The AI telecom race is gaining strength in 2025 with innovations redefining industries, including telecoms, with key technologies like large language models (LLMs) and Agentic AI are the drivers of the transformation that will push telecom providers to innovate if they want to truly lead in this new era of connectivity between telcos and AI.
China’s DeepSeek achieved never-experience-before success back in January, with its R1 model that not only surpassed OpenAI’s top models but also outperformed it cost wise, proving that AI and telecom integration can succeed without relying on expensive hardware.
DeepSeek developed a source-efficient, independent-learning AI using reinforcement learning. Even though the Chinese gen-AI company could not use high-end Nvidia GPUs – due to sanctions imposed by the US – its success in time of crisis showed that creating advanced AI no longer depends on the most sophisticated hardware, changing standards in developing AI.
AI innovation in telecom no longer hinges on the latest chips to deliver powerful, affordable solutions. As the future of AI in telecom business unfolds, businesses must embrace technologies that maximize capability and efficiency without relying on the most expensive infrastructure.
The Next AI Powerhouse
Following Deepseek’s success, a new player entered the AI arena, Manus AI – AI agent that uses several models under the hood to automate tasks, make decisions, and reason in real-world situations.
Manus outperforms OpenAI’s O1 and DeepSeek’s R1 in areas like logical reasoning and multi-modal inputs and plans to open-source its agent in late 2025, potentially shaking up the market.
The collab between Manus AI and Alibaba’s Qwen AI will leverage Alibaba’s open-source infrastructure. With this AI telecom collaboration having the needed man and machine power to minimize costs and widen Manu AI’s adoption, it will offer developers and telecommunication companies alike the needed access to create more advanced AI solutions.
Future of AI In Telecom Industry
Telecom operators are still wary of adopting AI completely, with 39% go for supervised automation, while another 39% prefer AI-augmented manual operation, according to a Telecoms.com survey. Problems such as cost, trust and unavailability of specialist skills are hindering generative AI for telecom adoption.
But hope is not lost as AI can transform telcos. AT&T’s GenAI platform has already reduced software development time and optimized customer service efficiency, with some telecom and AI solutions promise lower operational costs, customer personalization, and enhance productivity across the sector.
For telecommunication operators, adopting AI is now a fundamental need, with companies like DeepSeek and Manus AI reconstructing the market with AI, forcing telcos to act quickly to stay competitive. From cost savings to AI automation, AI solutions for telecom operations hold immense benefits.
Looking ahead, AI networks will transform telecoms in preparation for the 6G and 7G eras, with gen AI in telecom proving to telcos that their business models can be integrated with AI as their core businesses, even though it will not occur overnight, but the path to AI-driven networks is clear.
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