Report:

Magic Quadrant for AI in CSP Customer and Business Operations

Top Vendor Products for AI in CSP Customer and Business Operations in 2024

• Amdocs
• AsiaInfo

AI in CSP Customer and Business Operations Vendor Product Comparisons 2024

• Amdocs - Leader
  

  Pros:

  • Amdocs' expertise and experience in the BSS domain provide a strong lever to the vendor to influence CSPs' customer and business operations through the application of various AI/ML technologies in a number of use cases.
  • Amdocs has partnerships with Microsoft, NVIDIA, Snowflake and Amazon Web Services (AWS) and investments in the application of generative AI as evidenced by its many patents filed covering low-code applications, autonomous operations and large language models (LLMs). It demonstrates several effective use cases of AI assistants across the customer life cycle.
  • It offers on-premises and cloud-based SaaS, along with component-based pricing, and it has deployed its AI solutions in several CSPs in Canada, Philippines, the U.S. and the U.K.

  Cons:

  • Amdocs has a greater focus on generative AI compared to other AI technologies. Besides generative AI, the vendor demonstrates primarily ML-based use cases only.
  • Amdocs' portfolio for AI and customer and business operations solutions comprises several products, frameworks and services. Some of these, such as Customer Engagement Platform, are specific-partner-oriented. Some others, such as amAIz are service-oriented. This makes the portfolio and fitment in a CSP confusing.
  • The vendor's AI strategy is heavily aligned with its BSS product strategy and therefore suited primarily for its BSS customers, where it offers several services to augment the CSP operations with AI capabilities. This approach may not suit CSPs not using Amdocs' BSS.


• AsiaInfo - Leader
  

  Pros:

  • AsiaInfo has the greatest depth of AI product capabilities among the vendors assessed in this Magic Quadrant project. Its product features strong capabilities for AI model development, AI model training and AI model life cycle management.
  • AsiaInfo offers commercial, deployment and service flexibility. It has tiered pricing and modular packaging options for customizable usage. It uses an aggressive pricing strategy, which is reflected in its relatively higher renewals in the market.
  • Reference customers surveyed for this Magic Quadrant report positive feedback on nearly all parameters associated with AI products and implementation by AsiaInfo. AsiaInfo is executing relatively larger projects with higher budgets.

  Cons:

  • Although AsiaInfo has operations in emerging Asia/Pacific and Europe, its major operations are still in the Chinese market. CSPs in other regions may find it difficult to leverage the capabilities of AsiaInfo.
  • AsiaInfo doesn't offer SaaS pricing outside the Chinese market, limiting commercial options with AsiaInfo for CIOs outside China.
  • Lack of ground operations (with people such as developers, architects and solution experts) in countries outside of China creates dependency on China operations. This mode of operation may not suit many CSPs.


• Comviva - Visionary
  

  Pros:

  • Comviva has been investing in foundational capabilities (both services and products) as well as ready-to-use models for a variety of use cases with the goal of supporting CSPs across their customer life cycle management.
  • Comviva has built an AI product suite covering ML models for customer value management (CVM), GUI-based workbench for faster model development, no-code application, and models' performance and life cycle management. These capabilities are integrated with many of its marketing, sales, BSS and other applications and are offered in various commercial models including, outcome-based.
  • The vendor has partnered with AWS, Microsoft, IBM, Teradata, Oracle, Cloudera Hadoop, Google Cloud Platform (GCP) and others to enable CSPs in various stages of AI implementation and to support interoperability of applications. It offers data readiness services supporting a wide variety of data environments.

  Cons:

  • Comviva has limited presence outside of the Southeast Asia, Middle East and Africa market. CSPs in developed markets may not find suitable customer references for Comviva in their regions.
  • Comviva's customer deployments of AI lie in mostly marketing and sales use cases in the emerging markets, overshadowing other areas of AI implementation across customer and business operations.
  • Comviva's product strategy and collaboration with its parent company (Tech Mahindra) is unclear, and even lacks uniformity in messaging.


• Flytxt - Niche Player
  

  Pros:

  • Flytxt's CLTV AI solution consists of ML models, a recommendation engine, generative AI and explainable AI that are integrated with its own marketing and CX solutions but can work with other such solutions being used by CSPs.
  • Flytxt brings expertise in implementations of AI use cases across product management, digital commerce, marketing, sales, customer service and privacy for customers in diverse markets.
  • It offers easy to subscribe API-based access to its AI product for a variety of use cases associated with customer experience and omnichannel marketing and uses subscription pricing as a commercial model.

