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AI-driven 6G networks: The future of telecommunications

AI-native 6G networks will redefine connectivity, integrating AI for seamless optimization, security, and efficiency in mobile communications

Telecommunications is undergoing a major transformation with AI-native 6G networks.

AI is transforming industries, and telecommunications is no exception. With the rise of artificial intelligence, a new concept is emerging—AI-native telecommunications networks. These networks integrate AI from the ground up, shaping the design, deployment, and operation of mobile communication systems.

As researchers push the boundaries of what’s possible, the next generation of wireless technology—6G—will depend heavily on AI to drive efficiency, security, and performance.

The Shift Toward AI-Native Telecom Networks

Mobile networks have evolved significantly over the past few decades. Early generations focused on increasing data speeds, but 5G introduced a shift toward integrating cloud services and edge computing into telecommunications infrastructure. While this brought new efficiencies, the leap from 5G to 6G is expected to be even more transformative.

AI-native networks move away from static, rule-based models and embrace adaptive, learning-driven approaches. These systems use large-scale AI models, including Generalized Pretrained Transformers (GPT) and other machine-learning algorithms, to manage network operations intelligently.

Unlike traditional telecommunications infrastructure, which relies on pre-defined rules, AI-native networks continuously optimize themselves based on real-time data.

Lauri Lovén, Director of the Future Computing Group at the University of Oulu Finland, who coordinates the Distributed AI research line in the national 6G Flagship research programme. (CREDIT: University of Oulu)

A crucial component of this vision is the AI Interconnect, a system that enables AI-driven decision-making within the network. This advancement enhances network performance in key areas, such as radio signal optimization, resource allocation, and security management. The ability to dynamically select, provision, update, and create AI models within the network will lead to smarter, more efficient communications systems.

The Role of Large Language Models in 6G

Large language models (LLMs) are at the core of this transformation. These AI-driven models process vast amounts of data, interpret human and machine-generated input, and execute complex operations with minimal human intervention. In the context of 6G, LLMs will serve multiple roles.

First, AI will be a tool for managing network operations, commonly referred to as “AI for RAN” (Radio Access Network). This approach enhances network efficiency by using machine learning to optimize signal transmission and traffic management.

Second, AI-based applications will leverage 6G connectivity to enable new services, an approach known as “AI with RAN.” From IoT devices to autonomous vehicles, these applications will rely on fast, intelligent networks to process and transmit data in real time.

Finally, AI will become an integral part of the network itself, referred to as “AI on RAN.” In this scenario, the network adapts AI capabilities dynamically, ensuring seamless integration between computing and communication functions.

According to Lauri Lovén, Director of the Future Computing Group at the University of Oulu and coordinator of the Distributed AI research line in Finland’s 6G Flagship research program, “During the first four generations of wireless, we got used to seeing data rates skyrocket to new heights at each turn, transforming the way people use the network. With 5G, the improvement didn’t feel quite as radical, even though it was taking place.

The focus of network development had shifted beyond improving the user experience, introducing various machine-to-machine communication scenarios and implementing network services using modern software development methods, making them easier and better to manage in many ways. Put simply, 5G integrated cloud services and edge computing into mobile networks. With 6G, wireless networks will be combined with artificial intelligence.”

This evolution sets the stage for a future where AI is not just a supplementary tool but a fundamental part of telecommunications infrastructure.

AI Interconnect’s cross-layer design across control, user, and application planes. (CREDIT: University of Oulu)

Research and Development in AI-Driven 6G Networks

The foundation for 6G is being laid today. The University of Oulu was the first in the world to publish a comprehensive 6G white paper in 2019, outlining key research directions. Since then, over a dozen scientific papers have expanded on various aspects of 6G, with a recent focus on AI integration.

The latest publication, Large Language Models in the 6G-Enabled Computing Continuum: A White Paper, presents a collaborative effort involving 46 researchers. Edited by Lovén and a team of international experts, the paper explores how AI and 6G will converge to create new communication paradigms.

“Our focus is on the technical aspects, but we also briefly discuss regulatory and application dimensions, as well as security and resilience,” Lovén explains.

“Research on AI methods and ethical concerns is excluded from this publication. The writing process was demanding, but we are pleased with the final result. During the writing, there were differences of opinion. A small group of authors decided to withdraw their contributions altogether because they felt the changes we proposed were too extensive.

No conflicts occurred, however. The rules of the game were clear from the start: the editors have the final say on content.”

