• Anantaya Pornwichianwong

5 Industries that can grow exponentially with AI



AI and machine learning are considered to be a game changer that has changed the entire world because of their capabilities to do things that we once thought only humans could do, such as predicting, analyzing, and using human-like senses.


As you may know, technologies that make such a huge impact unavoidably transformed various industries. Whether big or small players have been planning to incorporate AI and machine learning into their operations to get ahead of the fast-moving competitors.


Among all industries affected by AI, some figured out how to maximize the value of AI and take the leap of growth. Today, Sertis will take you through these 5 industries that can grow exponentially with AI.


If you are one of these 5 industries but haven't planned to implement AI yet, now is the perfect time to jump at the chance to increase your competitiveness. Or else, you will fall behind.


Start now with Sertis, one of Thailand's leading data and AI solution providers. Our experts are here, fully ready to help you customize your own AI and data solution that is right for your business. Let's grow exponentially together.



1. Retail

In 2021, the statistics showed that AI in retail generated 1,741 million dollars, and AI in retail market size will have expanded by 40.5 percent annually until 2030.


AI and machine learning play a vital role in businesses' data analytics and operation optimization by reducing cost, increasing accuracy in strategic planning, and creating better customer experiences on both online and offline platforms.


AI analyzes a large volume of data to improve the supply chain and predict customer demand using the Demand Forecasting solution. It can also provide personalized recommendations using the Customer Knowledge and Product Recommendation solutions. For the back office operations, it can help predict optimal stock and calculate ordering using the AI ordering solution, select product mix presented in each store using the Product Assortment solution, and monitor customers in-store using the Computer Vision solution.


Mentioned above are the uses of data analytics and AI in operational processes. Furthermore, AI can learn from data and automate analytics processes to provide real-time insight, replacing the manpower that used to be needed for this task.


Learn more about solutions for retails from Sertis: https://www.sertiscorp.com/retail



2. Food & Beverage


In 2021, the global AI in food and beverage was valued at 4.49 billion dollars and is expected to grow annually by 45.4 percent until 2029.


There has been a huge growth of AI in F&B because 30 percent of all food and beverages in the U.S. is discarded each year, costing 48.3 billion dollars, a huge loss of money that the F&B industry needs to bear. AI offers the benefits of reducing costs and increasing quality in F&B.


AI can be utilized to monitor and analyze customers' behaviors, e.g., tracking their footsteps and their choices in a physical store, together with their clicks on an online shopping platform. AI allows the F&B to understand their customer and develop new products that serve the needs in order to reduce the cost of a mistake. AI can also assist in improving the supply chain system by optimizing the production of products with limited shelf life, controlling quality and hygiene, and designing logistics plans to maintain the quality of products and expand the capability to serve customers' demands.


Learn more about solutions for F&B from Sertis: https://www.sertiscorp.com/fmcg



3. Logistics


McKinsey predicted that by 2030, AI will have transformed the logistics industry and developed a new-age logistics paradigm that surpasses human capabilities. Accenture also expected that by 2035, AI will have increased the productivity of the logistics industry by 40 percent.


AI has contributed to the 360-degree transformation of logistics using its intelligence in data analytics and prediction. AI skyrockets predictive analytics, improving inventory management and reducing cost. For example, AI predicts the optimal containers, selects the vehicles, and predicts routes and travel time to plan cost- and time-effective scheduling. AI can also forecast the offload and inspection time. Besides, computer vision can be leveraged to streamline the custom inspection process to avoid bottlenecks or delays at ports and reduce the costs of downtime.


AI can perform all these tasks by learning and getting training from data circulating in the industry. The ability ultimately leads to the escalation of the industry's growth.



4. Banking and Finance


It is expected that the value of AI in banking and finance will have reached 64.03 billion dollars by 2030 and has expanded at 32.6 percent each year since 2021.


AI has played a major role in digitizing traditional banking and innovating Fintech. For example, predictive analytics is deployed to generate more profits. It automates and increases accuracy in credit risk assessment and credit scoring using AI to analyze clients' data, including demographic data and behavioral data. AI is also utilized in fraud detection by deploying blockchain technology and machine learning to inspect suspected behaviors. Personalized solutions by AI can contribute to creating a better customer experience in the banking and finance industry, such as personalized financial product and service recommendations for individual clients.


These technologies maximize profits, optimize operations, and improve the security and trustworthiness of the banking and finance industry.



5. Energy


For the energy industry, it is forecasted that AI in the energy industry will generate a potential difference of 67.8 billion dollars during 2020-2025 and is expected to grow by 34.1 percent annually.


The major growth of AI in the energy sector is from AI and machine learning software in energy management and in building a smart grid. A smart grid utilizes the integration of AI and blockchain technologies to elevate energy management processes, e,g., electricity production, transmission, and distribution. Machine learning will provide real-time analytics to calculate and forecast electricity demand, and balance the demand and supply. AI will analyze and monitor the production processes to avoid failure and automate the processes to streamline the operation.


Juniper Research forecasted that a smart grid will have helped save an electricity cost of 14 billion dollars by 2022. The energy industry is one of the sectors that can make the most from AI and it is growing exponentially.


Learn more about Sertis Smart Energy Platform: https://www.sertiscorp.com/smart-energy-platform


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