Why automation hits harder here than almost anywhere else in England
Drive out of Grantham on any road heading east or south and the scale of the thing becomes immediately legible: field after flat field of brassicas, root vegetables, sugar beet — the working landscape of a county that grows roughly one-eighth of England's food. Greater Lincolnshire's annual agricultural output runs to approximately £2.5 billion. Around 30% of England's vegetables and salads come from here, as does 18–19% of its poultry.
The numbers that matter most, though, are the employment ratios. Agriculture generates 18% of Greater Lincolnshire's GVA against a 3% national average. Some 13% of local workers are in the sector, compared with 3.6% across England. Take the wider food chain — processing, packaging, distribution — and the figure climbs to 24% of all Greater Lincolnshire jobs, close to double the national share.
That concentration is not a point of regional pride so much as a structural exposure. When automation moves through an industry that employs one worker in four, the consequences are not contained to the farm gate. They spread through every packhouse, cold store, and logistics yard that sits downstream. The question, then, is a practical one: as robots and AI systems begin taking on the work that has always required human hands in Lincolnshire's fields, what actually changes — and for whom?
The labour shortage that opened the door
Two distinct forces are pushing the transition, and conflating them produces a distorted picture of what is actually happening.
The more visible is the labour shock that followed Brexit. When free movement with the EU ended, Lincolnshire's intensive horticulture sector lost reliable access to the seasonal workforce it had built its logistics around for decades. Packhouses and vegetable farms around Spalding — the heart of England's cut-flower and salad-leaf trade — now report chronic vacancies in picking and packing roles that have not been filled through alternative routes. The Seasonal Worker Visa scheme has partially compensated, but six-month caps, added bureaucracy, and year-on-year recruitment uncertainty have left a structural gap in the semi-skilled workforce. The Lincolnshire Farming Conference has explicitly framed automation as the sector's operative response to that gap.
The second driver is quieter but was always coming regardless of immigration policy. Precision tools — AI-guided sprayers that target weeds rather than entire fields, autonomous soil-mapping units, lightweight robots that tread lightly on compacted ground — offer farmers genuine input-cost reductions and a route toward sustainability commitments that regulators and retailers increasingly demand. These are productivity and efficiency arguments, not substitution arguments.
The distinction matters because it changes who bears the risk. Replacing absent workers is a short-term structural fix; upgrading productive capacity is a long-term transformation of what tasks farms require humans to perform at all. Both pressures are active simultaneously — which is why the transition is accelerating now rather than in five years.
What the machines are actually doing in Lincolnshire fields
The FarmDroid FD20 offers a useful way into this. Solar-powered and GPS-guided, it seeds and weeds in a single pass — eliminating the need for either chemical herbicide runs or hand labour between crop rows. It featured in Clarkson's Farm Series 5, which gave it a visibility few agricultural machines ever achieve, but by the time the cameras were rolling, early units were already operational on Lincolnshire farms.
Alongside the FD20, AI-powered weed-detection sprayers are moving from demonstration plots into routine use. Rather than treating whole fields, these systems photograph and identify individual plants in real time, applying herbicide only where needed — cutting chemical inputs and input costs simultaneously. Autonomous soil-mapping units give operators continuous data on compaction, moisture, and nutrients across variable terrain, making field-scale decisions that previously required contractors or guesswork.
Coordinating multiple machines across a single operation is the problem that Lincolnshire spin-out JABAS.AI has built its platform to solve — providing real-time autonomy software for robot fleets rather than requiring each unit to be individually managed in the field.
Behind the commercial adoption sits a research infrastructure that gives the region unusual depth. The University of Lincoln's Lincoln Institute for Agri-Food Technology (LIAT), based at the 200-hectare Riseholme Campus, won the Queen's Anniversary Prize in November 2023. Its work feeds into the AgriFoRwArdS Centre for Doctoral Training — run jointly with Cambridge and the University of East Anglia — which trains PhD researchers in autonomous harvesting and multi-robot systems using Thorvald field robots, returning technically skilled people to a regional sector that badly needs them.
The skills gap running alongside the technology gap
The finding that surprised Lincolnshire County Council's own agri-food forum is worth sitting with: technology adoption across the sector is being held back less by the cost of the machines than by a lack of confidence, knowledge, and appropriate training among the people who would use them. This is a different problem from an equipment-procurement problem, and it requires a different kind of solution.
The challenge is structural. Skills in robotics maintenance, sensor data analysis, GPS-guided machinery, and digital farm management are in short supply — and the agricultural workforce is ageing, which compounds the gap. These are not failings of individual workers; they reflect the speed at which the skills precision farming now demands have changed relative to the systems built to teach them.
