In the not-so-distant past, the buzzword in technology was digital transformation. However, today, a new term has taken center stage: Artificial Intelligence (AI).
As tech giants vie for supremacy in this groundbreaking field, there is enough reason for players in all sectors to understand what this could mean for their industry.
And for those who do business in the food and agriculture industry to whom insurance is so crucial, the advent of AI is anticipated to bring about substantial changes. Insurance is one of the most important pillars across major industries, and the food industry is no exception. From the farmland to the dining table, the various stakeholders involved heavily in this industry rely on insurance as a safeguard against all manner of risks.
Let’s delve briefly into how AI is likely to influence different aspects of insurance within the food industry, specifically for farmers and businesses along the food chains.
Crop insurance
AI can be used to predict crop yields and identify areas that are at risk of crop failure. This information can be used to price crop insurance more accurately and to help farmers make better decisions about their crops.
Cutting-edge AI technologies such as machine learning and satellite imaging could be harnessed to gain accurate insights into crop health, predict potential disease outbreaks or disasters, and estimate yields. With real-time and accurate data on hand, insurance companies could provide more tailored insurance policies that align with the farmer’s specific circumstances and risks, ultimately leading to fairer premiums and more timely claim settlements.
According to the Food and Agriculture Organization (FAO), disasters through the decade between 2008 and 2018 resulted in losses running into billions of US dollars across several regions. Asia was the worst hit at $49 billion, followed by Africa at $30 billion.
If the power of AI was to be put into good use, these huge losses can be mitigated.
Farm equipment insurance
AI can be used to monitor farm equipment for signs of wear and tear. This information can be used to predict when equipment will need maintenance or repairs, which can help to reduce the risk of costly breakdowns.
With the advent of AI-powered predictive maintenance, insurers could monitor the health of farming equipment continuously. This data-driven approach could allow for more personalized policy pricing, depending on the equipment’s usage, maintenance schedule, and age. Consequently, farmers could potentially lower their insurance costs by demonstrating responsible equipment usage and regular maintenance.
In other words the current approach of detecting and repairing will transition to predicting and preventing. The advent of autonomous farming equipment will make this even much easier.
Livestock insurance
The incorporation of AI algorithms into monitoring systems could track animal health indicators, such as body temperature and movement patterns, thus predicting potential health risks. This allows for proactive risk management, potentially reducing insurance claims due to unexpected livestock loss. Also, with the help of AI-driven analytics, insurers could offer more precise premium calculations and faster claim processes, thereby elevating the overall customer experience for livestock owners.
The AI system’s ability to consistently monitor and analyze the health data of each animal can inform more accurate risk assessments for the insurer. This could potentially lead to personalized premiums, saving farmers money by accurately reflecting the health condition and risk associated with their specific livestock.
Transportation insurance
By analyzing data from IoT-enabled devices in vehicles, such as GPS trackers and onboard sensors, insurers could better predict and prevent accidents and losses during transportation. This could result in safer transit routes, decreased freight costs, and lower insurance premiums for businesses.
Risk analysis and mitigation is the name of the game in insurance, and risk is a big deal in the food industry. A truck carrying expensive food could overturn and suddenly the food becomes valueless. Extreme weather conditions can render a promising crop useless in one day.
What if we could predict most of these risks with precision? It’ll be a win-win for both the food businesses and the insurance companies. This is what Artificial Intelligence promises to deliver for insurance across the food and agriculture sector.
Instead of focusing on detecting problems when they have already occurred, AI will bring prediction and prevention.
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