Global AI in Telecommunication Market at CAGR ~ 40% through 2026 – 2027

The Global AI in Telecommunication Market [1.] is estimated to be $1.2 Billion (B) in 2021 and is expected to reach $6.3B by 2026, growing at a CAGR of 38%, according to a report by Research and Markets.

For comparison, Valuates says the global AI In Telecommunication market size is projected to reach $14.99B by 2027, from $11.89B in 2020, at a CAGR of 42.6% during 2021-2027.

Note 1. Artificial Intelligence in Telecom includes handling large volumes of data using machine learning and analytics, automating detection and correction of failures in transmission, automating customer care services, and complementing Internet of Things(IoT), e-mail, voice call, and database storage services.

Key factors of AI in telecom include the deployment of 5G mobile networks, growing demand for effective and efficient network management solutions have been driving  AI in telecommunications market growth. Increasing AI-embedded smartphones and the growing adoption of AI solutions in various telecom applications are likely to further drive market growth.

Market Drivers:

  • Increasing Adoption of AI for Various Applications in the Telecommunication Industry
  • AI Can Be the Key to Self-Driving Telecommunication Networks
  • Increased Need for Monitoring the Content Spread on Telecommunication Networks
  • Growing Demand for Effective and Efficient Network Management Solutions

Telecom vendors commonly use AI for customer service applications, such as chatbots and virtual assistants, to address many support requests for installation, maintenance, and troubleshooting. To improve customer experience, telecom operators are adopting AI.

Other common uses of AI in Telecom include:

  1. Predictive maintenance

  2. Network optimization

  3. Fraud detection and prevention

  4. Robotic process automation (RPA)

Opportunities include:

  • Cloud-Based AI Offerings in the Telecommunication Industry
  • Utilization of AI-Enabled Smartphones

Conversely, incompatibility between telecommunication systems and AI technology, which leads to integration complexity in these solutions, is the major constraint for market growth. Also, the lack of skilled expertise and privacy & identity concerns of individuals are some other factors hindering the market growth.



Exium Collaborates with IBM on Secure Edge Compute for AI and IoT Applications

Exium, a 5G security company [1.], today announced that it is collaborating with IBM to help clients adopt an edge computing strategy designed to enable them to run AI or IoT applications seamlessly across hybrid cloud environments, from private data centers to the edge. Exium offers clients an end-to-end AI deployment solution designed for high performance on the Edge that can extend to any cloud. This platform can help clients address vendor lock-in by providing flexibility to run their centralized Data/AI resources across any cloud or in private data centers.

Note 1.  Exium was founded in 2019 by wireless telecommunications entrepreneur Farooq Khan (ex-Phazr, ex-JMA Wireless).  The company believes that the current Cybersecurity Model is broken. Existing cybersecurity approaches and technologies simply no longer provide the levels of security and access control modern digital organizations need. These organizations demand immediate, uninterrupted secure access for their users, teams, and IoT/ OT devices, no matter where they are located.

Exium’s Intelligent Cybersecurity Mesh™ (see diagram below) provides secure access for a distributed workforce, IoT devices, and mission-critical Operational Technology (OT) infrastructure, protecting businesses from malware, ransomware, phishing, denial of service, and botnet infections in one easy to use cloud service.

CyberMesh consolidates three technologies, 5G, Secure Access Services Edge, or SASE, and Extended Detection and Response, or XDR in a single powerful cloud platform.

The Intelligent Cybersecurity Mesh is the first network security platform rooted in internationally accepted digital trust standards and is a reflection of Exium’s commitment to an open, interoperable, and secure global internet for all.


Exium’s Secure Edge AI is designed to provide a secured, highly performant Edge for IoT data collection and AI execution that works with WiFi/Ethernet/4G today and will be able to assist enterprises to upgrade to 5G in the future.

Exium’s CyberMesh is designed to deliver Zero-Trust Edge Security, Intent-Driven Edge Network Performance, and connect Edge and Cloud locations to help provide scalability and resilience out of the box. Zero-Trust Edge Security addresses trust assumptions to help build the connection between users, devices, and edge applications. Intent-Driven Edge Network enables edge applications to influence the 5G network for traffic routing, steering and QoS control.


“With computing done in so many places—on public and private clouds and the edge–we believe the challenge that businesses face today is to securely connect all these different elements into a cohesive, end-to-end platform,” said Farooq Khan, Founder & CEO at Exium. “Through our collaboration, Exium plans to integrate with IBM Edge Application Manager to offer edge solutions at scale for our clients.”

“We look forward to collaborating with Exium to help clients deploy, operate and manage thousands of endpoints throughout their operations with IBM Edge Application Manager,” said Evaristus Mainsah, GM, IBM Hybrid Cloud and Edge Ecosystem. “Together, we can help enterprises accelerate their digital transformation by acting on insights closer to where their data is being created, at the edge.”

A recent IBM Institute for Business Value report, “Why organizations are betting on edge computing: Insights from the edge,” revealed that 91% of the 1,500 executives surveyed indicated that their organizations plan to implement edge computing strategies within five years. IBM Edge Application Manager, an autonomous management solution that runs on Red Hat OpenShift, enables the secured deployment, continuous operations and remote management of AI, analytics, and IoT enterprise workloads to deliver real-time analysis and insights at scale. The introduction of Intel® Secure Device Onboard (SDO) made available as open source through the Linux Foundation, provides zero-touch provisioning of edge nodes, and enables multi-tenant support for enterprises to manage up to 40,000 edge devices simultaneously per edge hub. IBM Edge Application Manager is the industry’s first solution powered by the open-source project, Linux Foundation Open Horizon.

