Google Cloud: How Telco is Seeing ROI from Gen AI

The telco industry has holistically embraced Gen AI technology, with many companies already seeing tangible returns on their investments.

To evaluate this progress, a new global study that evaluated 282 senior telco leaders by Google Cloud, highlights the growing impact of Gen AI across telecom operations, from customer service to network optimisation.

The study shows that the adoption of Gen AI in the telco sector has been swift and widespread.

This surge in adoption reflects the industry's recognition of Gen AI's potential to transform operations and enhance customer experiences, so we take a look at the four key findings.

1. Over two-thirds of telecom firms have deployed Gen AI in production

Google Cloud reveals that 68% of telco companies surveyed have moved beyond experimentation and implemented Gen AI in real-world applications.

This adoption rate outpaces the global cross-industry average of 62%.

Deepika Adusumilli, Chief Data and AI Officer at BT Group, emphasises the importance of having "the key to taking the leap from testing to production successfully is having solid foundations in place to ensure that all gen AI use cases are effective from start to finish.”

The rapid increase in adoption is further evidenced by the fact that the number of operators actively pursuing or deploying Gen AI nearly doubled.

This momentum underscores the sector's commitment to harnessing the transformative power of Gen AI.

2. Majority of companies using Gen AI report positive returns

The study also found that 74% of telco firms with Gen AI in production are seeing a return on investment from at least one use case.

This high percentage indicates that the technology is delivering tangible benefits across various applications within the industry.

Simon Norton, Head of Digital Networks at Vodafone, emphasises the technology's potential across various areas: "Everything from how we plan our network investments—targeting them for customer experience, revenue growth, and churn reduction—all the way to how we optimise the network, excites me about the potential of Gen AI".

The diversity of Gen AI applications in telecoms is additionally notable.

Customer service remains one of the primary areas where the technology is being implemented, with AI-driven tools like Vodafone's 'SuperTOBi' chatbot becoming more sophisticated. 

These solutions handle complex customer queries and provide more tailored interactions, elevating the customer experience.

3. Significant productivity gains reported by nearly half of companies

Among telco companies reporting productivity improvements from Gen AI, 48% indicated that employee productivity at least doubled.

This substantial increase in efficiency demonstrates the technology's potential to transform work processes within the industry.

Hesham Fahmy, Chief Information Officer of TELUS, shared concrete results: "Results from an internal employee survey showed that team members are saving more than 40 minutes on average per interaction with gen AI.

“As adoption has ramped up over the past year, you can imagine the time and resource efficiencies we’re already seeing.”

These productivity gains are being realised across various areas of telecom operations.

For instance, Gen AI is powering responses to field technicians, creating network agents trained with thousands of manuals and technical documents.

This allows field techs to quickly access relevant information and resolve issues more efficiently.

4. Focus on operational efficiency and customer experience

Google Cloud further revealed that telco companies are prioritising two key areas for Gen AI investment: improving internal operations (46% of respondents) and enhancing customer experiences (45% of respondents).

Vikram Sinha, President Director and Chief Executive Officer at Indosat Ooredoo Hutchison, explained how Gen AI is transforming customer service: "Gen AI solutions can equip call centre staff with gen AI tools to enhance their productivity and effectiveness.

“Specifically, these tools can provide live call transcription; recommended responses derived from knowledge bases; real-time conversation analysis; and post-call sentiment analysis, leading to faster, more accurate, and more effective resolution of customer queries".

However, despite the impressive progress, challenges remain in scaling Gen AI projects.

Data privacy (83%) and data security (80%) are significant concerns for telecom companies. Additionally, ethical implications (60%) and the availability of in-house talent and skills (54%) present barriers to wider adoption.

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