By addressing both technical challenges and broader implications, researchers are helping shape policies and innovations that will define the future of telecommunications.

Taxonomy of LLMs for 6G, mapping the potential applications of LLMs to both 6G use cases and underlying network architecture enablers. The LLM controller serves as a hub, suggesting the cooperative and management roles LLMs can play in a 6G ecosystem. (CREDIT: University of Oulu)

The Future of AI-Driven Telecommunications

6G networks will introduce a new level of automation and intelligence. The integration of AI will not only improve network efficiency but also revolutionize the way data is transmitted, stored, and processed.

The implications extend beyond telecommunications. AI-driven networks will play a critical role in industries such as smart cities, autonomous transportation, and robotics.

The ability to process data at ultra-fast speeds with minimal latency will enable applications that were previously impossible.

“Of course, the technologies for different AI models are developing at a dizzying pace, and so are the applications. On the tele-networking and computing continuum, from local devices to cloud computing centers, these may change not only the content of data transmitted and processed but also the methods of managing the network and its computing capacity.

Meanwhile, we may soon have personal AI helpers, or even a whole army of them, and we can already see the enormous computing and data transmission requirements that will come with them,” Lovén says.

Ecosystems will harness the capabilities of 6G, targeting goals like smart cities, gender equality, and climate change mitigation. (CREDIT: CC BY-SA 4.0)

Despite rapid advancements, some challenges remain. AI development moves at an unprecedented speed, while telecommunications standards follow slower cycles.

A new generation of mobile networks typically takes a decade to reach widespread adoption. Given this timeline, researchers are already preparing for the expected launch of 6G in the early 2030s.

“This was necessary and worthwhile to get published. In AI research, five years is a very long time.

A lot can happen in a year! But data network cycles are slower. And standardization takes a long time. One G takes about ten years. 6G is expected to hit the consumer market sometime in the early 2030s. That’s why we’ve already been researching it for years,” Lovén explains.

From early human-to-human communication to AI-driven interactions, the evolution of wireless networks has been remarkable. The next step will see AI playing a central role in facilitating human-to-machine and even machine-to-machine communication.

As researchers push the limits of AI and telecommunications, the future of connectivity will be shaped by networks that learn, adapt, and evolve in real time. The AI-native telecom revolution is just beginning.

Source: www.thebrighterside.news

Writer: Joshua Shavit

Cisco launches solutions to enable telcos to monetise AI services

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(These solutions cumulatively offer telcos the tools to evolve their networks, develop new service offerings, and monetise the delivery of assured services, according to the company.)

US-headquartered telecom gear maker Cisco on Tuesday launched a framework for telecom operators to kickstart the monetisation of artificial intelligence (AI)-driven services.

“Service providers are set to play a critical role in defining how, where, and when data from artificial intelligence (AI) applications moves across networks,” Cisco said, adding that its solutions can enable telcos to handle the increase in data volume and variety, and monetise the services supporting Al traffic.

“The Al revolution is a massive potential tailwind for service providers,” said Jeetu Patel, Executive Vice President (EVP) and Chief Product Officer, Cisco. “Al, and especially the advent of Al agents, will mean an incredible influx of new digital workers who will be working together and communicating constantly. Cisco’s Agile Services Networking is the blueprint for service providers as they look to capitalise on the opportunities of Al by meeting the demand for high-bandwidth, secure, and energy-efficient connectivity.”

Cisco’s ‘Agile Services Networking’ framework comprises the Cisco Silicon One systems and platforms, Cisco coherent pluggable optics, and network automation and assurance features that are “designed to remove complexity with simplified networking that converges network layers and services”, the vendor said.

These solutions cumulatively offer telcos the tools to evolve their networks, develop new service offerings, and monetise the delivery of assured services, according to the company.

The first of Cisco’s Silicon One-powered 8000 series has become available, while additional models are targeted to ship in the spring and summer of 2025. The first of Cisco’s new coherent pluggable optics is also targeted to begin shipping in the spring of 2025, while the network automation and assurance features are available now.

Source: telecom.economictimes.indiatimes

Nigeria Approves AI Trust & Universal Connectivity Project

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In a significant move toward enhancing digital access and driving technological innovation, the Nigerian government has approved two transformative initiatives aimed at bridging the digital divide, expanding rural mobile connectivity, and positioning the country as a leader in artificial intelligence.

