Bienvenue chez BROADBAND AFRICA, le partenaire incontournable des entreprises africaines pour construire ensemble les réponses idoines aux besoins en Télécommunications. Que ce soit en termes de connectivité, de mobilité, de sécurité, BROADBAND AFRICA vous conseille dans vos choix stratégiques.  Idéalement implantés au Cameroun et au Bénin, notre expertise est au cœur des régions d'Afrique centrale (CEEAC) et d'Afrique de l’Ouest. Nous proposons de vous accompagner à choisir, ensemble, des solutions adaptées pour protéger vos données, vos infrastructures et vos opérations face aux menaces numériques croissantes. Grâce à la maîtrise des technologies avancées voir avant-gardistes combinée à une approche personnalisée, nous garantissons de vous aider à mettre en place des systèmes sécurisés, fiables et performants. 

A few days ago, John Saw introduced a term that reframes how we think about AI in the physical world. He called it the kinetic token. His argument is simple but structural: If large language models are built on informational tokens that represent fragments of text, then machines that move, lift, weld, or drive must be built on atomic units of time-indexed physical state and not just symbols. Measurements are tied to position, velocity, force, energy, and identity.That shift marks the boundary between Language AI and Physical AI. In one world, tokens optimize probability distributions over words. In the other, tokens sit inside control loops where milliseconds translate into motion, and error margins translate into safety risk. When intelligence leaves the cloud and enters factories, roads, ports, and robots, the unit of computation changes. And with it, the infrastructure and monetization logic must change as well.

Our productized service orchestration platforms allow digital service providers to manage broadband devices and services, bringing extensive automation and analytics to reduce operational costs and improve the user experience. Our solutions are proven in CSP networks globally, delivering tangible operational efficiencies and service agility.

We provide the expertise and global reach to accelerate the industry’s journey to the cloud and improve business operations, driving innovative next-generation digital experiences for the end user. Our 5G-ready, cloud-native set of solutions ensures fast time to market and flexibility to keep up with technology’s exponential pace. We also have strategic cloud collaborations with AWS, Microsoft Azure and Google Cloud.

OSS (système de soutien opérationnel) se concentre sur le bon fonctionnement de l'infrastructure des télécommunications, ce qui la rend plus efficace. orienté vers le réseau.BSS (Business Support System) gère l'aspect commercial des télécommunications, ce qui lui permet d'être plus efficace. en contact avec les clients.

A key component of the Digital Experience Solution, Incognito's Auto Configuration Server (ACS) is a vendor-agnostic, massively scalable software platform that manages and monitors devices over any network, including fiber, fixed wireless, xDSL, HFC, and IoT. By leveraging remote management protocols such as TR-069 CPE WAN Management Protocol (CWMP), TR-369 User Services Platform (USP), SNMP, and MQTT, Incognito's TR-069 ACS device management platform enables greater insight into the in-home network and other services, so you can deliver preemptive support, measure service quality and speed, as well as improve customer experience and QoE, all while driving cost reductions with greater operational efficiency.

Over the past 18 months, nearly every major telecom vendor has signaled its ambition in local distributed inference. Nokia aligned its future RAN roadmap with NVIDIA's accelerated GPU platforms. Ericsson has publicly discussed edge inference. SK Telecom is building edge GPU infrastructure. Deutsche Telekom launched its sovereign AI data center initiative in Germany. The telecom industry is repositioning inference from centralized data centers to distributed network environments.But these ambitions are crashing into economics.A modern data center GPU, such as an A100 or H100, typically costs tens of thousands of dollars before power, cooling, and integration. Even enterprise-grade RTX cards become capital-intensive when deployed across dozens or hundreds of sites. Industry surveys and operator feedback suggest that average enterprise GPU utilization often remains well below 50%, frequently in the 15-35% ange, depending on the workload mix. In centralized hyperscale environments, demand aggregation can smooth these inefficiencies. In distributed telco networks, geographic fragmentation tends to amplify them.