  Cons:

  • Flytxt has limited expertise and experience considering the overall scope of its CSP customer and business operations. It doesn't have experience with use cases associated with billing, fraud management and revenue assurance.
  • It is a relatively small vendor with a limited revenue base through its specialized and productized use-case-based products. Its offering may not suit CSPs that wish to work with one/few vendors for a broader AI implementation in their operations.
  • The vendor has limited partnerships and capabilities with data readiness and managing the full life cycle of AI algorithms for its customers. Flytxt may not be the best fit for CSPs looking for comprehensive products and services across their BSS use cases.


• Huawei - Challenger
  

  Pros:

  • Huawei's expertise and experience in the communication industry provide a strong lever to the vendor to influence CSPs' customer and business operations through the application of various AI technologies in a number of use cases.
  • Huawei is one of the leading players in the large language model market, with a strong position in China. It has developed a telecom-focused LLM and use cases for the telecommunications industry.
  • Huawei's extensive R&D team, coupled with its global professional services arm, ensures prompt response to customer's AI-related demand.

  Cons:

  • Huawei's AI offerings primarily concentrate on CRM, contact centers, billing solutions and marketing campaigns, providing AI capabilities within specific products or services rather than a comprehensive AI portfolio supporting wider BSS use cases.
  • Huawei focuses on embedding AI capabilities into its products, but it lacks capabilities such as model development and life cycle management. CSPs looking for end-to-end AI development and management may not find Huawei as the best fit.
  • Huawei's AI sales strategy predominantly relies on traditional licensing, emphasizing service offerings. However, the absence of flexible business models, such as a SaaS option, limits CIOs' flexibility in engaging with Huawei.


• Subex - Niche Player
  

  Pros:

  • Subex's HyperSense line of products offers AI-led solutions for multiple telecom use cases, emphasizing its focus on innovation and AI integration in telecom operations.
  • Subex's strong expertise in fraud and asset management within the communications industry positions it to significantly influence customer interactions for CSPs by applying diverse AI technologies in these areas.
  • Subex's HyperSense AI studio, featuring drag-and-drop AI algorithm development, simplifies AI adoption for its customers, making it easier to integrate AI into their operations.

  Cons:

  • Subex has reported a net loss in recent financial results, which could indicate ongoing financial challenges that may impact its operations and growth strategies.
  • Subex faces challenges in the telecom AI market due to lack of a clear marketing and sales strategy. This impacts its competitive positioning.
  • Subex's limited support team and inadequate partnership strategies could limit its service and support efficiency and global expansion in the telecom AI market.


• Tecnotree - Niche Player
  

  Pros:

  • Tecnotree has a well-defined portfolio covering customer experience, revenue management, cataloging and trust. It also integrates third-party API deployment.
  • Tecnotree has a strong focus on investments and product feature development in customer experience, revenue management and TM Forum data models. It has also invested in DataOps and ModelOps.
  • It also offers a well-defined pricing model and modular packaging along with model as a service (MaaS).

  Cons:

  • Tecnotree has limited presence outside of the Latin America, Middle East and Africa markets. CSPs in developed markets, such as the U.S. and Europe, may not find suitable CSP customer references in their regions.
  • Tecnotree's AI deployments focus majorly on use cases associated with marketing and sales and customer journey use cases in the emerging markets. This overshadows other areas of AI implementation across customer and business operations.
  • Tecnotree, being a relatively small vendor with fewer Tier 1 CSP accounts, may face resource constraints in supporting additional large CSPs and large-scale AI implementation.


• Whale Cloud Technology - Visionary
  

  Pros:

  • Whale Cloud Technology has depth in the AI capabilities, particularly in computer vision and marketing, emphasizing customer experience.
  • The company offers comprehensive AI life cycle coverage, including a model factory for development and features like version control and management.
  • Partnering with Alibaba Group, Whale Cloud Technology gains access to the latest large language models (LLMs) and draws from a rich experience across various industries. This enables it to support key business models like SaaS, enhancing its ability to support CSPs expanding in enterprise business.

  Cons:

  • With 62% of its AI revenue originating from China and the remainder mainly from emerging countries in APAC, Whale Cloud Technology shows limited experience with Tier 1 CSPs in developed markets outside of China.
  • Whale Cloud Technology's AI deployments primarily focus on marketing, sales and customer journey use cases, potentially overshadowing broader AI applications in customer and business operation, such as revenue and fraud management.
  • Whale Cloud Technology's product roadmap and go-to-market messaging for AI-generated content (AIGC) lacks clarity, which may limit its ability to efficiently engage CSP CIOs looking for use cases in this area.

Reference

• Gartner, Magic Quadrant for AI in CSP Customer and Business Operations, 4 June 2024, ID G00808857

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