Exium is part of IBM’s partner ecosystem, collaborating with more than 30 equipment manufacturers, networking, IT & software providers to implement open standards-based cloud-native solutions that can autonomously manage edge applications at scale. IBM’s partner ecosystem fuels hybrid cloud environments by helping clients manage and modernize workloads from bare-metal to multicloud and everything in between with Red Hat OpenShift, the industry’s leading enterprise Kubernetes platform.

About Exium:

Exium is a U.S. full-stack cybersecurity and 5G clean networking pioneer helping organizations to connect and secure their teams, users, and mission-critical assets with ease, wherever they are.

To learn more about Exium, please visit

About Farooq Khan, PhD:

Before founding Exium, Farooq Khan was founder and CEO of PHAZR, a 5G Millimeter wave radio network solutions company that was sold to JMA Wireless . Before that he was the President and Head of Samsung Research America, Samsung’s U.S.-based R&D unit, where he led high impact collaborative research programs in mobile technology. He also held engineering positions at Bell Labs, Ericsson and Paktel.

Farooq earned a PhD in Computer Science from Université de Versailles Saint-Quentin-en-Yvelines in France.  He holds over 200 U.S. patents, has written over 50 research articles and a best-selling book.

Emerging AI Trends In The Telecom Industry

by Harikrishna Kundariya, CEO at eSparkbiz Technologies


Artificial Intelligence (AI) is a technology that has the potential to shape our future. Today, almost all business verticals are utilizing AI in one way or another. AI is a large field, and there are many things yet to be researched, but it’s definitely been ground-breaking for many industries. Daily new research findings are emerging.  Most of these have shown how AI can help businesses improve operations and be more productive.

AI is a black box for some, whereas it is a portal to unlocking great potential for others. Most businesses have started adopting AI as much as they can. It is predicted that by the end of 2023, companies will spend $10.83 billion on AI and automation.

Considering AI’s involvement in every business sector, the telecom industry isn’t far behind. Telecom companies are doing their individual research on AI to improve their business models. Using AI, it is easier for telecom companies to make accurate decisions. Moreover, with the right predictions from AI systems, they can get an insight into their decisions before they implement them in real life. Using AI’s predictive capabilities, telecom companies can get an edge over their competition.

To sustain the competition, businesses try to adhere to market standards and trends. Trends justify the changes that are widespread and followed by everyone to gain some benefits.

Here are some trends that are up and coming in the telecom industry.

Improve telecom network maintenance:

Telecom network maintenance is essential. When a network goes down, it is not only the users who suffer, but the telecom company also suffers a more significant loss. Loss of network shows the company’s insincerity towards its services and lack of care for its customers. The business also suffers monetary losses due to network breakdown. If there is some significant fault, the company has to get it rectified quickly, and this is costly too.

Hence AI is being used to overcome this problem. With AI, telecom companies can quickly identify the point of failure. Most of the time in network maintenance is spent behind finding the first point where maintenance is needed. With the availability of AI, it has become easy. Moreover, telecom companies are also leveraging IoT, which is a great technology.

Companies are looking forward to developing context-aware AI systems. Such AI systems are brilliant and can identify their state quickly. These systems follow the observe-orient-decide-act model to make decisions.

Using AI, downtime can be minimized. Moreover, the maintenance work can be carried out quickly by benefitting from context-aware systems and IoT processes.

Many companies are carrying out network maintenance with the help of drones. Comarch is one such company that creates solutions for telecom network maintenance with the help of AI-enabled drones.

Optimize network performance:

Network performance is vital if you want to be in the market. No user prefers a slow network. If your telephone towers are weak, you’ll face difficulty in adding new customers as well as maintaining the current ones.

There are many solutions for optimizing network performance. With the advent of AI, telecom service providers are using AI to optimize their networks.

One of the most common ways in network optimization is to predict network traffic and usage based on past conditions. AI can find out trends based on past data. These trends can then be used to create strategies to serve customers in a better way.

Telecom service providers create intelligent AI and ML systems that can accurately predict network traffic for any region. The results generated from AI systems are pretty accurate, and companies use those to optimize network performance. Usage data for any area is freely available with the service providers, so they can use this data to benefit.

Network performance can be optimized by increasing a tower’s capacity and range during certain peak hours when the area has high usage. Also, it can be decreased at a later stage to accommodate lower traffic levels.

Using AI, network performance can be controlled just like a remote-controlled device. The service providers are loving this benefit; hence AI is being used extensively. Many companies like AT&T and other telecom leaders are using self-organizing network technologies. These technologies have AI at their base and can work effectively under heavy traffic conditions.

Taking network performance a step ahead, Intel and Capgemini have tied up hands to develop a one-of-a-kind solution. These companies are already working on increasing the 5G spectrum’s capacity. Their project macaroni aims to boost a customer’s network experience by using real-time predictive analytics. Using this AI solution, every cell phone tower can handle more traffic than before, ultimately resulting in better network performance under a heavy customer base.

Improve network security/authentication:

Security is a big concern in the telecom industry. Tower Hijacking, wiretapping, and call forwarding pose a severe risk to the telecom business. To secure the user’s data from theft and cyberattacks, telecom service providers are using new and unique techniques. Many of these techniques include AI at their base.

AI can be used to authenticate users and also provide security to towers. When users sign up for a new connection, the chances of fraud are highest. They can use fake addresses, proofs, images, and any other thing. Identifying these fake things manually is nearly impossible. Hence, telecom companies are using AI to authenticate new users.

