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Tag: AI

Future Skills Tracker report

Telcos need new skills to change their organisations to compete like technology companies. Insights from our Future skills tracker tool show that telcos are behind techcos in the penetration of key skillsets and provides direction on the capabilities required to become more innovative, agile and software-driven overall.

Telecoms 2030 Part 1: The telecoms industry problem

The traditional “moat-building” business model adopted by telcos is no longer viable. If telcos are to compete with internet giants in 2030, they must fundamentally change as organisations. Part 1 of our Telecoms 2030 series outlines this need for change, providing three possible business models for the telco of 2030 – Servco, Infraco and Techco.

MWC 2024: More than AI and APIs

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.

Automation: Reaching full potential

The maturity of telco automations in the network OSS and BSS varies significantly. Some telcos are reporting significant headcount reductions from mature automations while others are still in the early stages of simple automation deployments. There are important steps telcos must consider if they are to reach maximum automation.

Five ways to get open RAN deployment back on track

The first commercial deployments of open RAN networks have been announced. But operators are unsure whether to deploy quickly for first-mover advantage or play it safe and wait for more proof points. We explore the causes of open RAN inertia and how operators can get deployments back on track.

Edge AI – How AI is sparking the adoption of edge computing

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.