The Federal Ministry of Communications, Innovation & Digital Economy announced that the Federal Executive Council (FEC) has granted approval for the Nigeria Universal Communication Access Project, a strategic initiative under a Public-Private Partnership (PPP) funding model. Designed to complement Project Bridge, Nigeria’s ambitious 90,000km Fibre Fund, this project will extend mobile network coverage to over 21 million people across 4,834 remote communities currently lacking basic telecommunications infrastructure. By deploying additional base stations in underserved regions, the initiative aims to enhance connectivity and improve the quality of life for millions of Nigerians.

Nigeria’s vision to become a global AI powerhouse has received a major boost with the FEC’s approval of the National Artificial Intelligence (AI) Trust. As the first initiative of its kind globally, the AI Trust will mobilize resources, oversee AI development, and ensure strategic investments in AI-driven innovation. This move highlights the government’s commitment to leveraging AI as a catalyst for economic growth, job creation, and increased foreign direct investment, ensuring Nigeria remains at the forefront of the digital revolution.

These approvals mark a significant step in Nigeria’s digital transformation journey, reinforcing its role as a leader in connectivity and emerging technologies.

Source: www.telecomreviewafrica.com

The AI Revolution: Separating Fact from Fiction

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Author: Ing. Dr. Kenneth Ashigbey

One of the lessons I learned in my MA IT Law class, taught by one of the outstanding AI academics, Kwaku Boadu, was separating the hype of artificial intelligence (AI) from reality and what we need to do with AI; it is like any software in our quest to develop. Yes, we do not have to dismiss it; we need to focus on the mathematics that underlines the software and ensure that we get our young ones properly trained to develop our AI and AI strategies to help solve our unique challenges as part of the arsenals we need.


As AI continues transforming industries and revolutionizing how we live and work, it’s essential to separate fact from fiction. The AI hype has been building for years, with proponents hailing it as the solution to humanity’s most pressing problems. However, as the dust settles, it’s becoming clear that the reality of AI is more nuanced. Yet, this nuanced reality also holds the potential for AI to make significant positive changes in our world.


The Rise of Large Language Models
Large language models (LLMs) like ChatGPT, Bard, Gemini, and, more recently, DeepSeek are emerging as the most tangible and widely applicable AI technologies. These models combine existing knowledge from the Internet, using probability math to generate the most probable answer to a prompt. While LLMs have the potential to revolutionise industries such as education, healthcare, and customer service, they also have limitations.


The Hallucination Problem
One of the significant limitations of LLMs is their tendency to “hallucinate” answers. This means they can provide inaccurate or nonexistent answers. The implications of this are far-reaching. As LLMs become more pervasive, there’s a risk that we’ll rely increasingly on these models for answers rather than engaging in rigorous research, argumentation, and reasoning.


The Consequences of Over-Reliance on AI
The consequences of over-reliance on AI are already being felt. As we rely more heavily on LLMs for answers, we risk losing critical thinking skills and the ability to evaluate information critically. This could lead to a new normal of ‘hallucinated truths’ in academia, industry, and social settings. We risk our youth believing the lie that AI would do all the thinking for them so they do not have to think any more. This significant risk could further widen the digital divide and, by extension, the developmental gap between the so-called developing world and the developed world, which now comprises the West and East. It’s crucial that we recognize this risk and take responsibility for maintaining our critical thinking skills, ensuring that AI serves us rather than the other way around.


The AI Hype: A Cautionary Tale
The AI hype has created a market where any programmer can label their code as “AI” to command a higher price. This has resulted in a proliferation of AI-branded products, from mundane tasks to critical applications. However, not all AI is created equal. It’s essential to approach AI critically and nuancedly, recognising its potential benefits and limitations.


A New Era of AI Development
As the AI landscape continues to evolve, it’s clear that genuine AI will be free from the shackles of hype. The Chinese approach to AI development, which focuses on practical applications and rejects the hype, is a model worth emulating. By taking a more pragmatic approach to AI development, we can create more cost-effective and efficient AI solutions that benefit humanity. This approach should reassure us that AI can be a force for good when developed and used responsibly.


Conclusion
As we navigate the AI revolution, it’s crucial to separate fact from fiction. By recognizing the limitations of LLMs and approaching AI with a critical and nuanced perspective, we can unlock AI’s true potential and create a future where technology serves humanity rather than vice versa.

Telcos need to get creative to drive value from AI

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As AI becomes an increasingly dominant theme in telecoms, a recent TM Forum webinar explores how the technology could be used to create new services and ultimately, it’s hoped, generate revenue.

