Updated on February 12, 2025

The global market for generative AI especially AI chatbots in telecom was worth $302.34 million in 2024 and grew to $428.08 million in 2025. By 2034, the market is expected to grow to $9780.87 million, at 41.59% annually.
So, why has the telecom industry adopted generative AI at such a fast rate?
One of the key reasons is the unpredictable volatility in telecom customer support. For example, in Canada, customer complaints for telecom operators grew by 38% in 2024. The customer complaints against Rogers, Canada’s largest wireless and cable company, grew by 68%.

Customer service across telecom has been a persistent issue. 46% of telecom industry customers have changed their providers in the last year after a bad customer service experience. And the industry sees an average churn rate of 30-35% (compared to 15% in other retail sectors).
This earmarks a pressing problem in the industry and also showcases why generative AI has been such a hit for them. But what promise does generative AI hold for the telecom ecosystem?
In this article, we will talk about generative AI chatbots in telecom industry and their importance. We’ll cover:
1. Why Use Generative AI Chatbot for Telecom Customer Support?
2. What are the Benefits of AI Customer Support in Telecommunications?
3. How are Telecom Companies Approaching Customer Support?
4. What are the Challenges in Adopting AI for Telecom Customer Support?
5. Conclusion
Why Use Generative AI Chatbot for Telecom Customer Support?

In 2023, IBM surveyed 12 industries to understand how conversational AI had helped them with customer support. 97% of telecom industry executives reported CSAT score improvements after using AI in customer support.
This productivity and performance increase is mirrored in a McKinsey report. Researchers from the company outline that generative AI will boost the telecom industry’s revenue by $60-100 billion. The telecom industry is uniquely placed to gain a competitive edge from generative AI, and there are some specific reasons –
1. Multiple Mergers & Acquisitions – The telecommunications industry has been consolidated over the past few years. This has made a unified customer service and success approach difficult for many players.
2. Growth in Connectivity – Global communication service providers (CSPs) are seeing a massive spike in demand for internet services. Uninterrupted internet service is a table stakes for a new generation that consumes a lot of digital media. This makes providing at-scale customer service difficult.
3. Growing Customer Expectations – While CSPs have taken a one-size-fits-all approach to customer service, modern customers demand more personalized customer service for growth.
4. EBITDA Decrease – The rising cost of debt financing and raw materials squeezes the EBITDA margins for significant CSPs. In 2022, the industry saw its EBITDA shrink by 1.5%. Cost efficiency and optimization are needed even as the customer base expands.
The telecommunications industry is navigating a delicate balancing act: meeting customer expectations and demand while streamlining operations to drive cost efficiency and managing the challenges of mergers and acquisitions.

As Andres Irlando, the President of Zayo Group, says in his article for Forbes, “Telecom providers can no longer afford to be one-dimensional; they must become more customer-centric and meet customers wherever they are if companies hope to retain them.”
These conditions have made it crucial for telecoms to adopt generative AI at an advanced pace. And they’ve been some of the first beneficiaries of the benefits of this approach.

Let’s discuss the benefits of AI-first customer service in telecom.
What are the Benefits of AI Customer Support in Telecommunications?

Mckinsey researchers estimate that the productivity of customer support functions can be increased by 30-45% by incorporating generative AI chatbots in telecom industry. This is because generative AI adds a competitive edge to customer support. It provides.
1. 24/7 Availability – Given the different work schedules and increased digital media consumption, 24/7 connectivity is the top priority for telecommunications. As a result, any service disruption can lead to a spike in customer service tickets. AI chatbots for telecom, available at all hours, can provide this support on a large scale.
Modern AI ticketing systems also triage these requests, helping agents solve business-critical problems first.
2. Increased First Contact Resolution – AI chatbots can accurately answer repetitive questions from customers, increasing the rate of first contact resolution for telcos. Telecom chatbots can answer inquiries about subscription plans, future maintenance hours, and payment statuses, freeing up human agents for more critical issues.
3. Personalization at Scale – One of the primary problems in chatbots for telecom is personalization. Since the use base is vast, maintaining personalization isn’t possible through a human workforce. However, AI chatbots can manage a considerable amount of data simultaneously and provide personalized service to customers. For example – An AI can look at your CRM and give customers insights into how they might face low internet connectivity due to adverse weather conditions.
4. Cost Efficiency – An increase in productivity also translates to reduced costs. According to estimates, AI could increase the productivity of an individual agent by 30-45% without incurring an increase in overall costs.
5. Improved Accuracy – An agent must consult pre-made templates, the knowledge base, or SOPs to find the specific answer to customer questions. An AI does the same, but the search operations are accurate and instantaneous. This allows the AI to provide more precise answers to your customers.
6. Multilingual Support – One of the inherent complexities in expanding a telecom company is the requirement for multilingual expertise. AI agents can overcome this quickly. Most AI agents can answer in multiple languages (Kommunicate has a generative AI chatbot that can converse in 130 languages). Generative AI can also create an AI assistant that translates the conversation between your agents and customers.
These capabilities are central to AI-first customer support and provide a substantial competitive edge to CSPs. Essentially, generative AI helps telecom companies with the ability to answer repetitive customer questions accurately and at scale. This translates to higher CSAT scores and more retention.
Telecom companies have been adopting generative AI chatbots quickly since the ChatGPT launch. And we’ve already seen some great results. Let’s discuss how AI advances generate real-world results.
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How are Telecom Companies Approaching Customer Support?
Telecom industries are using generative AI chatbots to improve customer support efficiency and meet customer demands. One of the best improvements we’ve seen firsthand is that of TelOne, one of the leading CSPs in Zimbabwe.
TelOne – Scaling Support with Gen AI and WhatsApp