AI systems are being trained to spot fake documents. There are specific characteristics of fake documents that are well known. AI systems are trained to identify such characteristics on documents. When they reach a certain confidence level, they are used in everyday authentication work to ensure that no imposter is served.

Towers can be secured by using preventive AI technologies. These models are trained to look for defects in the towers every now and then. Sometimes the systems try to attack the towers to test the security procedure’s working. Using AI, it is easy for telecom companies to find towers in need of security. Such towers can be found by constantly monitoring and reporting if even a slight change is found in the tower’s characteristics.

End-user data protection is important because today, hackers are more active than ever before. Moreover, hackers are targeting places like telephone company’s databases where they can get a lot of personally identifiable data easily.

Many telecom service providers in the US are already using’s network security solutions. Companies like Verizon, AT&T, and Charter communications rely on AI services from to secure their networks. has a unique offering named Sentry that can process large datasets in seconds. This AI system is well developed and it can make its own decisions regarding whether there is a security issue or not. Moreover, these systems are trained heavily with real-world data, so they can easily detect and take actions on unauthorized actions over a telecom network.

When AI is leveraged, the need for better standards increases. Hence, many telecom service providers use end-to-end encryption and other newly created security protocols and encryption standards. With suitable security systems, the data is fully secure and free from any interference.


There are many trends that are seen within the telecom industry, and AI constitutes the majority of them. The telecom industry is being modernized at a large scale, and so they are trying to include AI as much as possible in their business models. Above, you’ve seen the three major trends seen in the telecom industry. These are the ones that are now becoming benchmarks for the telecom industry.



About Harikrishna Kundariya:

Mr. Harikrishna Kundariya is a serial entrepreneur leading eSparkBiz since 2010. Under his leadership the company has built its reputation as an excelling offshore development company. He values building relationships with clients rather than just focusing on the business at hand.



Juniper CEO: Cloud and AI-driven strategy: #1 in Cloud WAN routing

“Ultimately cloud is not just a market segment. When people think cloud, they think AWS, Azure and Google. Certainly, these are companies that have built their entire businesses around cloud-service delivery models but I view cloud as a way of life for every customer across every vertical. CIOs of enterprises wake up in the morning and wonder how they are going to protect their companies from disruption that’s happening outside of their four walls and do so while they don’t really have unlimited budgets and most of their employees are stuck in just keeping the lights on. Up to 80, 90% of the IT of an enterprise company are just keeping status quo running. That’s not a recipe for success,” said Juniper CEO Rami Rahim.

Expansion into Cloud Majors is a priority as it’s seen as the growth driver of enterprise digitalization:
– Accelerated enterprise shift of workloads into public clouds
– Direct Cloud connectivity drives growth in MX edge routers
– Two-sided business opportunity: Cloud + Enterprise WAN
Growth driver of 400G core upgrades
– Comprehensive 400G fixed & modular platform portfolio
– Investment in custom, high-performance Triton silicon for 400Gb/sec
• >100 customers for 400Gb/sec WAN solutions

Speaking at the JP Morgan 49th Annual Global Technology, Media and Communications conference today, Rahim said that the company’s enterprise business has never been as strong as it is today and he attributes much of that strength to the company’s AI-driven enterprise strategy.

“AI-driven enterprise is not just a marketing slogan,” Rahim said. “There is technical substance. We have an AI engine that drives the solutions that we are offering customers today,” he added.

Much of the company’s AI-driven enterprise strategy is a result of its 2019 acquisition of Mist Systems, which had an AI-powered wireless platform that Juniper then used to enhance its own networking solutions.

“We’ve been taking share [from competitors] in the face of meaningful headwinds,” Rahim said. “I expect once those headwinds lessen as we emerge from Covid, we will see even more improved dynamics.”

Juniper said that it plans to extend that AI-driven focus to other areas of its business, such as SD-WAN. Juniper purchased 128 Technology last October for $450 million and is in the process of combining 128 Technology and Mist’s AI capabilities into its SD-WAN solution.

Rahim said that he believes Juniper’s IP routing and transport business will see the most opportunity because the move to 5G will mean more traffic from the radio access network (RAN) to the transport network and the cloud.

Security is also a potential area of growth from 5G investments. Rahim said that future 5G networks are going to be more prone to threats, and service providers will need to invest in more high-end security.

He also said that Juniper projects that its service provider business will grow close to 2% for the full year with the revenue increasing 17% year over year.

On the supply chain front, Juniper executives warned during the company’s first quarter earnings report last month that it could be negatively impacted by the ongoing semiconductor shortage.  Those shortages are still a concern, the company said, noting that it will continue to need extended lead times for products through the rest of the year.


Highlights of AT&T CFO and CTO remarks at Morgan Stanley Investor Conference

Network quality driven by significant investments in 5G and fiber:

AT&T believes that its recent and anticipated network investments will bolster its network foundation to compete as the need for high-quality connectivity only continues to increase.  At a Morgan Stanley European Investor Conference, AT&T CFO John Stephens indicated that AT&T’s integrated fiber strategy is expected to improve the company’s connectivity offering for both consumer and enterprise markets and enhance its 5G network quality in a cost-efficient manner.

COVID-19 Impact:

AT&T CTO Andre Fuetsch said:  “Obviously what happened was everyone basically started working, started schooling from home, and all of a sudden we had to readjust our lives to work from home, learn from home, and all of a sudden we had to adapt very quickly to that.  Within our homes, we had to have these different personas that we normally don’t do — whether it’s doing your day job, performing that duty, helping your children get online so they can do their schooling, and then all the other things in life. That was a blurring, in a way, of these sort of enterprise and consumer segments coming together.”