(Source: Skorzewiak/Alamy Stock Photo)

Mobile World Congress is only a few weeks away and it’s already clear that artificial intelligence (AI) in telecom, from predictive through to generative and agentic, will be a prominent theme, as it has been since ChatGPT first made its presence felt. A quick glance at the conference program alone makes it clear how much AI will dominate the agenda, with sessions on AI and diversity, on-device AI, AI and governance and more besides.

More nuanced operator approaches to AI in telecom are beginning to crystallize, meanwhile. For instance, Laurent Leboucher, group chief technology officer and executive vice president of innovation networks at Orange, distinguishes between “AI for network”and “network for AI” to explain how operators handle a dual focus on AI, whereby the technology is used to optimize networks on one hand, and support revenue-generating services on the other.

A key question that many will be asking at MWC is: how will operators generate value from their deployments of AI, and what should the next steps be now that the industry is, perhaps, starting to move a little beyond the hype?

Driving value

Recent developments in AI mean that operators have the opportunity to use the technology for new product and service creation, potentially creating new revenue streams as well as optimizing their own networks and operations. But where do the opportunities lie, and where do they fit into the value chain?

This was the topic of a TM Forum webinar on Tuesday, titled “Leveraging AI for service and value creation.”

Mark Newman, chief analyst at TM Forum, remarked that much of the industry focus until now has been on driving operational efficiencies for greater productivity.

 “That can be one part of value creation. The other part of value creation can be creating new products and services, or enhanced products and services,” Newman said.

At the same time, he added, the idea of developing new products is “newer to operators, and it’s lagging behind. However … there’s a recognition in the industry that over a period of time, the focus on value creation will become as important as the focus on productivity and efficiency gain.”

To be sure, operators “have had a tough time building new value-added products and services. They’ve been endeavoring to expand beyond voice, messaging and connectivity for the last ten, 15, 20 years, without too much success,” Newman said.

For example, he made a comparison with operator attempts in the past to become public cloud providers. Ultimately these strategies largely failed, and operators became consumers of cloud computing services instead.

“Is the industry in a different position for leveraging AI for value creation than it was for cloud computing? … There is generally a view that operators might have always been behind the curve when it came to cloud computing, but when it comes to AI, maybe some of them are not so far behind. So they’re at an earlier stage in the exploitation of AI, to play an important role here,” Newman said.

Getting an edge

One topic that also emerged was the potential for edge computing with AI. As commented by Newman, “many enterprises will want to put their AI workloads both close to their own business and close to the network to guarantee performance, security, latency. So if that is the case, if that compute needs to be right next to network, does that therefore give telecom operators the opportunity to play in the edge computing space? Is it time to dust off those edge computing investment plans?”

Volker Tegtmeyer, principal product marketing manager at Red Hat, said edge will be key to avoid having to move all of the data to a central location.

 “I think from a deployment point of view, the flexibility is key. It’s either edge or it’s a private cloud, or could even be a public cloud, if you want to start something … at a small scale,” he said.

Tegtmeyer added: “What we expect to see is that service providers will have hundreds of AI models. They will leverage agentic AI, predictive AI, GenAI, and they might actually combine it, depending on what they need, to at the end, build a service. Not to make things more complicated, but yes, edge is important, and it will be a part of a much bigger puzzle.”

Getting down to business

According to Newman, “we can be pretty sure that there will be an explosion in new AI-infused products and services.”

He cited examples such as enhanced voice services, where operators try to modernize legacy voice and integrate them with services such as Microsoft Teams. Or there are concierge services, such as GenAI-based tools to help manage everyday life, as well as the concept of “artificial intelligence of things,” such as the combination of AI with video capabilities.

Ryan Walton-King, global industry market leader, communications, media, and consumer services at Pegasystems, also pointed out that predictive and adaptive AI can be used to gain insights about customers and then determine the best way to engage them, “whether that’s via digital, whether that’s via a call center rep, and making sure that you’re doing that with empathy and with context. 

Meanwhile, Richard Doughty, business development director at Cerillion Technologies, provided a couple of specific case studies of current AI implementations at telcos involving the deployment of AI-enabled catalogs and workflow. Here, he cited work with Paratus in South Africa as well as Ucom in Armenia.

Cerillion is “putting AI into the products to make them increasingly frictionless to use, and there’s a big focus on that ease of use, breaking down the interface … and then using that ease of interface with things like catalog to then help create products far faster, so reduce that time to market from weeks, maybe where it was 20 years ago, to days, really down to minutes now,” Doughty said.

