Pete Weir, Discovery Education's chief product officer. "Our employees want to understand: Is the expectation that I'm using every single technology that's coming out there because I need to stay at the forefront of it?"

Business Insider spoke with Weir about the company's use of generative AI to minimize mundane tasks and improve productivity, as well as guardrails to help employees explore and innovate without taking on AI projects beyond the company's scope.

The following Q&A with Weir has been edited for clarity.

What do you do at Discovery Education, and when did you start exploring the use of AI at the company?

My job is to bring all the parts of product development together, to make sure we're building solutions that work for teachers and kids across content, curriculum, and design.

We started looking closely at large language models nine to 12 months before ChatGPT came out and were stunned when we saw how good it had become.

How did you identify ways to deploy generative-AI applications at Discovery Education?

Certainly we have machine learning and AI as part of our products. But we started asking ourselves what are tasks that happen over and over again where we are constrained from doing things quickly?

One of the challenges has always been how to know that we're working on the right things in the right context. We have millions of kids and teachers using our products, and we get open-text feedback from all kinds of sources.

AI helps us build all that feedback into themes a lot faster, instead of going through reams of Excel files and trying to relate different datasets to each other.

That's one of the most tangible opportunities we see — taking those bridging tasks that eat up our team's time and focusing them more on bringing solutions to problems our teachers and kids have.

Is it easier to think of ways to use AI, since you're already steeped in technology?

The pace of change in this space is faster than anything I've seen in my career. It's really about understanding where you want to place your bets. It feels sometimes like you could work on something for six weeks and then it's obsolete because there's a new way of doing things that's come out.

One of the most important mantras we have is "don't be a hammer looking for a nail." What's a problem that we've always wanted to solve that a large language model can now make better?

That's a question we have to keep asking ourselves, because as technologists it's very easy to get drawn into how compelling the technology is. It's harder to take a step back and say why is the use of AI or the application of it in this specific area compelling as a solution?

We don't need to reinvent. Zoom came out with a feature where it can record a video and provide a summary — so we as a company probably shouldn't be trying to work on our own proprietary version of transcribing videos after a Zoom.

It's not great to get too far ahead of the curve, because it might be a problem that people with far more resources are going to solve on your behalf.

How have you organized your teams to foster and manage AI innovation?

For the executive team here at Discovery Education, our responsibility is to know where and how we're applying the technology.

It's been like a hub-and-spoke model for us — decentralize it to some extent, with some guardrails, and then have someone who's kind of in the know at all the places we're trying it.

An important aspect for us was having an AI policy, making sure that our internal employees knew what is appropriate use. In a very short period, anybody could do a lot of different things and send data to a lot of places. One thing I would encourage people to do is to make sure that where you're sending data is protected.

If I think about what steps we've taken, that policy and discussion across the different functions and executive functions were important. For someone who works very closely with an engineering team, we probably have a bias to understand these things. You take it for granted the exposure you have in product development and engineering.

So one of the most important things was a big zoom-out on how this is going to affect all of us. It is going to affect our customers? How do we think about it as a whole, from HR to recruiting, and how do we apply the technology there?

What advice do you have for a company that's just getting started on its own AI journey?

I think it's important not to focus too much on your actual products and services but on all the ancillary benefits you can have, and talk about those cross-functionally.

That was one of the smartest things we did very early on. You can encourage someone who may not have thought of a generative-AI application as benefiting them or similarly didn't see a risk that others see.

I think that dialogue has been constant for us, where we continue to talk about how we're applying it and what are the ethical uses of it, particularly in our industry, and then codifying that in a policy.

As bureaucratic as that sounds, what we found is our employees are looking for guardrails. Our employees want to understand: Is the expectation that I'm using every single technology that's coming out there because I need to stay at the forefront of it? Where are we on that risk curve, and what do you expect from me as an employee?

Another thing for us was to explain to our employees how we frame the use of this technology. In our industry, it's not meant to replace the teacher — it's meant to augment the teacher. If we're doing this well, it's seamless and people don't feel like AI is a verb. It's something that's just making you more efficient or better at what our purpose is, which is to help educate kids.

We're a company, not a business unit, when we think about this. We're in it together, and we have to have an open dialogue about the evolving use and benefit of the technology. It's a conversation.