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AI in Telecoms: Impact and Opportunities - Key Takeaways from the Webinar

Webinar

AI in Telecoms: Impact and Opportunities - Key Takeaways from the Webinar

The telecoms sector has moved beyond AI trials and is now integrating it into everyday operations. In this webinar recording, experts explore how AI is enabling predictive, data-driven decision-making, improving efficiency, and supporting smarter, more proactive network management.

Author: Jean Donan-Olliero, Principal Consultant at FarrPoint

Updated 7 November 2025

7 key takeaways from the AI in Telecoms webinar

1. The telecoms sector has moved beyond the AI hype.

AI in telecoms is no longer at the proof-of-concept stage. Many organisations have been experimenting with AI and machine learning for over a decade, particularly in areas like customer management, predictive maintenance, and service automation. The current wave of innovation is about broadening access and integrating AI into everyday processes, enabling wider teams to use AI safely and effectively.

2. Most telecoms carriers are not yet ready to deploy self-healing networks.

While self-managing and self-healing networks are technically possible, most operators still want a human in the loop to maintain oversight and responsibility for decisions made by AI systems. The consensus is that AI should assist, not replace, human judgment, especially in mission-critical environments.

3. Data and integration are key when it comes to AI in telecoms.

One of the biggest challenges isn’t the AI itself, but how it connects to the wider ecosystem. Telecom operators need to ensure AI systems can access and interpret data across multiple platforms, not just within siloed systems. Real value comes from using AI to link data, predict issues before they happen, and suggest actions or next steps.

4. There’s a shift towards proactive, predictive telecoms operations.

AI is already helping the sector move from reactive maintenance to predictive and proactive operations, facilitating root-cause analysis or highlighting capacity issues before they impact customers. This shift also supports more agile, data-driven decision-making, helping telcos respond faster to the evolving demands of modern digital networks.

5. AI is not a magic wand, so groundwork is essential.

AI’s introduction must be done gradually with strong foundations: data sources and APIs in particular must be of high quality to allow automation from AI agents and deliver value. The recommendation is to first introduce AI in response to current issues in the business and build on it.

6. AI is an enabler of smarter work.

Rather than focusing on job replacement, AI is best used to augment human capability. It can take over repetitive, data-heavy tasks such as analysing network performance or triaging common customer queries, allowing skilled professionals to focus on more complex and value-adding activities.

7. Every introduction of AI in the business must be done with ROI in mind.

There is no wishful introduction of technology without clear financial benefits.

Watch the webinar recording below

The panel of experts

(this will open in a new window)Jaime Tatis, Senior Vice-President and Chief AI Officer, TELUS

(this will open in a new window)Pavelas Sokolovas, Head of Networks, Trooli

(this will open in a new window)Roddy Alexander, Enterprise Account Executive for Cloud Networks, Salesforce

(this will open in a new window)Denham Pearce, Solutions Engineer - Innovation and Enablement, Cisco

Moderator(this will open in a new window)Jean-Donan Olliero, Principal Consultant at FarrPoint

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