AI in the Food Industry: Transforming the Food from Farms to Forks

Technology in the current world is improving the DNA of the industries, and the food industry is no exception. From thinking of expansions to overcoming setbacks, the first thing that one thinks of is

“There must be some technology to help me overcome this challenge?” 

One of the finest case studies of technology/AI in the food industry is of Tyson Foods. The company today uses computer vision and automation to improve their meat processing. This decision came shortly after they faced challenges with shortage of labour due to COVID-19 pandemic in 2020. 

Workers’ illness or COVID-19 safety protocols led to slowing down the production and disrupting the entire supply chain. 

In response, Tyson Foods decided to steer its way through the technology route. They accelerated their investment in robotics, computer vision, and machine learning technologies, starting 2021. Tyson announced that it would invest over $1.3 billion by the end of 2024 in automation and digital transformation of their production processes. 

Key focused areas:

• AI-powered vision systems to precisely cut meat and control quality
• Robotic arms to replace repetitive laborious tasks
• Sensors and analytics to real-time monitor the operations

Instant Impact:

• Significantly reduced reliance on manual labour 
• Enhanced speed and consistency in meat cutting and packaging
• Independent to threat of labour shortages

As a result, Tyson was successful in maintaining output irrespective of the challenges and set a safer, smarter, and more resilient way in food production systems. 

Well, that is how technology has erupted and transformed the food industry and its functions since decades now.

How Automation has Transformed Food Industry

Automation through AI in food industry has significantly transformed the entire journey of food from farms to forks. There is a new-age technology that assists in producing, storing, delivering, and consuming food.

Machine learning, generative AI, data analytics, and computer vision are some of the fundamental technologies behind revolutionizing the bottomline of the food industry. They are widely preferred in improving agricultural practices, optimizing production and supply chain, reducing waste, and planning production with predictive analysis from churning the precisely available data. 

Increasing Role of AI in Food and Beverage Industry

AI is taking over the end-to-end supply chain to apply mechanisms for reducing waste and adopting intelligent agricultural practices to improve yield. With its capability of being highly personalised, it is impacting efficiency and sustainability, irrespective of the food sector, hierarchy, or segment.

Source: Mordor Intelligence

This is why the current market size of the AI in the food and beverage industry is all set to cross USD 9.68B by the end of 2025. Growing at a CAGR of 38.30%, it is expected to reach USD 48.99B by 2029. 

Recent studies have found that in the near future AI will help in cutting production costs by up to 20% in the agricultural sector specifically. 

The way the application of AI in food industry is evolving, it is going to be a game-changer in multiple ways. 

Let us find out about more of its implications in the following parts of this blog. 

Benefits of AI in Food Industry- Segment Wise Implications

1. Advanced predictive analytics for agriculture

With the advancement in AI, latest predictive analytics are capable of precisely forecasting weather and crop yield predictions. The science behind this is that it analyses huge chunks of data regularly collected by drones, sensors, and satellites to monitor soil’s health, pest infestation if any, thereby resulting in healthier yields. This saves farmers’ time and cost otherwise incurred in field trials and food inspections. 

2. End-to-end supply chain management

Supply chains function as the nervous system that connects and coordinates the entire industry ecosystem. With its fundamental role of tracking products throughout, it additionally helps in managing inventories, conducting the quality check (QC) at the entry level, and ensuring best practices throughout the operational services. 

3. Reduced inventory stock hold in food retail

AI in the food service industry is being used more than ever in the current age. Not only its predictive analytics help in forecasting demand, but also reduce wastage. Automated accurate predictions, on the basis of data collected by AI, is one of the most powerful features of AI to reimagine the entire game in the food industry. 

4. Sets accountability for food safety and quality

AI in food industry is making companies more accountable by instilling compliance and transparency. From identifying staff that is not following the food safety protocols on the floor to tracking the production in real-time, it sees, captures, and highlights even the minutest details that can contaminate the entire produce. Smart isn’t it? Good quality, accountable supply chain, and significantly saved hours.  

5. Automation of food manufacturing in factories

Having a similar productivity 365 days is manually impossible. Because humans are not machines. But to effectively cut through the competition, one can enable technology, AI and robotics to eradicate all possible delays. 

With application of AI in food industry and robots, the entire process of sorting, categorizing, cleaning, and packing food in different containers become autonomous. 

Robots or automated machines will self move and undertake processes to convert raw materials into finer goods ready to move out of production to their next destination. 

6. Automating food delivery for precise conversion

AI plays a crucial role in automating the entire food delivery process and makes it faster, smoother, and efficient.

Let us take an example of Uber Eats here. When you open the app, it analyzes your location and suggests your preferred restaurants depending on your browsing history, order history, and location. After you place an order, it automatically assigns the delivery partner on the basis of their location, workload, and delivery history. Additionally, the AI predicts peak order time and locations, helping restaurants to make preparations in advance.

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How to Include AI in the Existing Food Industry

In order to successfully integrate AI with your existing food industry, you’ll need a more defined approach that will include cohesive planning, data integration, and execution. Below is the 10-steps guide to help you successfully integrate AI in the food industry. 

