Great-Grandparents

Today, if you asked someone what their great-grandparents did for a living, the odds were better than even they'd say "farmer" and be right.

In the early 1900’s, forty-one percent of the American workforce was employed in agriculture.

Today, less than 2% of the labor force is employed in agriculture.

That's what a century of structural change looks like when you summarize it into two percentages.

Innovation and mechanization of food production has dramatically increased. Although there have been plenty of downsides to this innovation (food industrialization may be a big contributor to obesity and other diseases) the output metrics are clear:

• In 1901, Americans spent on average 42.5% of household budgets on food versus 10.4% today.

• In 1940, one farmer fed 19 people versus 155 people today with less land, energy and water.

Over the roughly one hundred year time span, innovation has allowed us to produce more food at lower costs with less inputs of labor and other resources.

One question you might be asking is, “What happened to the farming jobs?”

Most assume they simply disappeared but that is an incomplete understanding of how innovation impacts businesses and labor markets.

Every innovation does two things at once. It grows the total value in a system, meaning the pie expands, often dramatically. And it redistributes that value across the system. The slices get cut differently, and almost never in the same proportions as before.

The question is especially relevant now considering how AI is poised to unleash innovations across the entire economy.

If you want to know what AI is going to do to your business or your career, look at what the last hundred years of innovation did to food.

Food

Everyone is trying to predict how AI will reshape industries. What happened to food over the past hundred years gives us a clue of how innovations transform industries.

The transformation occurs in three distinct acts.

Act 1: Production Got Solved

Pre-agrarian societies had to search and hunt for food they ate on the spot. Post agricultural revolution societies committed much less labor toward producing food and mostly people ate what was produced near them.

Agriculture was forty-one percent of the workforce in 1900 and roughly 1.2% today. Mechanization, fertilizer, genetics, and logistics removed forty points of the workforce from food production, and we produce more food than ever.

Act 2: Distribution Absorbed The Displaced Labor

The jobs didn't vanish. With production “solved”, they moved downstream into trucking, wholesalers, supermarkets and other industries. Now, not only did people not have to work to grow their food, they could increasingly eat food produced far from home. Distribution of food became the big business.

Walmart became the largest private employer in America as logistics and the internet boom commoditized distribution.

Food went from scarce to abundant to everywhere thanks to better production and improved distribution.

Act 3: The Relational Layer Absorbed The Value 

With production and distribution solved, the relational layer began absorbing the value.

The restaurant and foodservice industry now employs 15.7 million people, approximately 10% of the entire US workforce. That's five times the number of people who grow the food.

A cup of coffee costs fifteen cents to make but a café charges six dollars for it.

We didn't just move labor from production to distribution. We moved value from the commodity itself to the human element around it. The barista, the ambiance, the specific café on the specific corner. As production got cheap, demand migrated toward the layers where a person's presence and the customer’s experience was part of the product.

Who doesn’t love hearing, “Have a blessed day” upon receiving your chicken sandwich at Chick-fil-A?

The three acts don't happen distinctly or sequentially. They exist simultaneously, and what evolves is how value gets distributed across all three as the pie grows.

AI is about to grow the pie again. The value across production, distribution, and the relational layer will redistribute. Is your business positioned for where it's heading?

Relational Layers

If value is moving toward the relational layer, where does that exist in your work?

Where does a human being have to show up and matter? Not just execute, but notice, decide, remember, and respond to a specific person in a specific moment.

Be honest. Some parts of your work feel “human” simply because they always have been. That doesn’t mean they should be. AI will flatten anything that doesn’t truly require judgment, context, or presence.

Also ask, where are the places where human involvement could be valuable but is currently too expensive or too time-constrained to deliver consistently?

That’s where the puck is going.

One reason AI seems scary is that it is much easier to identify jobs innovations will make obsolete versus jobs it will create.

Barista is just an Italian word for bartender. It wasn’t specifically associated with coffee culture until the rise of Starbucks.

Relational Value Factors

"Relational" is too vague to be useful on its own. It's a cluster of different things, and different businesses win on different combinations.

Here's a partial taxonomy:

Personalization — it fits this customer, not the average one

Judgment — the product is decision making, not just execution

Trust — the value is tied to who is standing behind it

Presence — someone is actually there, in real time, paying attention

Memory — the relationship compounds over time

Taste — a point of view shapes the outcome

Care — emotional attentiveness that notices, asks, follows up

Provenance — this was made here, by them, for this reason, and that fact matters

Most products and services are a mix of anyone of these or more. There clearer you are on which ones you actually deliver, the easier it is to see where to focus your efforts.

Use AI To Enhance The Relational Layer

AI won’t eliminate the human relational layer, it will only redistribute it.

Every product or service is delivered by jobs and tasks that are either a commodity or relational. The commodity layer of your own work is exactly what AI is good at now.

The commodity layer is the repeatable, structured, first-pass effort such as research, formatting, scheduling, reconciliation, drafting to name a few.

If you offload even part of that layer, you don’t just save time, you create capacity. Capacity to think more carefully, respond more personally, and bring more relational value into your products and services.

The winners won’t be defined by how fast they adopt AI. They’ll be defined by what they do with the resources it liberates to focus on the relational layer.

Tractors didn't stop farming. Tractors increased food production, allowing resources to be applied up the value chain to distribution and relational aspects of food.

AI will do the same across many industries.

The Next Step

What happened to the food industry over one hundred years could occur much faster in other industries due to AI.

You don’t need to predict every change. Just get aligned with the direction.

The next steps are clear:

• Audit your value stack - Where is your work a commodity, and where is it truly relational?

• Find the edge of willingness to pay - Where would customers value more human involvement than they’re currently getting?

• Reclaim your resources - Pick one repeatable task this week and use AI to solve it. Reinvest the time saved.

Your product, service or labor won’t lose relevance, but you need to shift your focus to the layer where relevance compounds.

If you want to explore these concepts further, this issue was inspired by the excellent article, What Will Be Scarce? from University of Chicago Professor, Alex Imas.

My goal with The Leap is to provide you each Saturday with the knowledge, tools and lessons learned to help you get started and keep going toward building your future. 

Whether you are making the leap to startups, solo-entrepreneurship, freelancing, side hustles or other creative ventures, the tools and strategies to succeed in each are similar.