“All of this technology is great, but at the end of it, we are humans and anything we can do to help facilitate [and] build better, stronger human connections” will benefit society at large, Fuetsch added. “This year we’re really getting pushed and challenged to do that. I really think this type of technology is just going to make things better.”

Artificial Intelligence (AI) Improves Operations:

Some of these technologies, like Artificial Intelligence (AI), are already helping AT&T improve its operations, especially among its field technicians, he said, noting that AT&T’s entire routing and scheduling program relies heavily on AI.

“Any given day we have 35,000 network technicians driving around in trucks installing, and repairing, and maintaining our network. It’s essentially a very complex logistics algorithm and, as you can imagine with a company of our scale, just a single percentage improvement in efficiencies can lead to big, big dollars,” Fuetsch said.

AT&T is also trialing the use of drones with computer vision analytics to help improve inspections of its roughly 70,000 cell sites. When those drones take flight, they are scanning towers, looking for excessive heat dissipation, corrosion, loose cables, and bird nests, among other signs that indicate a required repair.

“All of this is getting fed back into a neural network, which is basically AI based,” and that program identifies the repair checklist, the technician and skill sets required, and the parts needed to remedy the problem, Fuetsch said.

AT&T’s experiences here and elsewhere gives him confidence that “the camera is still and will be the killer app” for the foreseeable future. However, the use of cameras is undergoing dramatic changes, he said.

“We carry about 400 petabytes a day across our network. About 50% of that traffic we carry is video traffic. Most of that is going out in a sort of downstream way. The future is going to be about upstream,” Fuetsch said.

Use of Video Cameras:

Fuetsch envisions new applications that “can help better manage our lives through a simple video camera” with the aid of video analytics and sensing. These advancements are occurring not just despite the scourge of COVID-19, but rather because of it in some ways as well, he said.

“This pandemic has really created some new norms here. I think the good news for operators is connectivity is so important and so relevant for everything we do. As we go into 2021, certainly with hopefully a light at the end of the tunnel here in terms of the pandemic with the latest news we’re hearing about vaccines, I’m actually very optimistic.”

“As we go into 2021, certainly with hopefully a light at the end of the tunnel here in terms of the pandemic with the latest news we’re hearing about vaccines, I’m actually very optimistic,” Fuetsch added.




COVID-19 has changed how we look at telecom infrastructure, cloud and AI

by John Strand, Strand Consult, Denmark; edited for clarity by Alan J Weissberger

The coronavirus (COVID-19) crisis has proven that telecom infrastructure is critically important.  Telecommunications networks delivered service during the lockdown, enabling many to continue to work, learn, shop, and access healthcare.

Policymakers will likely revisit regulation for telecom networks, not only to optimize network investment, but to improve security. Indeed, policymakers will also realize that security which has focused to date on the transport layer of networks is leaving the access and applications layers vulnerable.

While the focus on Huawei is long overdue, the discussion of network security and Huawei’s role are oversimplified. It is insufficient to address only one aspect of conventional components of networks: access, core, and transport.

The bigger issues are how end-user data will be protected while stored in the network/cloud and processed by artificial intelligence (AI) agents?  Also, how will connected devices on Internet of Things (IoT) networks and other applications (such as smart city solutions) can be secured?

Historically network connectivity was likened to the dumb pipe, the medium which transmits data. The “smart parts” of the network were the edge and the core, where users access networks and where information processing occurs. These actions have become more complex with third party providers of AI and cloud computing. Naturally, these models don’t fit 5G because intelligence must exist throughout the network.  However, telecom regulation has been associated with these three traditional functions.

Now that networks have evolved, it’s time for telecom regulation to evolve. If the goal of security measures is to reduce the risk and vulnerability of exposure to Chinese state-owned and affiliated firms, then policymakers need holistic frameworks that address the multiple aspects of network security at its various layers: application, transport, and access.

Indeed, the singular focus on Huawei in connectivity misses the fact that Huawei sells products for the other layers, and that many other Chinese state-owned firms should be scrutinized. For example, Baidu, WeChat, Alibaba, and Huawei provide AI solutions in the Applications layer; Huawei and ZTE in transport; and Huawei  smartphones and laptops by Lenovo  (the world’s leading maker of laptops as well as a leader in servers).

Strand Consult has described this in the research note The debate about network security is more complex than Huawei. Look at Lenovo laptops and servers and the many other devices connected to the internet.

The EU’s 5G Toolbox is the first step towards greater security and accountability for a discrete part of 5G network transport, but it does not address all elements of 5G security nor other layers.  In performing its security assessment, the United Kingdom looked beyond 5G mobile Radio Access Networks (RAN) and Core to other network layers, types and technology, notably wireline networks. Policymakers need a broader focus than 5G when assessing the security of telecommunications networks in the future.  Policymakers need to look at Huawei’s movement into cloud and AI solutions in the application layer as well as the many state-owned Chinese firms in the access layer like Lenovo.

In China, Huawei is vertically integrated and delivers a suite of products and services for all the layers of a network: it transports the data; it provides access through end user devices, and it provides the applications in the form of AI and cloud solutions. While European policymakers debate issues of RAN and core, Huawei is busy selling other solutions for the rest of the network: smartphones, routers, AI, and cloud solutions. As restrictions tighten on Huawei’s network products, the company will naturally push other business lines to compensate for lost revenue. A large operator in Europe works with Huawei on a joint Chinese-German cloud platform, and the reference customer for this solution is the European Organization for Nuclear Research, CERN in Switzerland. It is not logical how Huawei which can be deemed high risk for telecommunications and military networks, but somehow neutral for nuclear research. The agreement for the project is four years old; the question is whether such a project will be acceptable for political and security standards going forward.