Peer-led learning, it turns out, works better than top-down instruction. Lincolnshire farming clusters that have embraced collaborative knowledge-sharing have improved productivity by up to 13%, according to county council analysis — a concrete return from farmers teaching farmers rather than from mandated workshops.
Formal infrastructure exists and is growing: Riseholme College runs precision agriculture courses; the National Centre for Food Manufacturing at Holbeach delivers automation apprenticeships and short courses; LIAT's research pipeline at Riseholme Campus connects doctoral-level work directly to commercial practice. The problem is pace rather than absence. The technology is entering Lincolnshire fields faster than the training system can produce people who can confidently operate, maintain, and adapt it — and in a district as thinly employed as South Kesteven, that lag is not an abstraction.
Who carries the risk and who captures the benefit
The academic evidence here does not settle neatly, and it is worth being honest about that. A 2026 study applying vector error correction modelling to South African agricultural employment data across three decades found that Fourth Industrial Revolution automation has net negative effects on farm employment in both the short and long run — human labour, the authors concluded, is "particularly at risk of replacement." A contrasting 2025 American analysis reached the opposite conclusion: farm automation, it argued, can raise both employment and wages by expanding total output and generating better-paid roles in complementary sectors. Both findings are methodologically serious. The difference in outcome reflects real differences in context — sector structure, farm scale, policy environment — rather than a straightforward error by one side.
What bridges the gap between these competing conclusions is the concept of labour market 'thickness.' The idea is straightforward: the fewer alternative employers near you, the harder it is to find replacement work if your role disappears. In a dense urban economy, a displaced worker has many options within commuting distance. In South Kesteven — 147,151 residents, roughly 54,000 in employment spread across 6,265 businesses in a low-density rural district — that safety net is thin. Research published in the Journal of Rural Studies confirms that sparse rural labour markets convert automation risk into actual unemployment at higher rates than their urban counterparts.
The distributional question sharpens this further. Seasonal migrants, older semi-skilled workers, and domestic food-factory employees face the most direct displacement risk as robotics take on manual harvesting, weeding, and packing roles. STEM graduates, automation technicians, and data analysts are positioned to capture most of the upside. How many people in South Kesteven's agricultural workforce occupy each of those positions, and how their options would realistically look if their roles contracted, remains unanswered — a gap that any serious local policy conversation will eventually have to close through ground-level employer and workforce research.
What this transition means for work around Grantham
South Kesteven's Draft Local Plan names intensive agriculture as a key economic feature of the district's rural area — making automation not simply a farm-level efficiency question but a strategic one for the district as a whole. When machines replacing seasonal harvesting labour are already arriving in Lincolnshire fields, land-use and economic planning frameworks need to be thinking about where displaced workers go next.
The SKDC Economic Development Strategy 2023–2028 identifies one credible answer: the A1 corridor running through Grantham is flagged as a potential compensating employment zone, linking logistics, light manufacturing, and distribution to the agri-food supply chain. That offset is genuinely present in the planning evidence. The limitation is that the strategy contains no farm-specific projections — no estimate of how many agricultural roles in the district may contract, over what timescale, or which communities face the sharpest exposure. The planning framework has not yet caught up with the pace of on-farm technology change.
That gap matters in a district where the labour market is thin: roughly 54,000 people in employment across a low-density rural area, with fewer alternative employers within reach than most urban economies can offer. Research is clear that sparse labour markets convert automation risk into actual unemployment at higher rates than their denser counterparts. Whether the A1 corridor can absorb that pressure at sufficient scale and speed is, for now, unknown — because no one has been commissioned to quantify it.
The honest local takeaway is neither alarm nor reassurance. The transition is already underway; the regional training and research capacity this area has accumulated is real. The question — still open — is whether South Kesteven's economic planning moves fast enough to shape how automation lands, rather than arriving, after the fact, to manage the consequences.
- [1] Workforce Implications From Farm Automation. (2025). https://doi.org/10.1002/aepp.70009 https://doi.org/10.1002/aepp.70009
- [2] Impact of Fourth Industrial Revolution (4IR) Automation on Agricultural Employment in South Africa. (2026). https://doi.org/10.3390/econometrics14030031 https://doi.org/10.3390/econometrics14030031
- [3] Regional variations in automation job risk and labour market thickness to agricultural employment. (2022). https://doi.org/10.1016/j.jrurstud.2021.12.012 https://doi.org/10.1016/j.jrurstud.2021.12.012