Africa is getting more connected than ever before. When we first met the TelOne executives, Zimbabwe had added over 9 million active internet subscriptions in just a year, and the pressure on their customer service executives was at a breaking point.
With the increasing pressure to provide data plans and seamless support, TelOne adopted WhatsApp as its main channel.
However, only 20 customer service representatives couldn’t handle the influx of messages on the platform. So, they connected their Dialogflow bot with Kommunicate.
Here are the results:
- Five of their agents shifted to handle complex queries from the self-service portal using the bot-human handoff feature.
- 90% of the customers started directly interacting with the chatbot.
- The chatbot started having over 20,000 unique customer conversations each month.
This led to an increase in CSAT, and they could increase their productivity without investing additional human capital. TelOne senior developer Ryan Tapfumaneyi praised our generative AI chatbots: ‘If you are looking to automate your business processes, Kommunicate is the way to go.’”
Elisa – Handling 70% of Inbound Customer Questions with Generative AI.

Elisa is a major telecommunications company that serves North Europe. Due to the wide geographical presence, the number of customer service queries is also significant. Elisa receives around 100,000 inbound requests per month across all channels.
Since this demand kept increasing, Elisa implemented a generative AI-based chatbot solution. This lead to immediate results:
- Up to 70% of inbound conversations started with the chatbot.
- Conversations were resolved with 42% FCR.
- The bot entirely handled 34% of incoming calls.
- The chatbot achieved an NPS score of 30.
While outlining the pre-AI era of Elisa, Mailiis Ploomann, the Head of Telecom Services at the company, said, “The most important thing for any telecom company is to be there for your customer exactly when they need a solution, whatever question or problem they may have.”
Post-AI, Mailiis estimated that they were saving 1 minute per customer conversation, increasing their productivity by several factors.
As you can see, companies that have adopted generative AI-based customer service in telecom have seen outsized benefits. However, AI isn’t all peaches and roses, and we’ll be misplaced if we don’t outline the risks in the next section.

What are the Challenges in Adopting AI for Telecom Customer Support?
92% of telecom executives plan to adopt generative AI customer support chatbots into their workflows. And while we’ve talked about the multiple benefits of generative AI adoption, there are some risks, too. Specifically, these are:
1. Data Security – CSPs always handle sensitive data. So, the AI providers they use must be strict about data security and avoid any leakage of PII information. We recommend enterprises choose AI providers with up-to-date security certifications and a spotless track record.
2. Multilingual – While most AI models can converse in multiple languages, they are not proficient. For example – ChatGPT is great at understanding English but struggles with Thai.
These linguistic differences have caused an adoption lag in the APAC and MENA regions. To combat this, choose AI providers who have tuned their chatbots to interact in multiple languages and have some expertise in your language.
3. Integration with Legacy Systems – Legacy systems were built as monoliths that handle all aspects of communications. This makes it challenging to integrate these systems with AI. To solve this, choose vendors with experience setting up no-code native integrations with legacy systems.
4. User Trust and Transparency – A KPMG study revealed that AI might decrease customers’ purchase intentions. It’s essential to create transparent AI conversations that show when AI is being used to answer a customer question.
5. Cost of Customization and Maintenance – While AI is an economical way to increase customer support productivity, overage pricing, and maintenance charges might make the overall product expensive. Choose vendors that employ transparent pricing and have a clear SLA for their products.
Telecom operators are going to adopt generative AI. However, it’s necessary to understand the common risks with the technology. Having solutions and awareness of them will speed up the adoption process and help telcos meet customer expectations.
Parting Thoughts
The telecommunications industry is adopting generative AI at a faster pace than ever. As customer expectations increase and operations become more complex, AI-powered chatbots have become a lifeline for the sector.
While challenges like data security, multilingual gaps, and legacy system integration persist, proactive partnerships with trusted AI providers can make the process efficient and more manageable.
From TelOne’s WhatsApp-driven success in Zimbabwe to Elisa’s 70% automation rate in Europe, early innovators in the sector prove that generative AI isn’t just a trend—it’s the future of telecom customer support.
Ready to unlock the potential of generative AI for your telecom business? Talk to Us!
As the Head of Growth, Marketing & Sales, Yogesh is a dynamic and results-driven leader with over 10+ years of experience in strategic marketing, sales, and business development.