In the last three months, OpenAI has moved from speculation to reality. Reporting based on sworn court filings confirms a working prototype and indicates that the first hardware product will not ship before late February 2027, alongside a branding pivot away from the “io” name. Executive statements at Davos anchor a reveal window in the second half of 2026.More importantly, first-party hiring signals describe an end-to-end consumer device stack: custom silicon, embedded systems, operating system kernel and frameworks, camera firmware, secure boot, A/B OTA infrastructure, and hardened software supply chain controls. The pattern matches with OpenAI building a vertically integrated hardware platform designed to sit beside the smartphone and control the ambient AI interface layer around daily digital life.OpenAI is leaving chat interfaces behind and moving into the physical world.

For 18 years, telecom apologized for being “dumb pipes” while software ate the world. That era is dead. The illusion of the cloud has shattered against the hard physics of AI: you cannot run a trillion-dollar model on vibes. You need high-density power, advanced cooling, and deterministic glass. We are no longer utilities; we are the Intelligence Refinery.But assets alone won’t save us. While we own the “Last Mile” required for AI inference, our culture is constitutionally hostile to it. We worship the “Five Nines” of static perfection, while AI demands probabilistic speed and risk. If we don’t dismantle this bureaucratic reflex, we will build the most expensive railroad in history only to watch Silicon Valley own the trains.

The NVIDIA 2026 State of AI in Telecommunications survey shows an industry going all-in on AI. Yes, all in. Like very few industries in the world. An industry that will not wait for 6G to apply AI in spectrum, energy, and RAN. An industry where the majority will deploy inferencing at the edge, where AI is already embedded in operations, and where agents are moving fast into production environments.Why?Because the returns are already there. Most operators report improvements in revenue and costs, and almost all plan to increase AI investment in 2026. Telecom has chosen AI as its transformation story and wants to be early, not reactive. The implications are seismic.The AICO revolution is here.

Emboîtant le pas à B&YOU, trois autres opérateurs de téléphonie mobile annoncent l'arrivée de frais de résiliation sur leurs forfaits sans engagement.

Telco network exposure is the right move. Aduna shows what that looks like in practice. Structured as a joint venture between Ericsson and a group of leading global operators, and built on CAMARA standards, it aggregates network APIs so developers can integrate once and reach multiple networks. In the US, AT&T, Verizon, and T-Mobile are aligned. In recent interviews, Vonage CEO Niklas Heuveldop has been candid: authentication and fraud APIs such as SIM Swap and Number Verification are now generating revenues in the tens of millions.That proves demand is real, even if it remains marginal at telco scale. The industry narrative has matured from headline projections to a more grounded ambition: building the first $100 billion over time.

AI has forced a fundamental question inside the Radio Access Network: what kind of compute should power 6G? For decades, the answer was obvious: Purpose-built silicon optimized for deterministic signal processing wins on power, cost, and reliability. Now that assumption is under direct scrutiny. NVIDIA class-accelerated compute is entering the baseband conversation, and two European vendors with more than a century of survival behind them are taking opposite paths.Ericsson is doubling down on custom ASIC and energy-efficient Layer 1 acceleration. Nokia is aligning its future baseband roadmap with Nvidia accelerated platforms and positioning RAN as a distributed AI compute fabric. This is not a minor branding disagreement; RAN accounts for roughly 60% of Ericsson's revenue and about 40% of Nokia's. A wrong architectural bet in the 6G cycle could be fatal. But also, the final RAN Vision will also shape margins, market share, and long-term relevance.

I love Barcelona, and I love MWC. The people, the energy, the late dinners after Hall 3, the chance to meet half the industry in four days. It is the one week where telecom feels like the center of the world. But like any great city, there are tourist traps. And in 2026, many of them will have AI written in big bold letters. Some will be real innovations. Many will be light integrations, LLM wrappers, and marketing upgrades. I wrote this guide so you can skip the noise, avoid wasting time, and focus on the AI that actually moves cost curves, energy profiles, and revenue.