1. Create a SWOT (Strengths, Weaknesses, Opportunities, Threats) Analysis 

Identify areas in your food industry where AI can replace human and add most value, such as inventory management, supply chain management, customer service, or quality control. 

How to do it:

• Conduct internal audits of your operations and workflow
• Identify bottlenecks, triggers, and inefficiencies. Whether it was a gap in supply chain leading to long wait time, inaccurate demand assumptions. 
• Explore areas that can instantly benefit from integrating AI first, like customer service or automation in food production. 

2. Collect and segregate data

AI works on data, just data! The better your accumulation and organization of data would be, the better it will work as a generative AI in food industry. 

How to do it:

• To gather real-time data on temperature, humidity, and other factors, implement IoT sensors in your production, storage and delivery floors. 
• To gather transactional data and preferences, bring in use POS systems and customer feedback tools. 
• Finally integrate all your data in a central data management system

3. Carefully opt for the right option for AI in the food industry

Analyze and select for the AI tools and technologies that perfectly align with your opportunities and hold capabilities to extinct current business challenges. 

How to do it:

• To help you with demand forecasting and supply chain management, opt for AI platforms that use machine learning (ML) for predictive analysis. 
• To make customer service smoother, implement AI-powered recommendation engines and chatbots. 
• To assist you in food production and automating the process, explore vision AI and robotics. 
• To optimize routes and delivery management, consider AI powered delivery solutions.

4. Integrate AI in your existing system

Effortlessly integrate AI in your existing system without disrupting the entire workflow.

How to do it:

• Collaborate with top AI development company like Xicom Technologies to ensure a smoother integration. Host a suite of AI tools like POS, ERP, and supply chain management with a unified integration. 
• Preferably use cloud based AI systems to easily scale up as and how your business requires. 
• Make sure your AI tools are connected with all the relevant sources to feed in the accurate data for insights and predictions

5. Set up a pilot program first

Start integrating the program in stages. Do not fully load it at once, increase your dependency on AI step by step.

How to do it:

• Select a couple of domains where integration of AI will give maximum impact. For example: customer service or inventory management. 
• Run a pilot program in a controlled environment, such as one factory, route, or delivery center
• Collect performance feedback and assess its effectiveness. 

6. Conduct AI training

To make the adaptation process easy, conduct frequent AI training in the beginning and help them understand its benefits. 

How to do it:

• Conduct training for staff on how to use AI tools, interpret insights, and respond to alerts generated through AI. 
• Encourage inter department collaborations to ensure everyone in the team, from IT to operations, is adept with AI and its impact on their roles. 

7. Track, Evaluate, and optimize how AI will work

Constantly measure the performance of the AI in food industry, and optimize it on the basis of data and feedback generated. 

How to do it:

• Set KPI or Key Performance Indicators to track AI’s effectiveness on the parameters. Few scenarios of KPIs can include significantly reduced delivery times, more accurate demand forecasting, and reduced food wastage. 
• Frequent monitoring of AI models will ensure they remain accurate. Also, you can make adjustments in your system with the gathered new data and changing business conditions. 
• As you gain access to more insights, iterate and improve your AI models and strategies for better outcomes. 

8. Slowly scale up AI implementation

Once the pilot phase is over and successful, now you can expand AI to other branches or departments.

How to do it:

• Gradually scale your AI solutions across your supply chain process as per the roadmap created.
• After receiving success from AI in one department, expand other successful AI tools in other departments. 
• Consider AI for the future. Discuss, evaluate, and consider how AI can help you in the future. The earlier you plan, the ahead of the competition you will stay. 

9. Stay up-to-date with ever-evolving AI trends

Keep an eye on advancements in AI in food industry. Stay up to date with the latest developments and their impact. 

How to do it:

• For example, you must keep an eye og later AI and AgTech trends to evaluate how they may impact your production, manufacturing and packaging, and delivery. 
• Attend industry conferences and forums to stay well informed about latest AI tools and innovations. 
• Upgrade and update with time to ensure your system is relevant, effective, and secure. 

10. Ensure ethical practices for fair AI use

Make sure that AI implementation is fully ethical, transparent, and does not hinder individual’s privacy. 

How to do it:

• Ensure your AI system complies with data protection laws like CCPA and GDPR to ensure employees’ and customers’ data is handled responsibly. 
• Inform your customers well in advance on how you will be using their data. 
• Be vigilant with AI systems to avoid biased decisions. 

Challenges of AI in the Food Industry

Switching from contemporary methods to something new is always challenging. And, AI in the food industry is no exception. When you’re moving towards technology, there will be some barriers. Let us explore each one of those in detail and how you can overcome them.

1. Inconsistent data availability and quality

Inconsistency in data can be a big hurdle for AI to perform its functions accurately. While the existing data can be minimal, adoption of AI can help you overcome this challenge as the machine learning consulting services company will help you develop an AI system that can implement robust data collection, categorization, and its integration into the system to create reliable data sets. 

