AI Competency for the Agriculture Sector
Call to Action in the Agriculture Sector
The UK agriculture sector faces significant challenges in adopting and leveraging AI technologies, creating a pressing need for Atlas, an AI Training and Learning Specialist Agent. This need is supported by several research insights:
1. Low AI adoption: 55% of UK farmers have never invested in advanced AgriTech and have no immediate plans to do so, indicating a substantial skills gap that Atlas could address[1].
2. Productivity challenges: The agriculture sector is described as one of the least digitised in the world, highlighting the urgent need for innovation and efficiency improvements[1].
3. Cost barriers: 56% of farmers cite high capital expenditure costs as barriers to AI adoption, with many still determining the return on investment[1].
4. Skills shortage: As the industry becomes more technologically driven, there is a growing demand for talent with a wide range of highly developed skills [1].
5. Market growth: The AI in the agriculture market is expected to grow from £1.36 billion to £3.77 billion by 2028, emphasising the need for skilled professionals[3].
6. Transformative potential: AI offers significant scope to increase efficiency through predictive capabilities for weather data, prices, and crop yield[2].
7. Government support: Recent funding of £12.5m for 19 innovative projects in robotics and automation demonstrates the sector's potential for AI integration[2].
Atlas based on [6] offers a scalable, cost-effective option for AI competency development in the agriculture sector, but it needs to be aligned with industry priorities. The UK's world-class technology and research capabilities position it at the forefront of innovation and implementation in agricultural AI[1].
To this end, in December 2024 and January 2025, industry leaders are hosting online meet-ups to discuss the sector's next steps in addressing the AI skills gap. Join the conversation to shape the future of AI skills development in agriculture: https://calendly.com/josephconnor-carefulai/wednesday-1000-1030
Citations:
[1] https://www.barclays.co.uk/content/dam/documents/business/business-insight/Insights_AI_in_Agriculture.pdf
[2] https://www.pricebailey.co.uk/reports/current-trends-technologies-uk-agricultural-technology-industry/
[3] https://www.linkedin.com/pulse/bridging-ai-gap-uks-four-highest-growth-sectors-digital-catapult-tuz6e
[4] https://assets.publishing.service.gov.uk/media/656856b8cc1ec500138eef49/Gov.UK_Impact_of_AI_on_UK_Jobs_and_Training.pdf
[5] https://science.food.gov.uk/article/123638-use-of-ai-in-the-uk-food-system
[6] AI Skills for Business Competency Framework & Resources. Author Alan Turing Institute
https://iuk-business-connect.org.uk/opportunities/ai-skills-for-business-competency-framework-and-resources/
Citation: https://zenodo.org/records/11092677, https://creativecommons.org/licenses/by/4.0/legalcode
The UK agriculture sector faces significant challenges in adopting and leveraging AI technologies, creating a pressing need for Atlas, an AI Training and Learning Specialist Agent. This need is supported by several research insights:
1. Low AI adoption: 55% of UK farmers have never invested in advanced AgriTech and have no immediate plans to do so, indicating a substantial skills gap that Atlas could address[1].
2. Productivity challenges: The agriculture sector is described as one of the least digitised in the world, highlighting the urgent need for innovation and efficiency improvements[1].
3. Cost barriers: 56% of farmers cite high capital expenditure costs as barriers to AI adoption, with many still determining the return on investment[1].
4. Skills shortage: As the industry becomes more technologically driven, there is a growing demand for talent with a wide range of highly developed skills [1].
5. Market growth: The AI in the agriculture market is expected to grow from £1.36 billion to £3.77 billion by 2028, emphasising the need for skilled professionals[3].
6. Transformative potential: AI offers significant scope to increase efficiency through predictive capabilities for weather data, prices, and crop yield[2].
7. Government support: Recent funding of £12.5m for 19 innovative projects in robotics and automation demonstrates the sector's potential for AI integration[2].
Atlas based on [6] offers a scalable, cost-effective option for AI competency development in the agriculture sector, but it needs to be aligned with industry priorities. The UK's world-class technology and research capabilities position it at the forefront of innovation and implementation in agricultural AI[1].
To this end, in December 2024 and January 2025, industry leaders are hosting online meet-ups to discuss the sector's next steps in addressing the AI skills gap. Join the conversation to shape the future of AI skills development in agriculture: https://calendly.com/josephconnor-carefulai/wednesday-1000-1030
Citations:
[1] https://www.barclays.co.uk/content/dam/documents/business/business-insight/Insights_AI_in_Agriculture.pdf
[2] https://www.pricebailey.co.uk/reports/current-trends-technologies-uk-agricultural-technology-industry/
[3] https://www.linkedin.com/pulse/bridging-ai-gap-uks-four-highest-growth-sectors-digital-catapult-tuz6e
[4] https://assets.publishing.service.gov.uk/media/656856b8cc1ec500138eef49/Gov.UK_Impact_of_AI_on_UK_Jobs_and_Training.pdf
[5] https://science.food.gov.uk/article/123638-use-of-ai-in-the-uk-food-system
[6] AI Skills for Business Competency Framework & Resources. Author Alan Turing Institute
https://iuk-business-connect.org.uk/opportunities/ai-skills-for-business-competency-framework-and-resources/
Citation: https://zenodo.org/records/11092677, https://creativecommons.org/licenses/by/4.0/legalcode
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