USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN 1C

USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN 1C

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IT-Технологии

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41

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Журнал «Научный лидер» выпуск # 23 (173), Июнь ‘24

Дата публикации 16.06.2024

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В этой статье всесторонне рассматривается использование искусственного интеллекта (ИИ) и машинного обучения (ML) на платформе 1С. После описания фундаментальных возможностей и преимуществ этих технологий мы приведем конкретные примеры их практического применения в различных сферах бизнеса.

Introduction

The rapid development of AI and ML is transforming all aspects of our lives.

The 1C platform, keeping up with the times, integrates these technologies, offering its users a wide range of tools and ready-made solutions for their implementation.

Main capabilities of AI and ML in 1C:

1C allows you to use AI and ML to solve a wide range of problems:

Data analysis:

Demand Forecasting: Analyzing historical sales data allows you to accurately predict future demand for goods or services, optimizing inventory and production.

Uncover patterns: Analyze large amounts of data about customers, transactions, and other business processes to uncover hidden patterns and optimize business strategies.

Customer Segmentation: Based on the analysis of customer behavior and preferences, they can be effectively divided into segments for targeted marketing and increased sales.

Automation of tasks:

Document processing: Automatic recognition and extraction of data from source documents such as invoices, invoices, etc., reducing time and minimizing errors.

Data entry: voice speech recognition or automatic form filling to speed up routine operations.

Chatbots: creating virtual assistants to support customers 24/7, answer questions and collect information.

Personalization:

Recommendations: analysis of customer purchase history and preferences allows you to highly accurately recommend products or services that may be of interest to them.

Targeted Marketing: Create personalized advertising campaigns and offers for maximum effectiveness.

Pattern recognition:

Image analysis: identifying product defects, analyzing images from CCTV cameras, recognizing faces and objects.

Text processing: Analyze customer reviews, social media, and other text data to extract valuable information.

Forecasting:

Equipment failure prediction: analysis of equipment operation data allows you to predict equipment failures to carry out timely maintenance and minimize downtime.

Risk Forecasting: Analyzing financial data and other factors allows you to predict financial risks and make informed decisions.

Advantages of using AI and ML in 1C

The introduction of AI and ML in 1C provides a number of significant advantages:

Increased efficiency: automation of routine tasks, deep data analysis and accurate forecasting allow you to optimize business processes and significantly increase productivity.

Reduced costs: Reducing routine operations, optimizing the use of resources and preventing errors lead to significant cost reductions.

Increased competitiveness:

Application of AI and ML in 1C: practical examples

1. Sales scope:

Demand Forecasting: Analyzing historical sales data allows you to predict demand for products with high accuracy, which optimizes inventory, reduces costs and increases product availability for customers.

Personalization of offers: based on the analysis of customer purchase history and preferences, the system can recommend products that may interest them, which increases sales and increases customer loyalty.

Targeted Marketing: With the help of AI and ML, customer segments can be created and marketing campaigns can be developed, thereby increasing their effectiveness.

Analysis of the effectiveness of advertising campaigns: AI allows you to track the performance of various advertising channels and optimize their use to achieve maximum impact.

2. Customer service scope:

Virtual assistants: AI-powered chatbots can answer customer questions, provide support, and solve simple problems 24/7, freeing up employees' time for more complex tasks.

Customer Feedback Analysis: Using AI, you can automatically analyze customer feedback on social media, review sites, and other sources to identify problems, improve customer service, and increase customer loyalty.

Personalized service: Based on customer history and preferences, the system can offer them personalized problem solving and service options.

3. Scope of production:

Equipment failure prediction: analysis of equipment operation data allows you to predict equipment failures to carry out timely maintenance and minimize downtime.

Optimization of production processes: AI can analyze data on the operation of machines, conveyor lines and other elements of the production system to identify bottlenecks and optimize their operation.

Product quality control: With the help of AI-based machine vision systems, product defects can be automatically identified at various stages of production.

4. Accounting and financial reporting:

Automatic document recognition: AI can automatically recognize and extract data from source documents such as invoices, invoices and acts, which significantly speeds up information processing and reduces the risk of errors.

Reduce routine tasks: AI can automate tasks such as generating payment orders, maintaining a cash book, and preparing financial statements.

Reduce the risk of errors: AI can check accounting entries for compliance with legislation and identify potential errors.

Conclusion

The use of AI and ML in 1C opens up wide opportunities

for business, allowing you to increase efficiency, reduce costs, improve the quality of customer service and embrace competitive advantage.

It is important to note that for the successful implementation of these technologies, it is necessary to carefully prepare the infrastructure, train personnel and select suitable solutions that meet the specifics of the business.

In this article, we looked at just a few of the many examples of using AI and ML in 1C. As these technologies develop, their potential for business will only increase.

Список литературы

  1. Технологии искусственного интеллекта. URL: https://its.1c.ru/db/mdm25#content:184:hdoc, (дата обращения: 10.04.2024)
  2. Беляев, А. А., & Петров, И. В. (2021). Применение искусственного интеллекта для автоматизации бизнес-процессов в 1С: Предприятие. Информационные технологии в образовании, 2021(12), 112-119. DOI: 10.30323/1728-9171.2021.12.112 (дата обращения: 10.04.2024)
  3. Гусев, А. Н., & Кузнецов, М. В. (2019). Использование машинного обучения для анализа данных в 1С: Предприятие. URL: http://jmlda.org/papers/doc/2014/JMLDA2014no8.pdf, свободный (дата обращения: 12.04.2024)
  4. Л.Э. Мамедова, Л.Н. Иванова, Е.С. Алтаев Основные аспекты технологии искусственного интеллекта // Режим доступа: https://cyberleninka.ru/article/n/osnovnye-aspekty-tehnologii-iskusstvennogo-intellekta, свободный – (дата обращения: 13.04.2023)
  5. Filippo Santoni de Sio, Giulio Mecacci Four Responsibility Gaps with Artifcial Intelligence: Why they Matter and How to Address them // Springer Link, 14 may 2021. Режим доступа: https://link.springer.com/article/10.1007/s13347-021-00450-x – (дата обращения: 15.04.2023)
  6. Melanie Arntz, Terry Gregory, Ulrich Zierahn The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis // Режим доступа: https://www.researchgate.net/publication/303311529_The_Risk_of_Automation_for_Jobs_in_OECD_Countries_A_Comparative_Analysis, свободный. – (дата обращения: 15.04.2024)
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