2. Relatively higher initial implementation costs

There is no doubt about AI solutions being costly solutions. Therefore, AI solutions can be developed and deployed in stages to help food production businesses incur such heavy costs in smaller installments. 

3. Initial workforce resistance and skill gap

Lack of AI expertise and resistance to change are two commonly pointed out challenges. This can be easily overcome by user-friendly tools and initial training to make the transition smoother. 

4. Misinterpreted as threat to privacy

Initial resistance to switch can also be due to AI or technology being misinterpreted as a threat to privacy. But such is not the case. Such software/AI solutions are made legal guidelines in mind to protect data and promote its legitimate usage.

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Future of AI in Food Industry

AI, or Artificial Intelligence is set to disrupt the existing food industry and drastically enhance its efficiency, sustainability and consumer satisfaction. As AI is continuously evolving and seamlessly integrating into various aspects of the food value chain, from production to consumption, it is becoming highly transformative. 

In the agricultural sector, AI will play a crucial role in precision farming. Drones, advanced sensors, and machine learning (ML) models will enable farmers to monitor health of the crop, predict yields, and carefully optimize irrigation and pesticide usage. Thus, it will not only increase productivity, but will also support sustainable production. 

In food processing and manufacturing units, automation powered by AI will streamline operations, assist in quality control, and minimize the chances of human errors. Machine vision can detect defects, while proactive predictive maintenance systems can warn for system maintenance and reduce downtime. AI can also facilitate in developing new products from its analyses on consumer trends and preferences. 

Supply chain is another major area that will be highly impacted. AI will enhance precisely accurate demand forecasting, aid in inventory management, logistics and enhance sustainability to reduce food wastage. Real-time data analytics helping understanding changing market conditions and scenarios, such as seen during global events like COVI-19 pandemic. 

Last but not the least, consumer experiences will also transform. AI has started taking over direct consumers as well. With personalized nutrition, recipe suggestions, smart kitchen assistants, aids to cater to individual health needs, generative AI in the food industry will enhance overall consumer interaction and engagement. 

Despite its bright promises and work, AI in food industry will require constant checks to cater to challenges like data security, ethical concerns, and constant need for the workforce to upskill. With responsible implementation and fair usage, AI has the potential to create an intelligent, safe and sustainable food ecosystem for the future. 

Get Your AI solutions Developed with Xicom Technologies Just Like Keeta

Keeta is the new-age food delivery app developed by Xicom Technologies to cater to the evolving needs of the urban consumers. It has its headquarters in Hong Kong and internationally linked with China’s brand name Meituan. 

Keeta is designed to offer:

• Seamless
• Quick
• And affordable food ordering experience to customers.

Keeta collaborated with Xicom, software development services company to reimagine its platform’s performance, ace the user experience on the platform, and aid in scaling up.

Here are the set of challenges that Keeta came with to Xicom. 

1. Creating a consistent and seamless user experience across Android and iOS platforms with varying device specifications.
2. Managing real-time order tracking and restaurant discovery while ensuring accuracy and speed.
3. Developing a scalable architecture to support rapid expansion into multiple international markets.
4. Integrating multilingual support to provide localized experiences in each operational region.
5. Ensuring fast loading speeds and smooth transitions through optimized backend infrastructure and caching.
6. Implementing secure and flexible payment gateways, including local options, to cater to diverse user preferences.
7. Establishing responsive in-app customer support, capable of resolving issues quickly and efficiently across time zones.

Solutions:

As the first step, we delivered a customized, multi-lingual, and high performing food delivery platform with modern UI, real-time features, and options to facilitate global scalability. 

Being the top AI development company, Xicom Technologies crafted a comprehensive, user-centric food delivery app for Keeta. Our team implemented a sleek UI that aligned with brand’s color theme and ensured a smooth navigation. React was used as the fundamental technology to create a seamless frontend that could run across devices. 

Technologies like Node.js and MangoDB were picked to enable quick data processing, and Firebase supported real-time order tracking. Along with it, the built in multilingual support ensured global accessibility, secure payment gateways instilled trust and responsive in-app support worked together to create a wholesome experience.

These crucial technological advancements helped Keeta achieve:

1. 44% share in Hong Kong’s food delivery sector, surpassing competitors like Foodpanda and Deliveroo.
2. The app achieved 1 million+ downloads and maintained an average rating of 4.5 stars on playstore.
3. Keeta is now expanding to Saudi Arabia and considering local partnerships there.

You can refer to the full case study here: Xicom Keeta

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In the End, 

AI in food industry is helping companies upgrade their key areas of operation. One such case study of Keeta, the HongKong based food delivery app, is also shared above. It explains how Xicom Technologies, the top AI development agency, helped Keeta upgrade their UI, UX, route optimization to achieve precisely accurate in-app experience for their customers.

AI just does not integrate another layer of innovation, it focuses on revolutionizing your entire business and its processes. It starts from improving food safety, to sustainability, and focusing on reducing wastage to promote sustainable production.

Planning to integrate an AI solution and make processes in your food industry operations seamless? Connect with us now!

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