I hope you’re spending some time resting and recharging with family this week. At Section, we’ve wrapped up the last of our 2023 projects and end-of-year planning, so I’m taking some time to reflect on plans we’ve made for Q1.

If your company is all-in on AI like Section, you might’ve spent the last few weeks coming up with exciting AI projects to tackle in the new year. Brainstorming new AI projects with my team is some of the most fun, energizing work I get to do - but once we have our list of shiny new projects, the next step is less glamorous: figuring which ones we have the time (and budget) to actually execute. 

Today, I’m sharing the simple risk-reward framework that we use to prioritize AI projects. We’ll dive into:

• 2 angles to approach AI prioritization depending on your org’s comfort with AI
• The risk-reward framework for prioritizing AI projects
• How we did it at Section 
• What to learn next 

Ready to become an AI strategist in the new year? Join our AI Mini-MBA starting on Jan. 10. Use code AINEWYEAR for 20% off enrollment. 

2 angles for AI prioritization

Your organization’s comfort with AI will determine the projects you’ll be able to get greenlit. 

Whether your CEO is Slacking you over the holidays about a new AI tool he discovered (Merry Christmas, Greg!) or your leadership team is skittish about adopting a new technology, you’ll need to prioritize projects that are ambitious but doable. 

Start by thinking of AI projects in two buckets:

• Quick wins, or incremental improvements to your internal workflows or customer experience that require a lower investment 
• Big wins that align a core business goal with an AI project, so that the AI project adds substantial value for your business (but may require a higher level of investment)

If your company is just starting to use AI, you’ll want to prioritize projects in the quick wins category. When we started using AI at Section at the beginning of this year, we focused mostly on how AI could improve internal workflows, like brainstorming content ideas or generating simple first drafts.

Once AI becomes a part of your day-to-day, you can start to prioritize big wins that require more time and effort but make a larger impact on your business’ goals in the long run. 

Plot your ideas on the risk-reward framework

Now it’s time to go one level deeper in categorizing your ideas. Use this framework to plot your initiatives across two spectrums: high vs. low ROI, and slow vs. fast to measure impact.

Given how new AI is, we put a premium on ideas where you can assess results quickly. This isn’t the time for projects that take six months to get initial results. To get buy-in (and decide whether you have a one-time cool application or something worth embedding in your consistent workflows), you need to be able to measure initial outcomes or results quickly.

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If your company is still working on AI adoption, then your most executable ideas will likely end up in the lower risk/lower reward quadrant. These quick wins will be the low-hanging fruit that may not drive high-level business goals, but make small, incremental improvements elsewhere. They’re often about applying AI to internal processes, like using AI to summarize a dataset or training AI to generate V1 copy. 

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If you’ve already worked on some of your quick wins, you can start to focus on projects in the fast to measure/higher reward quadrant. These are the projects that may need more investment, and you should prioritize as soon as you have the bandwidth to do so. 

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How we did it at Section

Here’s how we did the exercise earlier this year at Section. We started by plotting all of our ideas (from different teams) on the matrix. Ideas to optimize internal workflows are in black, and ones to accelerate our product roadmap are in purple. 

We had 28 ideas and 25 team members - so the next step was cutting down the list to a number our small team could execute. 

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Anything that was slow to show impact got the chop. We’re a startup, and need to prioritize the projects that will add value, fast. We ended up with the 13 ideas on the right of the matrix. 

So far, this has been the right choice. We’ve seen huge productivity gains from optimizing internal processes, like using AI to create templatized emails or get feedback on our strategic decisions. 

Naturally though, my favorite projects are the heavy hitters in the high ROI/fast impact quadrant, like building a custom tutor bot for Section courses. 

Want to start 2024 by joining the AI class? Join our AI for Business Mini-MBA starting on Jan. 10. Use code AINEWYEAR for 20% off enrollment.