The most important number in specialty crop AgTech is annual automation revenue, and the big target we are taking on is how we can get that number up to $5B in one year. I’ve written before on the importance of getting automation to become a category with over $1B in annual sales. That metric is a big one from a segment perspective because in many tech categories there is precedent for that level of revenue generating follow-on segments of significance. In the case of automation, the opportunities are: (1) systems integration (helping ag operators incorporate the robots into their farming operations); (2) data/analytics (taking the data from multiple robots and turning it into a recommendation engine for agronomic decision making on future rotations; and (3) manufacturing/service ecosystem (at a certain level it becomes it worth it for manufacturers to begin manufacturing equipment close to their customers, no matter where HQ is located). In the case of enterprise data centers, as various iterations of storage (NAS, SAN – basically any combination of storage (S) and networking (N) you can acronym) reached $1B, the supporting infrastructure around systems integration and data/analytics tools often got to be 25-50% as large as the underlying $1B category.

So then I started doing some analysis on what the projections for automation revenue could look like over the next 5-10 years and beyond. As I dug into the amounts of venture capital already invested, the amount and trajectory of current revenue from known players in the space, and the likely trends of VC and revenue going forward, two things became apparent. First, with just the known players and expected growth trajectory, AgTech automation is poised to go from ~$310-325M in 2025 to $1B in 2030. This is a 26% compound annual growth rate (CAGR), and the growth rate for the last couple of years has been at least 25-30% with some spike years. Second, if you look at the expected AgriFoodTech VC funding for the next 5 years and the expected percentage on automation, it is very likely that a clear path to $2.5 billion in the next 10 years is not just possible but approaching probable.

How does the $1B show up? Well, over the last 10 years there has been $2.8-$3.2B in automation investment, and that has generated the momentum to reach $1B in revenue by 2030. This will largely come from non-harvest automation, including weeding robots from Carbon Robotics (laser weeders) and Stout (mechanical weeders); spraying robots from GUSS, Ecorobotix, and Verdant; thinning robots from Niqo (and worth noting that some of the weeding robots can also thin – and vice versa over time), harvest assist (Burro), and autonomous mobility platforms (Bonsai/Farm-NG and Agtonomy). These players can get most of the growth to $1B without new entrants – any new entrants (and we do expect some) will accelerate the growth rate and bring the target data for $1B into play earlier. So that is the clear glide path to $1B category status in 5 years.

Now let’s look at the path to $2.5B. Even with AgriFoodTech venture capital dropping 70% in 4 years ($54B in 2021 to $16B in 2025), we are still at $16B for 2025 after $16-17B the past two years. For the moment, it’s fair to model the next 5 years of VC at $15B per year (in range lower than the last 3 years in case there is further reduction). This means we can expect the total AgriFoodTech VC number for the next 5 years to land around $75B. Then, let’s look at the automation percentage of that number to see where we should forecast the investment for the category. It should be no surprise that once the funding for vertical farming and alt-proteins largely stopped (they turned 42% of the $54B in 2021 into a dumpster fire and stopped getting checks – or at least got a lot fewer – as a result), the percentage that invested in categories solving real problems started to increase. Automation, which is solving the real problem of labor, went from 1.6% to 5.6%. If I had to bet, I would bet that the percentage invested in automation is more likely to go up than down in the next 5 years. For modeling purposes, I used a flat line allocation of 5.6% of the $75B. That gets to $4.2B over 5 years that is forecast to be spent on automation.

Now we can make some assumptions about the impact of that $4.2B based on what we have seen from other segments in the past. We know that capital efficiency increases for a segment when it moves from going from $0 to $1B to $1B to $2.5B. This makes sense. The first billion in revenue supports the build-out of infrastructure and the next billion (and beyond) are able to leverage the installed base and ecosystem built for getting the first billion created. Recall that the clear path to the first $1B in revenue was based on ~$3B in AgriFoodTech VC. Based on what we know about history, it’s easy to model the next $4.2B as more than capable of generating an incremental $1.4-$1.5B (if you just straight-line the $3B result to $1B, $4.2B would expect to generate $1.4B – I think there is upside because any new progress from automation startups from the first $3B will capture upside beyond the model. For these reasons, I believe that if the $4.2B in automation revenue provides a clear path to $2.5B in annual automation revenue.

Now that we have a clear path to $1B in revenue based on $3B in investment and an equally clear path emerging to $2.5B in revenue based on the next forecast of $4.2B in investment, the clear next question is what do we need to do to get to $5B in revenue. And a supporting question is what does that number enable in terms of new business opportunities, and, even more importantly, what does it mean in terms of job creation?

First, let’s look at the capital we need to get to $5B. Based on the fact that $3B in VC resulted in a clear path to $1B in annual revenue and $4.2B in VC should get us to $2.5B, it makes sense that less than $7.2B (the number modeled for the first $2.5B) in VC to get to the next $2.5B in revenue. But we have to be honest about the VC space, particularly in AgriFoodTech. While AI remains a high-flyer and solid performers in cybersecurity and fintech continue to emerge and get good outcomes, AgTech remains a long slog with limited exits, almost no IPOs, and very few M&A transactions. So the entire extent of VC for automation may be the $4.2B for the next 5 years we already have modeled in. For the rest of the exercise, I assumed we would need additional non-VC sources of capital to fund the additional $2.5B in activity.