Walton-King also made reference to work with a US carrier on what he called outage deflection using AI. “We’ve been able to deflect over 200,000 calls in the call center and identify outages 15 minutes earlier than when they could before,” he said. “A struggle for a lot of carriers is, how do we get ahead of these outages so that we don’t have people calling in? We can deflect calls, but even better, we can fix it before it becomes an outage.”

Source : Anne Morris (Contributing Editor, Light Reading)

Digital and wealth gaps have no place in the Intelligent Age. Here’s how everyone can benefit from AI

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This article is part of:World Economic Forum Annual Meeting

  • Artificial intelligence (AI) is set to transform the economy, as well as the lives of people around the world, ushering in the Intelligent Age.
  • It’s important to pay attention to the disruption that AI could cause, particularly to those already left out of the digital economy.
  • To fully harness AI, everyone needs access to the technology, as well as the tools, education and infrastructure that underpin it.

The rise of artificial intelligence (AI) and generative AI (GenAI) has been stunning in its speed and impact. AI could add $2.6 trillion to $4.4 trillion to the global economy annually, according to McKinsey. And while we often hear about the promise of AI, we also need to pay attention to the careers, lives and communities it will disrupt – including those who have already been left out of our global digital economy.

In the US, for example, Black Americans are 10% more likely to be working in jobs slated for AI automation. AI is anticipated to disrupt 4.5 million jobs for Black people and affect jobs in sectors that employ many women such as administration, retail and customer service. This would impose billions of dollars of economic harm on both groups.

Further, biases in the data used to train AI models can proliferate existing prejudices, including by reinforcing discriminatory housing, lending, hiring and pay practices. Economic gaps between nations are also projected to widen as a result of AI because wealthier countries are better equipped to more immediately adopt and benefit from it.

Our urgent task, therefore, is to prevent new social and economic gaps from appearing in the Intelligent Age. This can be achieved by empowering all people to participate and lead in AI. That includes building infrastructure that supports AI enablement for everyone, including education on AI tools and access to the internet and computing power.

Closing the digital divide

At a minimum, we must eliminate the existing digital divide. Despite the rapid proliferation of the internet across the globe, over 2.5 billion people still lack access to it. Nearly a third of the world’s population cannot take advantage of online services that are essential in today’s digital world such as finance and banking, education and healthcare.

Divides exist within developed countries, too. In the US, nearly 24 million people still lack access to high-speed internet. This prevents millions of Americans from accessing the services only broadband can provide and from fully participating in the economy.

Closing these gaps will give the next generation of leaders the resources, education and technical access needed to master evolving technologies. We must also double our efforts to provide education around these tools. A combination of critical thinking and technical skills is essential for interacting effectively with GenAI.

One model for closing the digital broadband divide in Black communities in the US, for example, is the work being done by Student Freedom Initiative (SFI) at Historically Black Colleges and Universities (HBCUs) – 82% of which reside in broadband deserts.

In partnership with Stats Perform, an AI solutions provider for the sports industry and a portfolio company of Vista Equity Partners, SFI launched an “AI in Basketball” course at Morehouse College in 2023. This has since expanded to other HBCUs. These courses provide hands-on instruction in AI-use cases, preparing diverse students to be leaders in this field.

Another notable example is the work being done at internXL, which offers opportunities such as free training and certifications in AI, data science and machine learning, including access to over 500 AI courses. It also connects highly-qualified HBCU students with AI experts and employers for internships, enabling them to gain practical experience in the field. This work is bridging access gaps and ensuring that underrepresented talent thrives in the rapidly growing and in-demand field of AI.

It is critical that we do even more to close these access gaps in the US and across the globe, so that everyone can take advantage of AI’s benefits. But we must also ensure widespread access to compute, or processing power, to run these new tools and their applications.

Using the example of smartphones, compute was made possible thanks to telecommunication companies updating their infrastructure to handle 4G, 5G and LTE. But many communities did not receive these investments, and now lack equitable access to these resources.

To fully harness AI, communities need to have access to the tools and infrastructure that underpin the technology: computing power, requisite energy sources, and large language models and other machine learning and reasoning tools. This would also enable more diverse inputs to be included in the data on which GenAI systems are trained, enriching the models.

Equitable development of GenAI

The racial wealth gap will cost the US economy $1-1.5 trillion between 2019 and 2028, and it is estimated that gender discrimination costs the global economy up to $12 trillion.

