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Top 7 Use Cases for RPA Telecom in 2024

Written by
Cem Dilmegani
Cem Dilmegani
Cem Dilmegani

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

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According to Deloitte’s 2022 report, the telecom industry is facing multiple challenges with the rise of 5G technology. These challenges range from rising competition among service providers to novel threats relevant to the novel 5G technology. 

In this article, we explore how RPA telecom can intervene to tackle rising challenges by solving simple customer service issues, automating data processes, and mitigating cybersecurity risks. And select RPA vendors allow telecom operators to experience these benefits in a test environment before making a financial commitment.

Explore RPA ecosystem by comparing top RPA tools and exploring some cost effective RPA solutions such as: no-code RPA, open-source RPA & Python RPA tools & libraries.

1. Automate data processes

RPA bots are programmed to replicate human interactions with GUI elements, making them a great candidate to automate data processes in telecommunication, including:

  • Transforming unstructured data (e.g. invoice PDFs, handwritten site reports) into structured and machine readable data using OCR and NLP.
  • Updating relevant databases with data from emails, invoices, and reports, such as network usage by user, server logs, and last network maintenance record.
  • Performing extract, transform, and load (ETL) processes and maintaining an audit trail of data transfers.
  • Cross-checking data against different sources and cleaning it from duplicates and errors.

2. Provide self-service options to clients

A 2020 survey reports that unassisted customer service portals are increasing in popularity among telecom service providers as ~69% of telecom customers attempt to resolve their own technical issues before reaching out to the service provider. Additionally, customers who attempt but fail to resolve their issues before having a technician visit rate their satisfaction 16 points less on a 1000 point scale.

RPA bots provide a 24/7 available self-service portal to customers, as they can:

  • Collect information about the customer’s inquiry
  • Fetch data about the problem from relevant databases and troubleshooting documentations
  • Generate a step-by-step guide to solve the customer’s problem and communicate it to the customer either via a chatbot or via email
  • Generate a report about the customer’s inquiry and upload it to the ticketing system.

3. Help agents tackle First Call Resolution (FCR)

First Call Resolution (FCR) issues are problems reported by customers to customer service employees via emails, texts, or calls, which can be tackled by guiding the customer through troubleshooting steps.

RPA bots can help customer service agents enhance their productivity and increase the speed of the FCR by:

  • Fetching data about the problem from the relevant troubleshooting document and presenting it to the agent.
  • Notifying the agent about the customer’s demographics (location, past purchases, currently used services, past service towers near them) to enhance the customer’s experience.
  • Upload the relevant FCR data to the ticketing system.

See our article on RPA use cases in customer service to learn more.

4. Monitor networks and servers

According to a Nokia report, network traffic grows 30-45% each year, increasing the pressure on service providers to ensure that their infrastructure is sufficient. 

RPA bots can significantly reduce the amount of manual work required in network monitoring by:

  • Generating timely network usage reports by collecting data from relevant servers and IoT devices. 
  • Sending notifications to relevant employees if incidents or downtimes are detected.
  • Performing regular diagnostics on server performance to ensure correct and stable server connections. 

Data generated by RPA bot reports can be used to further analyze network performance in order to optimize networking and integration strategies. 

5. Detect security threats

Deloitte claims that telecom companies are a big target for cyber threats because they control critical national and international infrastructure, and maintain a significant amount of customers’ private data (e.g. phone number, address). And with the rising cost of cyberattacks and data breaches (up to $4M per breach) it is important to mitigate these risks to avoid tarnishing the brand’s reputation and facing lawsuits (see Figure 1). 

RPA bots can help telecom service providers avoid cyber threats by:

  • Automating privileged data management
  • Automating software updates and patch downloads
  • Detecting unauthorized access and reporting it to specialized employees
  • Running cyber threat hunts and penetration tests
  • Detecting malware and virus attacks by leveraging NLP to detect malicious language in received emails and links.

See our article on RPA use cases in cybersecurity to explore these cases in detail.

Figure 1: Impacts of cyberattacks on businesses

Image shows the short and long term effects of cyberattacks. One of the RPA use cases in telecom is improving security measures.
Figure 1: Short & Long term costs of cyberattack

6. Ensure compliance

The telecom industry is governed by standards that ensure consumer privacy and welfare. These standards and regulations are constantly being updated to match the emerging technological advances such as 5G, AI, and IoT. Therefore, it is important for telecom organizations to stay up to date about the regulations to ensure that their internal policies comply with the regulatory changes.

RPA can tackle several compliance related challenges by:

  • Automating data processes, thus minimizing data errors
  • Creating audit trails to monitor user activity
  • Cross-checking process logs against policies
  • Scraping regulating websites to notify compliance and audit personnel about policy modifications and regulatory updates.

See our article on compliance automation to explore RPA use cases and benefits for compliance.

7. Competitor analysis

Telecom is a fast growing industry with many emerging companies trying to join the marketplace. Keeping tabs on competitors’ offerings, unique product features, and customers’ reviews enables businesses to gain insight about market trends, and optimize their products and strategies accordingly.

RPA bots can help telecom business leaders analyze the market and their competitors by:

An alternative to RPA solution, businesses can leverage web scraping tools that automate data extraction from web pages in a timely manner, and send it to the user in the designated format.

Explore competitor monitoring automation in more details.

For Telecom providers that struggle with choosing a customizable RPA tool, we recommend checking Python RPA. Python RPA libraries and Python RPA tools can deliver flexibility and adaptability to implement RPA in Telecom.

For more on RPA

Explore different RPA use cases to understand how to implement it in your business:

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If you are looking for an RPA solution that fits your business needs, shortlist your options by checking our data-driven list of RPA vendors and hub of automation solutions.

And we can guide you through the process:

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This article was drafted by former AIMultiple industry analyst Alamira Jouman Hajjar.

Cem Dilmegani
Principal Analyst

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

Sources: Traffic Analytics, Ranking & Audience, Similarweb.
Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics, Business Insider.
Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are, Washington Post.
Data management barriers to AI success, Deloitte.
Empowering AI Leadership: AI C-Suite Toolkit, World Economic Forum.
Science, Research and Innovation Performance of the EU, European Commission.
Public-sector digitization: The trillion-dollar challenge, McKinsey & Company.
Hypatos gets $11.8M for a deep learning approach to document processing, TechCrunch.
We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million, Business Insider.

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