Vertical integration was the standard model for traditional state-owned telecommunications. The government built a telephone network (the wires and switches); it delivered a single service – telephony; and it sold the end user device, typically a classic phone. Privatizing networks was about opening up the value chain to different kinds of providers. This worked well in mobile networks; different firms specialized for different parts of the value chain. However, Huawei is driving the decentralized chain back to the state-centered concept, perhaps fitting for its practice in China where it partners with the government to deliver full-service surveillance solutions.

Policymakers, regulators, and competition authorities have long been skeptical of vertical integration in telecommunications, and it was frequently a way to control traditional telecom operators by demanding that the divest certain parts of their business or by prohibiting certain acquisitions.

COVID-19 has proven that telecommunications networks are vital infrastructure at all layers and levels. It’s not just military and public safety networks that need to be secure. Everyone needs to have secure networks if we are live in a digital society. If politicians and telecom operators don’t recognize this, network users do. Change is being driven by companies which themselves are increasingly victims of cyber-attacks. Companies are putting increased pressure on telecom operators and governments to do more to make networks secure.

John Strand | New Europe

John Strand of Strand Consult


Six big issues on the future of telecom regulation:

Strand Consult believes that governments will take a broader view about network security. Here are six categories of issues for policymakers to consider.

  1. What is critical infrastructure, and how will it be defined in the future? Historically, critical infrastructure had to do with physical and digital network assets which are required for physical and economic security, health, and safety. Indeed, there are many vital network assets deemed “critical” including those for chemicals, communications, manufacturing, dams, defense, emergency services, energy, financials, food/agriculture, government facilities, healthcare, information technology, nuclear reactors, transportations systems, and water/wastewater. Are these networks equally prioritized? What are the security concerns and protocols for each, both on the physical and cyber fronts? Do some have greater security than others? How does this change in the COVID-19 world?
  2. What are the government’s responsibilities to ensure the security of communications infrastructure?What are the minimum requirements to restrict a vendor? How is this balanced with requirements for fair and open processes for bids and tenders?
  3. What are the relevant communications networks to secure? Is it enough to focus on 5G mobile RAN and core or should security requirements apply to wireline networks, satellite, Wi-Fi, 3G/4G and so on?
  4. Is it sufficient only to address the transport element of network security? How will security be ensured for the storage and processing of data, for example on the computers, laptops, and servers provided by Chinese state-owned Lenovo where China’s rules for surveillance and espionage also apply? What about apps like TikTok and Huawei’s AI and cloud solutions?
  5. Who should perform the security assessment? Telecom operators, military departments, intelligence agencies, private security consultants, law enforcement, or some other actor?
  6. How will shareholders account for increased security risk in networks? Have shareholder asked relevant questions about operators’ security practices and the associated risk?

Strand Consult believes it is dangerous for telecom operators to make the decision about Huawei themselves without involving the authorities.

There are a lot of arguments for why telecommunications companies should involve the competent and relevant authorities. Telecom operators must understand that If telecommunications companies assume responsibility as those who assess each supplier in relation to national security, they will be held responsible when things go wrong.

When you take on a responsibility, you also take on risk. Thus, shareholders are exposed to increasing risk when using high risk vendors. The historical facts show that telecommunications companies have been wrong in the past when assessing cooperation with partners which have proven to be corrupt. Some partnerships have cost shareholders billions of euros. In practice, operators are limited in their ability to judge whether partners and vendors are trustworthy.

Strand Consult’s research shows that is not only government, intelligence, and security officials who are concerned about companies like Huawei. Nor is it just telecom operators which build and run networks. It is the small, medium, and large enterprises that use networks that fear that their valuable data will be surveyed, sabotaged, or stolen by actors associated with the Chinese government and military. Consequently, it is the clients of telecom operators which push to restrict Chinese made equipment from networks. This is described in this research note, The pressure to restrict Huawei from telecom networks is driven not by governments, but the many companies which have experienced hacking, IP theft, or espionage.

What the future looks like – just ask the banks:

If you want to see the future of the telecom industry, look at what happened with banking. European banks have been required to implement Anti-Money Laundering (AML) and the Counter Terrorist Financing (CFT). About 10% of European banks employees are today working with compliance. Telecom authorities, defense officials, and other policymakers and will likely see cybersecurity is vital for Europe and that telecom infrastructure is critically important. So just as the banks have been put under a heavy regulatory regime to address corruption and financial crimes, the telecom industry will be required to implement deterrence of cyberattacks.

In practical terms, the authorities in the EU and in each nation state will likely make some demands that challenge the network paradigm that telecommunications companies operate today. The rules will likely be so rigid that they will effectively eliminate Huawei and other Chinese companies from being vendors without making explicit bans. However, it won’t be governments alone driving the charge. Corporate customers of telecom networks, companies that have experienced hacking, IP theft, or espionage, will also join the effort. This is described in this research note, The biggest taboo in European telecom industry is the cost of cybersecurity – just ask the banks.

Copyright 2020. All rights reserved


About Strand Consult:

Strand Consult, an independent company, produces strategic reports, research notes and workshops on the mobile telecom industry.

