The Demographic Collapse Is Already Here: Is the AgriFood Industry Ready?

Published on June 17, 2025

Demographics is one of the topics that fascinates me the most. Indeed, what is more important for our collective future than knowing how many people will be on this planet? In my opinion, it might be the most underestimated threat facing the food industry. While fertility is collapsing globally, ageing is accelerating everywhere, and yet no one seems to be preparing for it. From fewer farmers to shrinking consumer markets, the impact will be brutal unless we act now.

1 – We need to reduce labour in food more than ever

In the past week, we have received multiple worrying signs on fertility and birth rates. First, the United Nations released an update to its global fertility report, which downgraded its fertility outlook.

As you can see in the graph, this follows a severe decline in fertility around 2020 and the COVID pandemic, from which we have not recovered, as the world entered a period of high inflation and rising concerns about economic opportunities.

Japan, often mentioned as a country at the forefront of this reversed demographic transition, announced an extremely low number of births for 2024. Only 686,000 Japanese were born last year, which the country planned to reach only in 2039!

2 – Agriculture’s workforce has plummeted globally and will continue to shrink

One of the first consequences of this declining birthrate is that the number of people able to work in the agrifood value chain will also shrink at a rate that will probably be even higher. Indeed, as the industry tends to offer lower salaries and harsher conditions, it will have a harder time competing with other employers.

That’s why technology, notably automation, will be necessary to feed a population that will keep rising, even as it is ageing. On the positive side, as you can see on the graph below, this has already been done with great success over the past century for the upstream part of the value chain. While more than 50% of the workforce was involved in agriculture, that share has now declined to low-single-digit numbers.

For agriculture, the consequence of the fertility decline will be pretty visible in the short term, with farmers already being relatively older than the rest of the population. Beyond a more proactive adoption of automation technologies (including precision farming), concentration appears to be inevitable. However, that’s not where we are heading, notably in Europe, where the idea of extensive farms manned by robots is not what voters want to see.

3 – Automation is still not working for food retail

Compared to agriculture, food and beverage retail stores have just started their automation journey. For now, most of the experiences have had quite mixed results.

This can be illustrated by the graph below about Starbucks’ case in the US. While the company expanded its number of stores in the past years, it has seen its number of employees per store (or more precisely, the number of employees in the company divided by the number of stores) shrink. But the result has been far from positive. Starbucks’ results have been quite bad over the past couple of years, with the recently installed CEO hinting that consumers feel less well-served and lack some human interaction. In other words, the company will go in the reverse direction and halt the deployment of some of its high-tech solutions.

Starbucks is far from an isolated case. A recent similar example is Chipotle’s founder’s new restaurant venture. It was supposed to be a fully automated place. After a year and $36M raised, it was a failure, and it is now being rebranded as a quite classical sandwich delivery business. Other experiences are more successful. Sweetgreen’s automated restaurants seem to work, but they still include a significant part of human service and are only viable in some high-traffic areas.

4 – What could be the consequences for the food industry?

In a word, the population is ageing much faster than anticipated (including in developing economies). This creates multiple threats as well as opportunities for food companies, including:

Threat #1 – a shrinking pool of consumers: an ageing population means that the traditional model of development of agrifood business (more mouths to feed) will rapidly vanish. This will be compounded by the fact that many developing economies could miss their opportunity to reach middle-income status.

Opportunity – focusing on healthy ageing, services, and added value ingredients

Threat #2 – declining workforce and raw resources become scarcer

Opportunity – automation and vertical integration

Beyond these obvious factors, demographics is a multi-faceted challenge that includes many other aspects, notably societal and political behaviours that will evolve alongside the age distribution. As we often say to our clients, answers won’t be in short-term trends (and especially not in consumer surveys).

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Use case: project for a global F&B company looking to map its AgTech innovation ecosystem and the best startups to partner with

What we did:

  • Mapping of the AgTech ecosystem: startups, research regulators, and other leading companies.
  • Discussion to select areas to focus on.
  • Analysis of the information to reveal the trends and a model to analyse eventual partners.
  • A workshop to validate the opportunities based on our recommendations.
  • Scouting of relevant partners followed by introductions.

