INSIGHTS
Scaling Gen AI in the Telco Industry
Altman Solon is the largest global TMT consulting firm with expertise in telecommunications consulting. In the following insight, we share findings from a survey conducted in collaboration with Kyndryl and sponsored by Google Cloud Platform. The survey sheds light on scaling generative AI solutions in telecommunications.
In the two years since the breakthrough of generative AI, the telecommunications industry has faced challenges in adopting and implementing this transformative technology.
For better insight into the industry’s progress with generative AI and to better understand relevant use cases, Altman Solon partnered with Kyndryl and Google Cloud Platform on a survey of over 100 senior business leaders from tier one and two communication services providers (CSP) across the U.S., Europe, and Asia. We also conducted interviews with 14 industry experts.
Our results identified several opportunities that telcos can harness from generative AI, including more efficient network operations and reduced workloads for agents. Companies also shared their challenges: some struggled to implement generative AI due to internal roadblocks, and others reported rapid cost escalations. These insights are timely; while the adoption of generative AI is high amongst telcos, only 30% are currently in production.
Additionally, our research revealed four audience segments that we grouped by behavior, proficiency, and prioritization of generative AI. These include:
- “Broad Experimenters”: Large CSPs leading generative AI adoption with high success rates and high spend
- “Cautious and Focused”: Companies achieving success through a highly focused implementation
- “Hesitant Adopters”: Somewhat immature adopters facing low success rates and few cases in production
- “Catching Up”: The most immature adopters with few use cases that are generally struggling to scale
The two groups reporting best outcomes are “Broad Experimenters” and “Cautious and Focused.” They used contrasting approaches with generative AI. "Broad Experimenters" took risks in many areas. In contrast, "Cautious and Focused" used targeted methods with close supervision.
The following infographic is a snapshot of the results and key insights from our comprehensive study.
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Thank you to Kyndryl for their contributions to this report.