For 25 years, Strand Consult has held strategic workshops for boards of directors and other leaders in the telecom industry. We offer strategic knowledge on global regulatory trends and the experience of operators worldwide packaged it into a workshop for professionals with responsibility for policy, public affairs, regulation, communications, strategy and related roles.

Learn more about John Strand:

Learn more about Strand Consult:

Strand Consult
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Copenhagen 1117 K

Juniper Research: Network Operators to Spend Billions on AI Solutions

A new study from Juniper Research has found that total network operator spending on AI solutions will exceed $15 billion by 2024; rising from $3 billion in 2020. The research identifies network optimisation and fraud mitigation solutions as the most highly sought-after AI based services over the next 4 years. AI-based solutions automate network functionalities including routing, traffic management and predictive maintenance solutions.

For more insights, download our free whitepaper, How AI Analytics will Boost Operators’ Revenue.

Network Optimisation & Fraud Prevention Driving Adoption in Developed Markets

The new research, AI Strategies for Network Operators: Key Use Cases & Monetisation Models 2020-2024, found that operators in developed regions, such as North America and Europe, would account for over 40% of AI spend by 2024, despite only accounting for less than 20% of global subscribers. It predicts that growing demand for operational efficiencies will drive operators in these regions to increase their overall investment into AI over the next 4 years.

The research urges operators to embrace a holistic approach to AI implementation across service operations, rather than applying separate AI strategies to individual use cases. It suggests network operators leverage AI to unify internal data resources and encourage cross-functional insight sharing into network efficiencies to maximise the benefits of collaboration across internal teams.

Image result for pic of ai in telecommunications

The research predicts that AI spend by Emerging Markets operators will exceed $5 billion by 2024, rising from only $900 million in 2020. It found that this growth will be driven largely by operators exploring early use cases of AI before expanding the presence of AI in their networks to include more comprehensive services.

The report forecasts that Indian Subcontinent and Africa & Middle East will experience the highest growth in spend on AI services, with operator spend in both regions forecast to grow over 550% over the next 4 years. It anticipates that operators in these regions will initially invest in AI-based CRM (Customer Relationship Management) solutions that yield immediate benefits.

Related post:

Market Research Firms say Telcos Need to Invest in AI now!



Market Research Firms say Telcos Need to Invest in AI now!

Due to ever increasing demand for data, saturated mobile markets, and stiff opposition from cloud companies,  global telecom network providers are facing difficult times. These market pressures have led to vicious price wars for mobile services and, as a result, declining average revenue per user (ARPU).  This is especially true in India where Vodafone Idea and Bharti Airtel have recently announced huge losses, write-downs as their share prices collapsed.

Mobile revenue


Artificial Intelligence (AI) use in Telecommunications:

For many global telecoms, shoring up market share under today’s pressures while also future-proofing operations means having to invest in AI. The telecom industry is expected to invest $36.7 billion annually in AI software, hardware, and services by 2025, according to Tractica.

Through its ability to parse large data sets in a contextual manner, provide requested information or analysis, and trigger actions, AI can help telecoms cut costs and streamline by digitizing their operations. In practice, this means leveraging the increasingly vast gold mine of data generated by customers that passes through wireless networks — the amount of data that moves through AT&T’s wireless network has increased 470,000% since 2007, for example.

AI applications in the telecommunications industry use advanced algorithms to look for patterns within the data, enabling telcos to both detect and predict network anomalies, and allowing them to proactively fix problems before customers are negatively impacted.

Image result for images: AI in telecommunications

Some forward-thinking telcos have focused their AI investments on four main areas:

  • Network optimization
  • Preventive maintenance
  • Virtual Assistants
  • Robotic process automation (RPA)

In these areas, AI has already begun to deliver tangible business results, according to blogger Liad Churchill


Meanwhile, a Tractia report on AI for Telecommunications Applications identifies the following functions which will benefit from AI:

  • Network Operations Monitoring & Management
  • Customer Service & Marketing VDAs (Voluntary Disclosure Agreements)
  • Intelligent CRM Systems
  • Customer Experience Management
  • Cybersecurity & Fraud Mitigation
  • Other Use Cases


Here are a few takeaways from the AI in Telecommunications report by Business Insider Intelligence:

  • Telecoms have long struggled with their customer experience image: In 2018, telecommunications had the lowest average Net Promoter Score (NPS), a measure of how favorably a company is viewed by customers, of any industry.
  • Companies that use advanced analytics, which can be accessed via AI, to improve this image and the overall customer experience are seeing revenue gains and cost reductions within a few years of adoption.
  • Most (57%) executives believe that AI will transform their companies within three years, per Deloitte’s State of AI in Enterprise.
  • Overall, telecoms should focus on a hybrid organizational model to move beyond pilots to launch full-scale AI solutions that can have the biggest impact on their companies.


Artificial Intelligence for Telecommunications Applications


GSMA, China Telecom & Huawei on 5G; GSMA says 40% of the world’s population will be on 5G by 2025

Mats Granryd, the Director General of the telecom trade organisation GSMA talked up  5G and AI in a keynote speech on “intelligent connectivity” at Huawei’s MBB 2018 event at London’s ExCel.  Granryd said those two emerging technologies will be key enablers for what the telecom industry has to offer in the years to come.  Granryd discussed the potential of 5G to drive inclusion, growth and sustainable development, especially in the developing world. He also touched on the impact of “smart” capabilities like artificial intelligence and network capabilities, and how such networks and technologies must be secure to drive the growth not only of smart cities, but all cities. He said intelligent management will be key with “the development of a rich and vibrant digital economy.”