So what are these new sources? I have been looking at both potential capital sources and programs for re-allocating spending from other programs to AgTech automation. I have found some programs that are using poor metrics and/or not measuring their success (or failure) very well. Three large areas of potential re-allocation that have been identified so far are climate-smart funding, regenerative ag practice payments, and federal economic development grants. I’ll dive into each in a future article. For now, I just want to summarize the high-level findings. I identified $23.8B in federal funding that are aimed at agricultural operations: (1) $19.5B in IRA (Inflation Reduction Act) climate-smart ag funding; (2) $3.1B in USDA Climate Smart Commodities; and (3) $700M USDA Regenerative Ag Pilot Program.

If we re-allocated 5% of that total to provide incentives for AgTech automation investment, we would have $1.1B in incentive payments. If you turn those incentives into an equipment repayment program similar to the EV tractor programs FARMER and CORE (which are run by CARB – the California Air Resources Board) and provide 40% public funding payments to support the 60% made the private funders (the growers buying the equipment), you get an additional $2.9B in additional automation revenue (which is comfortably over the $2.5B needed to reach $5B). We already have equipment support purchase programs for agriculture and other industries. We can re-use that infrastructure to accelerate faster towards the $5B target. We do not need VC funding – equipment funding can help reach the same goal.

And now we get to the point of the exercise – what does it mean when we get to $5B in automation revenue for specialty crop AgTech? I have been digging into this from a few viewpoints. The short version is we get three great outcomes at the same time:

1. There are 67,000 new jobs created that significantly over-index in rural communities: (1) 42,000 – 50,000 direct jobs at the startups that are designing, building, selling, and supporting the robots; and (2) 25,000-40,000 indirect jobs in related industries (like AgTech dealerships or manufacturing firms). This is why we believe that at $5B in automation revenue, this effort becomes rural economic infrastructure all across the US in places where specialty crops are grown.
2. Between 20-25% of the total US farm labor hours are automated. Much of this is continued growth in the non-harvest segments discussed above. We are also modeling some (but limited) progress in harvest automation. This will help reduce the pressure on farmer operations from increased H-2A immigrant farm workers. This is a significant percentage of the ongoing labor challenges that get solved through the use of automation solutions.
3. Based on what we have seen from tech segments historically, when a primary category like automation reaches $1B, there are sub-categories that tend to emerge. When we can push that category number to $5B, the sub-categories increase in opportunity size and in this case increase in count. In the case of automation, I believe there are 5 sub-categories that get created at $5B in annual revenue: (1) systems/operations integration – the dealers and support network that help the robots work inside of and integrate with grower operations represent a $1-2B annual opportunity; (2) the data/analytics tools that emerge from all the data captured by the robots that are making regular passes through fields also represent a $1-2B annual opportunity (this is software solutions – no hardware required); (3) manufacturing growth inside of specialty crop growing regions (we are already seen home grown manufacturing in US specialty crop areas as well as additional manufacturing from international startups seeing success and traction in the US market; (4) bio-circular economy solutions (the re-use and recycling of bio-mass from permanent crop acreage – trees and vines – that are being pulled out for market and SGMA water risk considerations and from the food production facility waste streams in many grower operations that produce things like bagged salads; and (5) AI workflow optimization – which will certainly increase operational efficiencies across the agriculture supply chain based on what we are already seeing from organizations in other segments the past 3+ years. Together, these 5 represent $3.5-$5.5B in annual opportunity in addition to the underlying $5B in automation.

There’s the summary of the strategy around automation – existing VC investment pushes us to $1B in annual revenue and expected VC investment pushes us to $2.5B, then $1B in re-allocated capital supports an incremental $2.5B based on $1B in investment for an equipment support program with 40% subsidies on selected automation equipment. That $5B then creates the 3 outcomes above: (1) 67,000-90,000 jobs; (2) 20-25% of labor automated; and (3) the 5 sub-segments above, which represent $3.5-$5.5B in known adjacent annual opportunity.  We will be working hard with our partners in agriculture, AgTech, DC, and Sacramento to dial in a lot of the details the next several years.

There is more to be done to continue building this out. We need to continue tracking progress towards the $1B in 2030 and $2.5B in 2035, as well as the VC funding for automation to support it. We need more and better solutions around harvest automation to round out the portfolio and drive revenue targets even higher. We need to model the path to $5B to make sure that the startups on the field and emerging soon can get to the kind of manufacturing volume we need to support the $5B target. Lastly, we need to do a fairly complete re-think on the strategy for Universities. To me, this is one of the largest opportunities. Our ability to change the strategy from primarily research deliverables to commercialization deliverables is job 1, and to do that we need to re-allocate dollars toward increased investment in IP protection, licensing, and start creation and we need to incent those outcomes at equal importance to research. We need a healthy front end of the funnel for innovation to create the number of startups required to get enough successfully commercializing to get to the $5B number. More on these topics later. For now, we are excited to share the outline for what we are working on in the WG Innovation team and what we’re building for over the next 10 years.