Instead of becoming a new economic wedge, AI could become a prolific source of generational wealth. So long as we take appropriate steps to prevent these tools from mimicking and reinforcing racial and gender biases, the innovation and economic growth AI would spur has the potential to generate prosperity for all.

With AI’s current trajectory, there will be three distinct waves of opportunity through which value will be captured. We are already seeing the first wave of value creation benefiting hardware vendors. The second wave will go to super scalers like Microsoft, Google, Oracle and other large companies that have the ability to broadly offer connectivity to compute. The third wave will benefit enterprise software vendors who provide AI and GenAI solution sets on top of their existing products.

These are the three distinct verticals on which we must focus efforts to enable equitable development and deployment of GenAI.

The good news is, unlike the digital revolution, we have the luxury of foresight. As AI evolves and established companies and new start-ups scale products, develop features and capture value at each stage, we must commit ourselves to ensuring everyone in every nation has access to the internet, AI education and tools, and processing power.

As we stand at this crossroads, we must think expansively and act decisively to ensure we unlock GenAI’s full potential.

(Source: www.weforum.org)

Beyond the Hype: How AI Will Shape Telecom Infrastructure in 2025 

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While many focus on AI’s role in customer service chatbots or network monitoring capabilities, the underlying changes run deeper: AI will help alter how telecom services are structured, delivered and optimized. Here are our predictions for 2025.

#1: AI Will Enhance Network Intelligence

Traditional telecom networks generate massive amounts of data, but this information remains trapped in silos, limiting its utility. In 2025, a significant shift will start to occur as Large Language Models (LLMs) begin integrating across the entire telecom stack, changing how networks operate and adapt

LLM-powered systems will enhance network management through conversational interfaces, allowing administrators to interact naturally with their data. By recognizing patterns across previously disconnected data points, these systems will enable proactive maintenance and help predict network failures, reducing service interruptions. The technology will also optimize network resources automatically, using real-time usage patterns and predicted demand to improve capacity allocation and cost management.

These systems will convert raw telecom data into actionable business intelligence. Network operators will gain new insights into customer lifetime value and identify service opportunities that were previously hidden and uncorrelated in siloed data environments.

However, this advancement comes with important caveats. Network operators must carefully validate AI-generated insights, as LLMs can hallucinate with a high degree of inaccuracy. The challenge of 2025 will be striking the right balance between AI automation and human oversight in critical network operations.

#2: AI Will Enable Autonomous Network Operations

Self-healing networks will emerge in 2025 as AI takes on a larger role in network operations and performance management. Telecom providers are moving beyond basic automation toward autonomous networks that can predict, prevent and resolve issues with minimal human intervention.

The addition of AI systems, such as Agentic AI, that interact with a combination of other AI technologies including machine learning, natural language processing and automation technologies, allows decisions around network optimization and performance to be made autonomously without constant human guidance and attention. Agentic AI will make decisions and adapt to changes autonomously based on predictions and human behavior, learning and improving from these interactions as it goes to proactively solve complex network problems independently.

These types of systems mark an important shift in network management, analyzing network data to prevent potential issues or resolving issues faster and more efficiently. From identifying signaling storms to adjusting for bandwidth spikes from new device launches or fraudulent network usage, AI will optimize network performance while determining cost-effective operational strategies.

The industry acknowledges the risks in this transition. As telecom providers expand their AI capabilities, they must balance automation with transparent, unbiased decision-making that meets regulatory requirements.

#3: AI Will Reshape Telecom Economics

AI will enable new approaches to telecom pricing and delivery in 2025. Static pricing and service models are shifting toward dynamic, AI-driven systems that align with network capabilities and customer needs.

This change is evident in how telcos are adapting to bandwidth-intensive applications. Gaming illustrates the trend: as 5G networks mature, providers need pricing models suited to low-latency, high-throughput scenarios. The implications extend beyond gaming to XR (Extended Reality), enterprise services, private 5G networks, cross border plans, IoT and V2X (Vehicle to everything) deployments.

AI will guide this economic evolution by helping carriers implement responsive pricing strategies. These systems will adjust pricing based on capacity demands, service quality metrics and usage patterns, identifying revenue opportunities while optimizing network resources.

The transition moves telecoms from fixed service tiers toward flexible, value-based models. AI systems will analyze market conditions, customer behavior and network performance to spot and act on new revenue opportunities.