Results:

  • Mapping the different categories of innovations in AgTech that should be considered now to create long-term benefits for the business.
  • Identification of key partners (an incubator and a couple of startups).

Use case: project for a CPG company on the healthy ageing ecosystem

What we did:

  • Education of the board through a couple of workshops to define the perimeter
  • Identification of key opportunities and threats created by long-term evolutions (technologies, business models, behavioural changes).
  • Deep dives on each of the priority categories.
  • Co-construction of a vision on how the company should address these challenges.
  • Identification of partners (startups, incubators, funds) to move forward.

Results:

  • Creating a consensus on which categories to prioritise and how to address them.
  • Implementation of an open innovation strategy through the development of partnerships.

Use case: project for a global CPG company to develop a strategy on the healthy ageing ecosystem

What we do (ongoing mission on a subscription model):

  • Kick-off where we present an overview of the AgriFoodTech ecosystem to select with the client the categories to cover and for each, the level of information required.
  • Monthly newsletter: each month we send a newsletter with the articles that we have gathered ranked by relevance, their summaries, and a layer of analysis.
  • Database: we set up a personalised database that will be filled month after month with the information gathered on the companies identified for the watch.
  • Workshops: twice a year with the client’s innovation team and other “innovation curious” team members, we present an overview of the evolutions, key trends and a dashboard of the topics followed by the watch.

Results:

  • A clear, regular and evolutive tool to follow what is happening in terms of innovation on key topics.
  • A forum (through the workshops) to discuss innovation trends and new opportunities.

Use case: opportunity screening for an ingredient company

What we did:

  • Kick-off to define the perimeter of the ecosystem studied.
  • Mapping of the different trends shaping the innovation ecosystem of the client.
  • Analysis of the trends on DigitalFoodLab’s trend curve and other relevant frameworks.
  • Workshop to discuss DigitalFoodLab’s recommendations on key trends to prioritise

Results:

  • Shared view of the innovation ecosystem for the client with a view of the trends to prioritize.
  • Clear document (personalised trend curve) that can be easily shared internaly to explain the company’s innovation choices and which can be then updated each year.

Use case: scouting for an agriculture coop

What we did:

  • Kick-off to define the perimeter of the client, the goals of the scouting (partnerships) and the criteria on which startups should be evaluated.
  • Set-up scouting: we selected the first batch of 20+ key startups following the criteria of the client.
  • On-going scouting: then we set up a quarterly scouting of about ten startups.
  • For each scouted startup, we created an ID card with key information such as the business and technological maturity, funding, and corporate partnerships. We also added an explanation of why we selected this startup.

Results:

  • An ongoing and evolutive scouting are matching the client's criteria and its capabilities in terms of deal flow.

Use case: working on an acquisition process for a CPG company

What we did:

  • Kick-off to define what the client is seeking, notably in terms of maturity.
  • Workshop with the client based on a mapping of the different innovation ecosystems adjacent to its activities to select some priorities and discuss inspiring examples of startup acquisition stories.
  • Identification of 20+ targets.
  • Workshop to select the most relevant to engage with.
  • DigitalFoodLab worked as a sparing partner during the acquisition process, notably to help design how the acquired startup could be integrated into the overall company’s strategy.

Results:

  • Different results from traditional M&A processes with a focus on the client’s innovation strategy.
  • Identification of a good match for an acquisition.

Use case: market due diligence on sugar alternatives

What we did:

  • Kick-off with the client to discuss its interest on this category, its expectations and existing level of information (notably on the target company).
  • Mapping of the ecosystem to analyse the different existing alternatives and technologies to compare them.
  • Interview (calls) with relevant startups made by our internal biotechnology expert.
  • Recommendation on whether to invest or not.

Results:

  • Clear view of the ecosystem and of the reasons to believe (or not) in each sub-category.
  • Enforceable recommendations based on facts and expertise.