통신 업계용 AI 조사 서비스

ABI Research’s Telco AI Research Service provides guidance and insight into the telco Artificial Intelligence (AI) journey and the platforms used to enable AI, including competitive dynamics of public, hybrid, or private clouds for telco AI payloads. The service also covers core network technologies, virtualized and cloud-native platforms, and data related architectures that provide the necessary data for telco AI model training and inference.

Telco AI Coverage Areas

Our Telco AI Research Service coverage, which includes data, forecasts, and vendor benchmarking reports, provides industry-leading research and guidance on the transformation of the Mobile Network Operator (MNO) into a AI company. Cloud-native networks and Artificial Intelligence (AI)/Machine Learning (ML) topics include Generative Artificial Intelligence (Gen AI), virtualized platforms, and cloud-native technologies.

ABI Research exercises a sharp focus on business and operational transformation issues, in addition to technical coverage with a priority on helping telco operators address the emerging sovereign and enterprise AI domains.

• Market trackers and forecasts for telco AI deployments
• Telco platform datasets for public, private, and hybrid cloud deployments
• Competitive analysis, vendor benchmarks, and market shares for emerging AI and cloud-native areas, including public cloud deployments for telco network elements
• Regional trends for telco AI deployments
• Telco AI monetization strategies, including Graphics Processing Unit-as-a-Service (GPUaaS)
• AI use cases in telco networks, including network automation
• AI model lifecycle in telco: training, inference, and deployment at the edge
• Core AI readiness index for telcos
• Closed-loop automation potential in telco networks, from core to Radio Access Network (RAN)
• Telco AI vendor taxonomy from Operations Support System (OSS)/Business Support System (BSS) to radio
• Virtualized and cloud-native network deployment and implications
• Advanced telco cloud features: network slicing and service chaining
• Network slicing and 5G networks
• Open source and ecosystems in telco cloud
• Big data and ML for telco analytics
• Service exposure platforms

Telco AI Research Powers Technology Innovation & Implementation

For Innovators

• Bridge MNO with AI Infrastructure Capabilities: Provide clear insight into telco AI requirements and future evolution paths and deployment strategies.
• Identify Successful AI Deployments for Monetization: Identify how GPUaaS is being deployed by telcos and who are the leading operators around the world.
• Track Emerging Use Cases and Demand Signals for Telco AI Use Cases: Monitor how telcos aim to use AI to enable new services like network slicing and Application Programming Interfaces (APIs), and how they will utilize cloud-native platforms, and the public cloud to enable these.
• Evaluate Competitive Landscape: Offer detailed analysis of competitor strategies, differentiators, and market positioning to support strategic planning.
• Understand Which Technologies Will Become Mainstream and Which Ones Will Not: Identify which technologies to invest in for the telco AI domain and which to invest in for the long term.
• Inform Ecosystem Collaboration: Highlight key partners, platforms, and integrators driving enterprise connectivity adoption to guide ecosystem engagement strategies.
• Accelerate Time to Market: Support faster and more confident product development through access to current enterprise pain points, priorities, and deployment timelines. Optimize your telco AI strategy by understanding your customer pain points in detail.

For Implementers

• Clarify Technology Differentiators: By providing detailed analysis and insights into enterprise requirements for sovereign AI, telco implementers will be able to select the optimal deployment strategy.
• Understand Market Size and Future Opportunities: Through this service, telcos will be able to understand how big each technology domain will become, especially monetization-related technologies that are driven by AI and include network slicing and API platforms.
• Understand Which Vendors Lead in Critical Network Areas: Identify which vendors lead in the telco AI domain and which ones are likely to help mobile operators remain relevant in the highly competitive telco environment.
• Identify Which Technologies Will Sunset and When: The telco network is a patchwork of legacy technologies. Our service allows telco executives to understand which of these will likely be replaced or augmented by AI, helping them optimize their deployments.
• Assess When Closed-Loop Automation Will Take Place: Identify when network automation will be deployed and how it will progress from the current state of the market. This will allow implementers to choose vendors and which direction to follow for AI adoption.

Our Telco AI Research Helps Solve Real Business Challenges For Key Stakeholders

Cloud Providers

• What challenges can we help you solve?
  • Identify how to address opportunities in the telco vertical for AI.
  • Align cloud strategy with telco AI priorities.
  • Understand how telcos will evolve their cloud-related efforts toward 6G.
  • Identify what role telcos will play in the sovereign AI domain and how to partner or compete with them.
• What key questions can we help you answer?
  • How will telcos deploy AI capabilities in the public, private, and hybrid cloud domains?
  • What role will telcos play in the AI/ML domain, especially in Gen AI?
  • What is the dichotomy between public and private clouds in telco networks for AI?
  • How will 6G change AI dynamics in telco networks?

IT Vendors

• What challenges can we help you solve?
  • Understand how big the telco vertical will be for AI infrastructure.
  • Identify what platforms telcos will deploy, between x86, Arm, and Graphics Processing Units (GPUs) for AI at the edge.
  • Align telco investment strategies with infrastructure capabilities.
• What key questions can we help you answer?
  • Will telcos continue to deploy private clouds or shift to the public cloud for AI?
  • What solutions will help telcos manage their data center workloads in the future?
  • Will telcos continue to manage their networks or will they outsource a large part of their technology capabilities?

Telco Infrastructure Vendors

• What challenges can we help you solve?
  • Align product roadmaps with enterprise and telco AI needs.
  • Identify high-growth AI technology areas.
  • Differentiate infrastructure capabilities for telco AI in the context of Standalone (SA) and APIs.
  • Identify how hyperscalers and neoclouds will compete or cooperate with telcos for AI.
• What key questions can we help you answer?
  • How are telcos implementing closed-loop automation?
  • How big is the market for telco AI and which areas should vendors focus on?
  • How will strategies of Tier One vendors differentiate?
  • How will hyperscalers affect this technology domain?
  • What innovation will 6G bring to telco AI?

Telcos

• What challenges can we help you solve?
  • Improve telco AI deployment strategy.
  • Optimize network and AI vendor partnerships.
  • Identify telco AI innovation.
  • Assess viability of GPUaaS deployment and business models.
  • Identify if and when closed loop automation is viable.
• What key questions can we help you answer?
  • How fast will telcos adopt GPUaaS?
  • What is the evolution path of telco AI toward 6G?
  • What new AI concepts will make an impact on telco revenue?
  • Will telco APIs succeed?
  • How will AI enable network slicing and where?
  • Where should telcos focus regarding the core for AI applications?