#4: AI Will Advance Customer Experience

AI’s role in telecommunications customer service will expand in 2025, moving beyond today’s basic chatbots. AI assistants will act as problem-solvers, analyzing usage patterns and suggesting plan adjustments based on individual needs.

These systems will graduate to addressing complex issues, including billing discrepancies, device troubleshooting and service disruptions more efficiently than current solutions. By connecting with autonomous network operations, these assistants can identify and resolve problems in a contextual, conversational, human-like interface and in most cases resolve them before customers notice them.

Mobile Virtual Network Operators (MVNOs) will introduce AI co-pilots that change how customers interact with their providers. These assistants, available through mobile devices, will offer immediate support without requiring traditional customer service channels. They’ll function as service advisors, using network data and economic insights to customize service recommendations.

Looking ahead

While these changes won’t fully mature by 2025, the year will mark AI’s shift from experimental to established technology in telecom infrastructure, alongside a paradigm shift from AI assisting Humans to Humans assisting AI. Success will come to organizations that grasp AI’s broader potential: moving beyond automation to reshape how telecom services are delivered.

This evolution brings challenges, from privacy concerns to data governance and AI validation requirements. Yet the benefits—improved network efficiency and personalized services—make adoption necessary.

As we approach 2025, the question becomes not whether AI will alter telecom infrastructure but how organizations will adapt to and use these capabilities to drive better business performance.

Source: www.thefastmode.com

Author: Adil Belihomji

Adil Belihomji is the chief technology officer at OXIO, where he leads the technology vision and strategy for the company’s global telecom-as-a-service (TaaS) platform. He plays a pivotal role in driving product innovation while overseeing the development and implementation of technology solutions.

2025 in focus: Africa’s ICT regulatory outlook

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The key regulation issues forecast to be top of mind in 2025 include artificial intelligence, data protection, the digital economy, digital public infrastructure, and competition.

(Source: https://www.menosfios.com/)

As the new year gets underway, technology and its related business environment will be characterized by numerous policy and regulatory discussions around the need to address ongoing and emerging issues, either through revisions to existing frameworks or the formulation of new measures and approaches to market regulation.

With the ongoing evolution of technology and the changing complexion of the marketplace, there is a need to provide an enabling environment in which innovation, consumer and business interests are protected, while at the same time appreciating that such deliberations and resulting actions can never really define any end games for a sector that is constantly in flux.

Some of the key issues that will occupy discussions among policy makers, regulators, civil society and the business community include artificial intelligence (AI), the digital economy, digital public infrastructure (DPI), data protection, and competition.

To a lesser but equally crucial extent, ongoing discussions on improving data protection, social media and cybersecurity frameworks can be expected to continue.

Artificial intelligence

AI regulation was one of the areas of key focus across the continent in 2024.

Two main sides emerged – one was against regulation, reasoning that regulating AI would stifle innovation and slow adoption. The other side looked beyond innovation and adoption and viewing AI through a consumer protection lens, looking at the possible harmful and ethical issues relating to AI.

Related:The ethical considerations of AI in Africa

While there have been huge advances and greater adoption of AI across different sectors – with some already demonstrating tangible benefits – AI has also brought with it unsavory application areas. These include using AI as a tool to enable cybercrime (for financial fraud, phishing and social engineering) as well as in the social and political space with misuse intended to spread falsehoods and misinformation via AI altered text, images or videos.

AI regulation will still be a key focus across the continent in 2025. (Source: Image by DC Studio on Freepik)

Existing laws relating to data protection and privacy, cybersecurity, and misuse of computers and intellectual property, have been useful in the interim as a framework to address some of these areas, but in most cases they are not explicit enough to tackle these problems squarely and with any degree of finality.

At a continental level, AI has been discussed at the Africa Union (AU), where a draft policy was published in 2024, with several countries already making individual pronouncements in the form of sector guidelines.

Looking ahead, the way forward will very likely be paved with soft regulations that take the form of guiding principles to which all stakeholders must adhere, while at the same time continuing to draw on or amend existing regulations.

Related:The changing complexion of e-commerce in Africa

The digital economy

The steady march by business and consumers into the digital sphere, as well as the need to address the requirements of tech-savvy consumers who require new channels to transact, is bringing about the gradual realization of digital economies, with more and more organizations undergoing digital transformation.

One natural consequence of the shift into virtual spaces is the need to ensure tax collection is not affected; authorities are continuing to explore modalities that allow them visibility over the amount of business that happens online. 

