Revolutionizing AI Assessment in Agriculture

There are roughly 500 million smallholder farms worldwide(source: FAO). 

This figure generally refers to the smaller-scale, family-run operations that dominate agricultural production in many developing regions.

Small and medium-sized agriculture farmers globally share the same challenges, threatening their bear survival, especially in the non-golden billion countries.

Digital transformation and AI can help them - in theory.

The influence of digital technologies in Agriculture started approximately 20 years ago, with very different results.

The most developed and wealthier world countries gained significant results. The example of the EU: the solid number of smallholder farms have a considerable extent foreseeable future due to the two facts:

1.  They succeed in boosting productivity, organizing in unions, orienting to more profitable cultivation, engage in higher parts of the food cycle (not just suppliers of the raw materials)

2.  They succeed due to the vast amount of subsidy programs.

Many economists state that Agriculture in the EU has become a "social category." Given the economic and political challenges the EU will face in the following years, there is a real fear of what will happen if the budget shrinks. The small farm holders are not adequately prepared for the Market.

The situation is far more challenging for farmers in the rest of the world.

Multi-billion initiatives and subsidy programs have not achieved much nationally or through global financial and humanitarian institutions.

The reason is simple:

There was no methodical platform with concrete and practical goals to cover a complete ecosystem of transformation of smallholder agriculture farms.

AKFM Matrix, when implemented and developed as a strategic vision, can evaluate all current AI initiatives, projects, and tools  and find their place in the ecosystem with the following flow:

Awareness:

Farmers are fully aware that the climatic changes and globalized economy will affect their future.

Due to satellite imagery and highly trained AI models, the farmer gets fully personalized insights into what is expected of his micro-location regarding climate change, extreme weather, etc.

Farmers get fully personalized and tailored suggestions on the optimal way of production or recommendations on swapping into different cultures or parts of agriculture (innovative ways of cultivating the existing culture, enhancing the portfolio with added value like bees, swapping from corn to vegetables or greenhouses, from traditional production to organic, etc.), based on the AI-driven model which will measure the influence of the climate change on their micro-locations.

Farmers are fully aware, business-wise, of their performances in the following years, with high accuracy, if they "do nothing" and what their performances will be if they accept help.

Knowledge:

Farmers get the necessary knowledge to pursue a chosen action plan through specific knowledge AI services, which will cover tailor-made day-to-day operations. Most small farmholders do not have sufficient knowledge to improve, enhance their current product portfolio, or enter something entirely new for them. AI technology has brought such a possibility to light.

Farmers raise the general knowledge base level by enhancing their financial skills, entrepreneurship, agriculture in general, Technology in Agriculture in general, and foreign languages, among other things.

Funding:

Farmers have chosen, with the help of AI, the most appropriate way of action to mitigate the influence of climatic changes and the globalized economy.

With the help of sophisticated AI models, farmers have access to all the necessary knowledge to tailor-make day-to-day operations.

The complete assistance of efficient AI tools that will help farmers understand how to optimize their production, gain knowledge in other fields of agriculture, and give all adequate knowledge to conduct operations is not enough.

There is another barrier. Funding.

a. most small farmholders do not have sufficient funds to finance the chosen initiative.

b. The real-life examples showed that government-based subsidies are necessary but not enough or the best solution.

c. The real-life examples showed that many small farmers, especially in rural areas and older populations, lack the necessary skills or information to identify or apply to some programs.

d. Private companies interested in financing particular production face almost insurmountable obstacles in working with a large number of small agro households that are geographically dispersed.

e. Global Financial, International cooperation, or Aid institutions like the World Bank, GTZ, ADA, etc., have obstacles in actively approaching and covering large numbers of dispersed small agriculture households.

Per the AKFM Matrix, AI tools must enhance farmers' access to government and other institutions, subsidies, programs, and initiatives, preferably automatizing and optimizing customs for each farmer.

AI tools must allow private companies to reach small farming households, where AI serves as a proxy and chooses the most appropriate partner for each farmer.

AI tools must allow easy integration of multiple (many) farms into the cluster or union.

AI tools must have trained models that will calculate with a significant level of accuracy :

a. total needed level of costs for the chosen plan

b. revenue stream and profit

c. ROI

MARKET

The fourth pillar of the challenge is the Market. Let's go through the AKFM Matrix, which shows the flow of small farmholders (almost) anywhere in the world.

The AI has introduced the farmer to an accurate and concrete estimate of what will happen with his land, business, and life for the next 10 years, considering climate change and business environment challenges. The farmer is aware and accepts the proposed model of improvement and transformation. 

Through AI, the farmer gains all the customized knowledge necessary to achieve a target. The farmer has also received all the required funding for his activities.

All this effort and finance will be for nothing if there is no proper way for a farmer to sell their goods.

The vast majority of small farmholders are limited to the local trader due to the lack of resources, which offers buyout prices much lower than those from the stock exchange. So, the farmers must find a way to sell "outside their village."

With the help of AI and proper tools, software, and models that will allow AKFM Matrix to score the best, Farmers will gain access to sell directly without proxy to multiple sales channels, dedicated e-commerce sites, and other platforms.

Moreover, AI tools must allow small farmers to quickly and automatically group their products into standardized lots and sell directly on commodity stock exchanges. 

THE CURRENT STAGE OF DEVELOPMENT OF AKFM MATRIX:

It is a brand new model that is about to be used for the first time with a Study of implementing AI into Serbian Agriculture. Dear reader, this is just the tip of the iceberg: conceptual axioms. 

THE FUTURE OF AKFM MATRIX

Think large; start with a small. 

We plan to use our research to identify projects that can pass all pillars of the matrix and gain practical and measurable results in the shortest pace. The chosen proposals will be part of the Study. 

Frequently Asked Questions

Your top concerns addressed to assist you in understanding AKFM.