Between 2010 and 2020, IoT was positioned as telecom’s next growth engine. Forecasts projected tens of billions of devices, recurring revenues, and deep enterprise integration. The volume materialized, but the value did not.By the end of 2025, global IoT connections reached roughly 21 billion, according to IoT Analytics. Cellular IoT alone accounts for approximately 4.5 billion connections and is projected to reach 8 billion by 2031, according to the Ericsson Mobility Report. On paper, scale exists. IoT connections are projected to double by 2031, but most growth comes from short-range technologies rather than cellular.However, the economics of this business tell a different story. Cellular IoT ARPU in many markets ranges from $1 to $5 per device per month for NB-IoT and LTE-M deployments. Even broadband IoT modules, such as LTE Cat 1, operate at narrow connectivity margins. Compare that to satellite IoT, where legacy plans often range from 40 to 70 dollars per device per month. Volume versus premium.

In early February, more than $285 billion in software market value was lost in a single session following the release of enterprise agents by Anthropic and OpenAI. Within days, cumulative losses across SaaS names crossed $1 trillion. The IGV Software Index fell roughly 30% from its late September peak. Forward earnings multiples compressed from around 39x to near 21x in a matter of months. Short sellers reportedly generated more than $20 billion in profits in 2026 positioning against legacy SaaS.

If you follow the US telecom market closely, there is little need for scripted drama elsewhere. In Q3, the three kings were still marching in different directions. Verizon was focused on yield discipline and cultural reset. AT&T was executing a fiber-led convergence model with almost mechanical consistency. T-Mobile was scaling fixed wireless and pushing growth into every open flank. Three doctrines, three tempos, three interpretations of where value would come from next.By Q4 and full year 2025, something shifted. The divergence narrowed.All three are now targeting the same asset: the American home. Not as a side product, but as the strategic control point of the account. Home broadband increases wallet share per household, reduces mobile churn through bundling, and raises switching costs by embedding connectivity deeper into daily life. Fiber passings, fixed wireless scale, and even satellite backstop coverage are now tools for the same objective: own the household relationship, and the rest of the revenue stack follows.

Quantum internet is approaching faster than many expected. At the same time, the world still runs on classical encryption that quantum computers are projected to break within the next decade.Enterprises, governments, and consumer networks rely on cryptographic foundations that will not withstand a quantum computer with cryptographic relevance. Post-quantum standards were finalized in 2024, and regulators have begun setting migration timelines. The transition is an infrastructure upgrade that must start now.Telcos sit at the center of this shift.They move the world’s data and operate the physical networks where quantum security will be deployed. According to STL Partners, 35 operators are already active across 75 quantum-related projects, from pilots to commercial launches.Telco Momentum is building, and yet the risk is familiar: Telcos can either shape the quantum internet and own the trust layer, or remain passive transport providers while others capture the value. As quantum capabilities move closer to the network, the strategic choice cannot be deferred.

Le lancement commercial des services 5G, amorcé dans certaines régions dès octobre 2022, a rapidement pris de l’ampleur. Les opérateurs majeurs – Bharti Airtel et Reliance Jio – se sont lancés dans une course effrénée, chacun revendiquant déjà 50 millions d’abonnés après seulement douze mois. La concurrence s’est ensuite intensifiée avec l’arrivée progressive de Vodafone Idea, notamment dans plusieurs grandes villes dès 2025.

Then in February 2026, T-Mobile US launched something unexpectedly bold: Live Translation, a network-integrated, real-time voice translation service available to postpaid customers in beta. During a live call, you dial a short code and translation activates instantly across more than 50 languages. No app, no special device. It works on VoLTE, VoNR, and VoWiFi, even when calling a landline, and only one party needs to be on T-Mobile. Speech flows, AI translates, the conversation continues.Simple, Useful, and technically elegant.But translation is the tip of the iceberg for Telcos. AI is now integrated directly into the carrier's voice path within the network. That means the call is no longer just transport; it becomes programmable. Once intelligence sits in the media stream, fraud detection, voice biometrics, compliance monitoring, contextual agents, and transaction controls become possible at scale. This is the beginning of something much larger, and now the question is whether operators will have the courage to build on it.