In addition to predicting that 70% of the world’s population, or roughly 6 billion people will be on mobile internet, GSMA forecast 40% of the world population will be on 5G networks. When it comes to AI, on top of improving individual experience (e.g. Personal Assistants) and serving new industry needs (e.g. network slicing), Granryd highlighted what the combined AI capabilities can do for society. The GSMA’s “Big Data for Social Good” initiative has launched in seven countries around the world. Mobile operators in those markets have worked with local partners to enable air pollution warning, malaria spreading prediction, and natural disaster preparedness, using big data and machine learning and prediction capabilities.

Guiqing Liu, EVP of China Telecom, the world’s largest integrated operators in the world by subscriber number, then took the stage to share what China Telecom saw as the biggest opportunity for telecom operators to undertake the digital transformation, especially with the ascendancy of industry markets. Liu included four key capabilities the industry in particular the operators need to master to succeed in the transformation. They are:

  • End-to-end slicing to cater to different user and industry needs;
  • FMC (Fixed to Mobile Convergence) edge computing to deliver seamless experience;
  • 5G+Cloud based network and services to provide flexible and special customization; and
  • 5G+AI to both optimise service delivery and network management.

Liu also outlined the key challenges the industry is facing before 5G can become a real commercial success. He conceded that use cases now are still very much focused on eMBB, and the industry has not thought through how to change business models in the new era, including how to bill customers for the new use cases. On network challenges, in addition to the CAPEX and OPEX and skill gap, Liu also pointed the indoor coverage weakness intrinsic of the high frequency bands most 5G networks will be built on.  For 5G to truly be transformative and improve people’s lives, Liu said that companies will need to work together and collaborate – even if they’ve traditionally been rivals.

Ken Hu, deputy and rotating chairperson of Huawei stressed the importance 5G was already playing in shaping the future of not only business, but humanity, adding Huawei has been working on 5G for more than 10 years. “We believe 5G will make a big contribution to our society.”  Hu also said 5G was leading to the integration of previously separate technologies and services not unlike individual pieces of Lego bricks being combined to make something larger – fundamentally changing the definition of what a telco or technology company is. The user experience will be redefined by 5G.”


Outside the main presentation halls, a number of booths showcased both Huawei technologies and those from  Huawei partners. A “5G bus” drove people around the surrounding Docklands area. The demo drive showed that 5G connections, download speeds and more could all be achieved while physically moving across large distances at a high speed and in poor weather (this being London, it was fittingly rainy, windy and cold). Tents erected outside ExCel London were also stuffed with 5G use case demonstrations.



SVIEF Kai-Fu Lee Keynote: Era of AI, Rise of China, U.S. vs China, etc & All Star Panel Session (?)

Well respected technologist, entrepreneur, writer and AI researcher Kai-Fu Lee, PhD presented a powerful and very incisive keynote speech on September 29th at the SVIEF conference in Santa Clara, CA.  The title of his talk was all encompassing and compelling:  “Era of AI, the Rise of China, and the Future of Work.”

Author’s Note: I was so impressed with Kai-Fu’s talk, I’ve ordered his latest book, AI Superpowers, which is already on Amazon’s best selling book list.


Here are several important highlights of Dr. Lee’s SVIEF keynote:

1.    Deep Learning (DL) is the biggest technological improvement in the 60+ year history of artificial intelligence (AI).  DL is a network of highly connected neurons in thousands of layers that can, in a single domain, take a huge amount of data and train to recognize, predict and decide and synthesize at a much higher accuracy than humans.

2.    DL is not human intelligence, it cannot think or cross domainsIt has no strategic or creative thinking capabilities. But in a single domain, with a huge amount of data, it is beating humans in almost every task imaginable. For example, AlphaGo (a computer program that plays the board game Go) has beaten Go champions. In addition, we’ve seen DL used effectively for speech recognition (e.g. Amazon Alexa, Google voice search, Microsoft Cortana, etc.) and facial recognition. There are new beginnings  of DL diagnosis of how to read  MRIs and doing a better job of that than radiologists. 

3.   This amount of improvement is leading to what are four waves of artificial intelligence:

  • Wave 1: Internet AI started in 1998. The Internet has more data than any other domain. With so much data, it enables Amazon to predict what you might want to buy. It powers Facebook to predict what you might want to read on-line.   Similarly, all the American and Chinese companies (Alibaba, Baidu, Tencent, etc) , all the great AI companies of today are all Internet companies, because they have the most labeled data.
  • Wave 2: Business AI started in 2004. Take banks, insurance companies, hospitals –they have amassed a lot of data in the past, they viewed data as a call center, as a legal requirement to archive. But now data has become a goldmine for them in various ways.
  • Wave 3: Perception AI started in 2011- the ability to see and hear.  Examples include: computer vision, speech recognition, speech synthesis, understanding all combined together. It also can be viewed as digitizing the physical world.
  • Wave 4: Autonomous AI (self driving cars, autonomous robots, etc) started in 2015.  In this wave 4, AI becomes autonomous in its ability to move around and manipulate sort of like having hands and feet. That will usher in an era of autonomous vehicles and robotics. Autonomous vehicles will bring about a huge transformation, especially the dis-incentive to own a car.  With safer autonomous vehicles, the natural next step is humans won’t be allowed to drive anymore.

4.    To make AI work, we need the following things:  a lot of data that is tagged within a single domain, a lot of compute power, and some AI experts to work on it.

AI is not perfect you can’t make it do perfectly unsupervised learning. You can’t make it learn on very little data. You can’t do AI with very little compute power.  

