Telco generative AI adoption tracker
The Telco generative AI adoption tracker is a database of deployments of generative AI by telcos around the world. It also features STL’s assessment of key telcos’ progress with AI
The Telco generative AI adoption tracker is a database of deployments of generative AI by telcos around the world. It also features STL’s assessment of key telcos’ progress with AI
Following early AI investment, in 2021 SK Telecom announced its intention to become an AI company for the AI era. What actions has SK Telecom undertaken to this end? What role is AI playing across its business? And is AI paying off?
The AI revolution is transforming networks, demanding greater capacity and agility in datacentre interconnectivity (DCI) to support diverse workloads. This report explores the challenges AI presents and offers recommendations for providers to adapt through flexible connectivity and NaaS models.
People’s appetite for AI appears to be insatiable. In recent months, there has been a proliferation in the number of consumer-centric AI solutions on offer by telcos, aiming to build new revenue streams or support loyalty for their existing services.
AI will create large potential opportunities for telcos in connectivity and use case enablement. But telcos must manage expectations and prioritise their investments carefully.
As AI’s energy consumption rises, so do sustainability concerns. This report explores why this technology is so power-intensive, how to mitigate its impact and whether it can help reduce emissions. It also examines four possible scenarios for future energy consumption – from unchecked growth to greater efficiency – and their sustainability implications.
STL Partners’ Research team present their observations from and analysis of the biggest mobile industry event of the year. There was a lot of buzz around AI and API but behind the tech jargon, we saw evidence that our industry continues to morph to become more open and customer-focused.
Generative AI is expected to create significant value across the telecommunications industry. To capitalise on the opportunity, telcos must build new skills across their organisations. Getting this right is critical given the scale of implementation challenges and the significance of impact on how employees work.
AI applications will require low-latency, local compute for rapid inferencing and large scale data collection, triage, and engineering. Edge compute will therefore play a key role in AI app delivery. However it’s not just about infrastructure – commercial scale for edge AI will depend on effective ecosystem collaboration models.