If you tuned in to the left side of the radio dial around Thanksgiving or Christmas, you might have heard a lot of people sharing their favorite recipes. They talked about cups and tablespoons, sage and thyme (and cooking time). They also talked about memories of cooking next to grandma or the feeling they felt when they first tasted their own apple pie. These people were excited to share.
There’s a reason that one of the best-selling cookbooks of the past 75 years is called The Joy of Cooking—the process itself can be a pleasure, and you really can’t get better at it without doing it. That’s a lot like people’s increasing experience with AI: it may be intimidating, but the results are often delightful.
So, what do Americans think about “Cooking” with AI?
Ipsos AI Monitor (2024) reports that 52% of Americans agreed that products and services using AI make them nervous, while 54% said they make them excited. Ipsos Consumer Tracker (2024) shows that nearly half of Americans report cooking dinner more at home due to economic pressures, while cutting back on dining out. There’s an overlap here: doing your own cooking that builds on knowledge from others can help you make wise use of resources. I think of my cousin who runs a nonprofit organization in St. Louis, and his team’s first-line AI prompts for client service all came from team members themselves. They got a recipe that worked for them, and they shared it.
Still, executing a recipe is a process and requires some vulnerability; our local station has a show called Turkey Confidential that lets you hide your confusion. No matter the level of confidence, holiday cooking makes us want to do our best, work calmly as a team (I’ve told my sons that doing the dishes makes the next meal more delicious), and make sure that everyone feels heard by getting something they like at the table.
In process or workflow reengineering, as with cooking, you can’t talk forever—eventually, you have to get the food in the oven and taste the outcome.
We talked recently about a phased AI operating plan for 2026. How about a phased AI discussion plan? Let’s take a page from MOM’s hackathon approach:
Get a ledger pad or digital process mapping tool like Miro, or even a Google spreadsheet:
- What’s common family knowledge? What’s a recipe one person knows?
- Is that personal secret already written down? If not, get it all out (not the 5-step version—the 50-step version). Ask clarifying questions.
- Think about how to translate individual wisdom to clear and useful tools that will benefit everyone.
- Start building and learning together.
Knowing who you want to please or what you want to make easier is as important to successful AI implementation as knowing your family’s favorite recipes is to a successful meal. Breaking down the way you work naturally into teachable chunks lets you decide how to improve the process and keep the experience positive for everyone.
