Annie Turner rounds up network automation and AI stories from what turned out to be a very busy May.

BT hit the headlines when its group CEO, Philip Jansen, announced the operator would cut 55,000 jobs – about 42% of its workforce – by 2030. This is not quite as radical as it looks at first glance as of thousands of them are contractors working on Openreach’s massive fibre build out which will be all but complete by 2030. However, about 10,000 roles will be lost due to more automation and digitalisation as BT looks to make annual cost savings of £3 billion a year by the end of 2025.

Jansen enthused about the potential uses of AI-enabled tools for automation and its impact on BT’s business, pointing out the operator “has filed more AI patents than any other UK-based company” and that it already runs a dark network operating centre where “network planning can be done automatically with AI in a way that couldn’t happen two or three years ago”.

He added, “We’ve got AI and all the data that can help create self-healing networks,” and said BT will be a huge beneficiary, to the tune of many millions of pounds, in terms of efficiency and cost. Jansen was speaking on the same day that BT reported a 12% decline in pre-tax profits to £1.7 billion, which it attributed to the higher cost of building networks, although revenue was down 1% too.

More staff, more automation

Vodafone Group’s new CEO, former CFO Margherita Della Valle, said Vodafone’s poor performance meant it would be cutting 11,000 jobs – more than 10% of the workforce – over the next three years by becoming simpler and leaner in an attempt to be more appealing to customers and shareholders.

This is not a straightforward reduction of headcount. While Della Valle said “layers are to go” at the London-based group offices in Paddington, in a recent exclusive interview, Vodafone Group’s CTO and Head of Vodafone Technology, Scott Petty, talked about the strategic decision to add 7,000 software engineers in October 2021. Although still far from that target, he commented, “Our headcount has gone up in Technology as we’ve added those capabilities, but our external spend with systems integrators has gone down by more so it’s helped us deliver our cost savings targets as well.”

Nokia adds insights for AIOps

Nokia is adding AI-derived insights to its Fixed Network Software-as-a-Service (SaaS).  solutions suite. AVA Fixed Network Insights will be launched later in the year and is designed to help operators to improve customer service while reduce operating costs.

It collects access and Wi-Fi network, router, device and OSS data to identify problems using Bell Labs developed AI/ML models. The insights will provide operations and customer care teams with automated recommendations so they can identify and resolve problems remotely before they manifest network service problems. The idea is to shorten call handling times and improve first-call resolution.

Julie Kunstler, Chief Analyst, Broadband Access Intelligent Service, at Omdia, said, “The SaaS delivery model is a critical piece of digital transformation for operators. Nokia’s new Fixed Network Insights SaaS component provides operators with another needed pathway towards AIOps-driven, self-healing fixed broadband networks.”

Turkey and acceleration

Mavenir announced a partnership with i2i Systems to work closely with network operators on Open RAN in Turkey. They plan to work on Mavenir’s containerised microservices portfolio and adapt it to “the necessary localization to accelerate the delivery and adoption of Open RAN”.

Mavenir also announced a $100 million funding round to expand its technology and its customer base. The firm said the funding is “anchored” by a long-establish backer and former majority owner, private equity company Siris.

Pardeep Kohli, Mavenir’s CEO and President, commented, “This new capital will allow us to accelerate our capabilities in automation, sustainability and use of AI as we enable our customers to efficiently deploy and operate Open RAN based end-to-end cloud-native networks. Our unique strategy incorporates best practices from the hyperscale, cloud and IT industries, to transform how the world connects and builds the future of networks.”

High performance Ethernet

DriveNets, which offers cloud-native networking solutions, has introduced Network Cloud-AI, which is designed to maximise the use of AI infrastructures to improve the performance of large-scale AI workloads. It is built on DriveNets’ Network Cloud which “is deployed in the world’s largest networks” and the company says has been validated by “leading hyperscalers in recent trials as the most cost-effective Ethernet solution for AI networking”.

The company explains that it was prompted to develop the solution because AI workloads perform best when the network is in full operational use. Yet until now AI networks were based on either traditional Ethernet leaf-and-spine architecture not intended to support high-performance AI workloads at scale, or with proprietary solutions that did not support network interoperability and had little flexibility for hyperscalers keen to avoid vendor lock-in.