This has necessitated different measures to gain visibility over business that happens online. Current measures include the onerous task of conducting audits of business and individuals using different social media platforms like Facebook, Instagram, and TikTok, as well as e-commerce platforms, as well as compelling providers (including telcos, streaming services and platform providers) to add levies to their subscription fees, in order to reduce the administrative load on revenue authorities.

Related:Cybersecurity: The big picture in Africa

In some cases, sizing up the digital space has involved working with payment gateway operators who have good visibility over such transactions between businesses and consumers.  

Broadly speaking, the legal framework on which digital economies can be enabled includes laws, polices and guidelines that touch on taxation, data protection and privacy, intellectual property and social media use.

During 2024, several African countries adopted different approaches to handing the digital economy, and it can be expected that, during 2025, these measures and existing laws will undergo further streamlining, amendment and harmonization.

Digital public infrastructure (DPI)

While DPI is still largely nascent, the push by governments and multilateral development agencies (whose ambitions relate to closing the digital divide and supporting transparency, among other areas) is something that will merit a review of existing laws.

Many have bearing on how DPI can be enabled since DPI inherently raises concerns about data protection, fraud, freedom of information, mobile payment regulation, digital identities and infrastructure sharing. 

Thus, it can be expected that discussions on implementing DPI will pick up pace as different stakeholders explore modalities on how this can be leveraged to deliver services to citizens. 

Competition

The move by satellite providers in different countries into the connectivity space is being met with some degree of consternation by some local Internet service providers and mobile operators, who mostly claim it makes the playing field uneven for them, with some indicating that such players are not subjected to the same regulatory oversight as local players.

In some cases, local players are the ones who have taken the initiative to strike deals with satellite operators who offer direct to mobile connectivity arrangements that allow them to plug voice and data coverage gaps and reduce their infrastructure spending.

Between 2023 and 2024, players like Starlink gradually increased their footprint across Africa, though it has not been easy sailing in some markets where regulations either require local ownership or the requirement to work with channel partners through whom authorities can gain visibility on operations for the sake of taxation and consumer protection issues.

It should be noted that, at the outset, satellite players were indulged on the premise that they could help address rural coverage. 

However, as has been noted in many countries, urban areas have been the focus for the simple reason that affordability is an issue in most rural areas. 

As such, most new subscribers are in urban areas, which has unseated that premise about closing the rural digital divide. 

Between 2023 and 2024, Starlink gradually increased its footprint across Africa but also faced challenges. (Source: Starlink)

In 2025, it can be expected that regulators will move to respond to concerns by local players, by introducing new licenses as well as ensuring such players are compliant with pricing guidelines set out.

It can also be expected that discussions by the International Telecommunications Union (ITU) on spectrum, rural connectivity, etc. may have some bearing on how these players operate.

Data protection

In 2024, only 36 out of 54 African countries had enacted data protection laws.

At a continental level, despite the Malabo Convention (on cybersecurity and data protection) being adopted more than a decade ago, when it came into force on June 8, 2023, only 15 AU countries had ratified it, limiting its continental credibility. This itself hampers efforts at harmonizing data protection laws as well as limiting collaboration on cybersecurity.

Data protection concerns keep morphing and will remain on the horizon for quite a while. 

Ongoing digital transformation, including by government entities, coupled with new business channels, mobile applications, and know-your-customer (KYC) principles by financial institutions are among other areas that will keep data protection in focus.

It can be expected that this convention will be reprised at the AU during 2025 as individual countries continue to address data protection.

Spectrum costs

It should be expected that spectrum costs will be among the areas up for discussions, in some cases based on lessons learned from 5G spectrum auctions for which many operators have yet to realize returns on investments. 

Therefore, pricing at auctions may require a review based on market realities and the potential exploitation of spectrum for different applications.

The spectrum gravy train may not have dried up yet, but it has certainly slowed down. 

Cybersecurity

Just like data protection, cybersecurity is a constant feature in the ICT landscape in Africa. 

With more and more cyberattacks registered in 2024, a good part of discussions on policy and regulation will invariably feature cybersecurity in 2025 because the risks are not bound by borders and threat actors can be either in African countries or outside of them.

The need to enable collaboration across the continent and globally will underpin discussions on cybersecurity in 2025.

About the Author

(Source: Image by DC Studio on Freepik)

Francis Hook

Africa ICT Analyst, Connecting Africa

Francis currently works independently undertaking ICT research and consulting projects across Africa.