But once you have those in place, AI can be effectively applied.  

5.   U.S. Leads China in Top Researchers, Patents, and AI Talent (and will likely continue to lead in AI research in the near future).

6.    Chinese Miracle of Last 10 Years with fast product/service iteration, intense competition, user acquisition, accelerated growth, high return on investment in a huge market.

7.   In 2018: U.S. and China Have Become Parallel Universes:

US Model: Breakthrough Technologies, Vision-driven, Light, Globalized.

China Model: Fusion + speed, Applications, Result-driven, Heavy, Localized.

8.  Investment in China:   A lot of money and capital investment went into China with smart VCs helping smart entrepreneurs build products and companies. And those products actually are so attractive they brought more Chinese users on the internet. And this loop kept going and going for the last 10 years taking China from 150 million users to about 800 million users by far the largest user base in the world. And this loop has created something that we never thought possible — a system that parallels the Silicon Valley.

9. The only way to succeed in China is to find a business model that is impregnable. In other words, build a business that’s uncomfortable.  Chinese companies kept improving going from copying from the U.S. to inspired by us and then leapfrogging the U.S.  For example, WeChat (messaging app) is better than WhatsApp and way better than Twitter.  But even more exciting is the third ladder where Chinese companies are brand new innovation, this Chinese model of building impregnable businesses have reached new heights, so that these brand new companies are being built.

10.   China Advantages over U.S. in AI:

Advantage 1: Chinese Product Innovation has Caught up with U.S.  Pure Chinese Innovations Have Arrived

Advantage 2: Tough Market Begets Tough Entrepreneurs

Advantage 3: China’s AI Capital Leads the World.  48% of global AI investments were made in China; 38% in U.S., 13% other countries. SOURCE: CB Insights 2017 Global Artificial Intelligence Investment

Advantage 4: AI Moves into Era of Implementation

Advantage 5: China is the world leader in amount of Data  (like Saudi Arabia is the country with the most oil for export).  Massive Data is Critical for AI Product Success– even more important than algorithms.  AI algorithms are generally shared, and it is up to the speed, execution, and size of the data that determines how companies will benefit from AI implementations.

11.  U.S.  Advantage over China in AI:  Early Adopters, Expert is King  (vs China which is Application Driven and Data is King)

12.  Who’s ahead in AI, mobile and Internet:  Dr. Lee thinks that generally U.S. is a little bit ahead today. But China will probably be ahead in four or five years. This is not about research. This is about implementation. 

U.S. will continue to be ahead in research for the next 10 or 15 years, because that lead is very difficult to overcome.

But this is not a zero sum game. U.S. VCs fund U.S. companies that develop products for us customers, whereas Chinese VCs fund Chinese companies who develop products for Chinese customers (domestic market).  The two countries are not going after the same market.  

“When a Chinese company wins, a  U.S. company does not lose.  When a U.S. company wins, a Chinese company does not lose. So I think the sentiment behind the current some of the current rhetoric is not correct. This is truly not a zero sum game. This is merely a keeping score of how far ahead each technology might get. So with China and us both pushing forward AI, I think AI will make a lot more progress than internet and mobile because those only had one engine the U.S. pushing forward. And there are a bunch of other reasons such as the seven cloud giants (Amazon, Google, Facebook, Microsoft, Alibaba, Baidu, Tenent) hiring people, and training people with large amounts of data VCs being devoted to AI.”


Concluding take-aways:

  1.  Embrace AI – it saves us from repetitive work and pushes us to do what human is called for.
  2.  AI cannot create ideas or thoughts. We are the masters and should be responsible of how to use AI.
  3.  (via Twitter) How U.S. can stay ahead in AI: 1) double AI funding, 2) increase AI professors pay, 3)offer green cards to all AI PhD’s.

Closing Quotes:

“So going forward, I think AI is electricity in the next 20 years, there will be huge opportunities and challenges. But I want to take us a moment into (the next) 50 years. When we look back ignore for the moment all these job displacement opportunities, I like to leave you with two thoughts. The first thought is that AI is serendipity. It is here to take away the routine jobs so we can really spend time on what we love and what human beings are on this earth for. And secondly, for those worry about AI causing problems. Just keep in mind AI is just a tool.  It possesses no creativity. We (humans) are the Masters.  We are the ones that have free will. And it’s going to be up to us humans to write the ending to the story of artificial intelligence. Thank you.”


In a post SVIEF conference email exchange related to AI’s use in telecommunications applications, Kai-Fu wrote this author:

“Thanks — this is not my major area of expertise.  But clearly communications in autonomous vehicles, IoT, and 5G, when combined with AI, will be a great combination.”

“On China catching up, it will be in technology related to the Internet, Mobile, and AI.”


SVIEF All Star Panel:

Kai-Fu Lee: “I feel a sense of social responsibility to tell people that as AI advances, job displacement is a serious issue. And I think I thought very hard about various solutions. I looked at universal basic income, I don’t think that’s going to work. I don’t really know what will work. But I do think generally, it’s in the direction of creating more empathetic jobs, because there should be a large enough pool of them, if only we would care about them, pay more for them. And that can hopefully lead us to a good ending.”

SVIEF All-star panel with VC Tim Draper, AI Rock Star Kai-Fu Lee, and Stanford Physics Prof. Shoucheng Zhang


Author’s Note:

Due to time and space constraints the above panel session may be summarized in a follow on article, provided there is sufficient reader interest.

Please email me at: if you’d like me to write such an article.


Transcript of Kai Fu Lee’s keynote (via speech recognition):