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AI For Your Business: Exploring Current Use Cases of AI In Wholesale Telecoms

Picture of Lejla Pljevljak-Rašidagić

Lejla Pljevljak-Rašidagić

Chief Product Officer

From ChatGPT to self-driving cars, AI has been making headlines for many years – and rightfully so. AI has the ability to revolutionize industries.

However, as Lejla Pljevljak-Rašidagić, the Chief Product Officer at ZIRA, explains, AI’s existing use cases in wholesale telecoms have yet to reach the technology’s full potential.

Read this article for the best of AI in telecoms that is yet to come.

The state of AI in telecoms

The communications industry has recently experienced an AI frenzy, with many companies announcing AI-enhanced products or AI integrations into their existing portfolio. According to NVIDIA’s recent survey, as many as 89% of telecoms companies are assessing or already implementing AI in their business. And this is just the beginning: research predicts that AI in telecommunications will be worth more than $10 billion by 2030.
There are good reasons behind CSPs’ interest in AI. When implemented correctly, it promises significant benefits. Let’s take a look at CSPs’ progress so far in implementing these into their operations.

State of AI in telecommunications:
2024 Trends

AI use cases: useful, but uninspired

Seeing the vast benefits of AI in the industry, it would be reasonable to expect that companies include it in every business area possible. However, so far, we have seen the majority of use cases converge in just a handful of key areas.

Customer experience

The highest number of AI use cases have revolved around customer experience. Indeed, this is one of the easiest ways of implementing AI into any business for a relatively fast pay-off and without any disturbance to your operations.
 
The numbers back this up: a 2023 survey by TM Forum found that 92% of operators already have a GenAI-enhanced chatbot in place to improve customer experience. Research by McKinsey gives further evidence of the positive effects of AI in CX, claiming that it can identify opportunities to reduce capital expenditure by up to 10% and generate an up to 15% increase in sales conversion.
 
It is obvious that AI can transform customer experience in telecoms for the better. However, the advantages of using it to enhance chatbots are not unique to the industry. Confining the use of AI to customer experience greatly limits its potential, when there are many more powerful use cases for it in the industry.

Network optimization

AI also lends itself well to improving CSPs’ network management methods. With its predictive capabilities, AI is well-equipped to optimize network operations and help CSPs anticipate maintenance needs, allowing them to reduce downtime and ensure seamless service.

Fraud detection

With telecom fraud continually on the rise, CSPs are investing in new and improved security solutions. Many are employing AI to enhance their fraud detection capabilities, which can be extremely helpful, especially amongst the rising number of Artificially Inflated Traffic (AIT) attacks.
 
Plus, as the number of fraudsters using generative AI tools to gain money grows, CSPs are also considering ways to recruit AI to protect themselves.

Automating business processes

For many years, CSPs have been using automation to accelerate everyday business processes within billing or customer onboarding. Now, AI can provide further support by managing the process end to end, liberating resources, and allowing CSPs to focus on more innovative tasks.

Improving marketing campaigns

AI also lends itself well to improving CSPs’ network management methods. With its predictive capabilities, AI is well-equipped to optimize network operations and help CSPs anticipate maintenance needs, allowing them to reduce downtime and ensure seamless service.

The future of AI in wholesale telecoms

The use cases we have listed can add real value to any organization in telecommunications. However, they don’t take into account the unique way in which data is used in the industry.

CSPs can greatly benefit from predicting changed in their circumstances and seeing how they might affect their business. Actionable insights can support decision-making and allow CSPs to enhance their business while minimizing risks. Outside of network optimization, no existing use case provides support for this. ZIRA is working hard to change this.

Discover ZIRA’s new product

Time series forecasting is one of the most impactful ways in which AI can be helpful to CSPs’ day-to-day operations and overall success. So far, this has been an almost completely unexplored area for AI implementation – and surprisingly so, considering how important it is for CSPs to understand data fluctuations such as changing supplier prices and international traffic, and how they will impact their interconnect business.

At ZIRA, we understand the specific needs of CSPs, which is why we have developed a brand-new, industry-first product that uses AI to analyze and forecast data in supplier prices, traffic, routing, profitability, and more.

In our next blog, we will explore how our AI product can support trading and routing management, allowing CSPs to optimize costs and retain their competitive edge. Stay tuned to learn more.

Solving the rate-decision disconnect with Trading & Routing Management

We will unveil our new product at DTW Ignite Copenhagen, held between 18-20 June. Joining the conference?

Follow us on LinkedIn to stay up to date with product updates.

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