AI Revolution In Telecommunication Training Ppt

Slide 1

This slide discusses the importance of Artificial Intelligence in the telecommunications industry. Telcos face several new issues when market conditions shift, such as new predictive models required and the regularity with which they need to be updated. Hence, the adoption of AI technologies becomes important as they increase productivity without sacrificing accuracy.

Slide 2

This slide talks about predictive maintenance that AI enables. Maintaining a network becomes more challenging as it develops and becomes more sophisticated. Fixing problems can be a time-consuming and an expensive procedure. When it comes to predictive maintenance, AI can make a significant difference.

Slide 3

This slide discusses Network Optimization as a use of Artificial Intelligence in Telecom. Building Self-Optimizing Networks (SONs) is another popular application of AI in telecommunications. AI algorithms monitor such networks and can detect and accurately forecast network anomalies.

Instructor’s Notes: According to IDC, companies are increasingly prepared to invest in AI as they recognize the value of deploying it in telecommunication network architecture. Over 63 per cent of telecom businesses are integrating AI to improve their network infrastructure.

Slide 4

This slide highlights the advantage of fraud detection and prevention as a result of incorporation of Artificial Intelligence in Telecom. The capacity to avoid fraud is the most significant benefit of AI-powered fraud analytics. 

Instructor’s Notes: When the system identifies a suspicious activity, it disables the related user or service, preventing the fraud from taking place. All of this is done automatically; organisations can, thus, effectively respond to an attack in a timely manner.

Slide 5

This slide introduces RPA and depicts its market size for the time period 2021-2023. RPA is a technology that combines software robotics/tools and Artificial Intelligence to partially or fully automate human activities for business processes.

Instructor’s Notes: Telcos can use RPA to automate data input, order processing, billing, and other back-office tasks that take time and require a lot of manual labor. This frees up time for employees, allowing them to focus on other important duties, and minimizes the number of errors associated with physical work. 

Slide 6

This slide illustrates the global market size of Artificial Intelligence in the Telecommunications Sector. The global AI in telecommunications industry is estimated to reach a staggering $14.99 billion by 2027.

Slide 7

This slide illustrates the most common challenges in implementing Artificial Intelligence. Even though the worldwide AI in the telecommunications market is expanding, many firms are still having difficulty deploying it.

Slide 8

This slide discusses the problem of unstructured or incomplete data. It's pointless to implement an AI system without access to relevant data. Many businesses struggle with data collecting due to issues of fragmented data, unstructured data, and incomplete data.

Instructor’s Notes: 

• Fragmented data: Different systems collect and store data, but there is no single unified database from which it can be retrieved
• Unstructured data: Any AI system will struggle to make sense of a large amount of uncategorized data with no context or explanation of what it is connected to
• Incomplete data: Using data with missing components can cause the AI system to learn inconsistently or inaccurately
• Solution - Big Data Engineering Ecosystem: As AI algorithms demand clean, well-structured data, ETL (extracting, transforming, loading) and data cleanup take up about 80% of any ML project's effort. As a result, it's critical to set up a big data engineering ecosystem (based on Apache, Hadoop or Spark) that can collect, integrate, store, and analyze data from siloed data sources

Slide 9 

This slide talks about the technical experience required in the deployment of Artificial Intelligence in Telecom. Artificial Intelligence (AI) is a relatively new technology. Building an in-house team might take longer and produce a negligible impact when local talent is scarce

Instructor’s Notes: Finding a vendor with the ability and experience to properly construct an AI system can be a task in itself. Furthermore, because deploying AI can be costly, it is critical to begin your project with the proper partner.

Slide 10

This slide talks about the importance of technical integration in an AI project, as the use of outdated legacy systems is one of the main reasons why a project might fail. The ability of the IT infrastructure can be ensured the creation of a consolidated database, using data lakes or cloud computing, etc.