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Telcos need ecosystem partnerships to seize back-office AI use cases as internal frictions hinder adoption

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back-office AI

Telecom operators have a significant opportunity to transform their operations using Artificial Intelligence (AI). However, due to inherent technology risks, early use cases will mostly be limited to the back-office in customer services, marketing, sales, and network support. Additionally, telcos may face significant deployment challenges, which could result in slower adoption compared to other industries. A report by a global technology intelligence firm, ABI Research, suggests that competition, ecosystem partnerships, and standardization will be the key factors that unlock the full potential of AI in the telecom industry.

While networking use cases have the potential to create value, the technology and telcos are not yet ready to make this leap. Instead, the back-office aligns more closely with AI use cases and has human touchpoints that help mitigate its risk profile. In comparison to the network, deploying AI in the back-office presents a better commercial model with cross-vertical shared innovation and a more apparent return on investment model. This is because it can save time, reduce headcount, and lower customer churn, resulting in a more significant ROI.

Reece Hayden, senior analyst at ABI Research, explains, “Back-office use cases make most sense, but it does not mean that they are simple for telcos to deploy. Telcos have highly siloed internal structures, significant knowledge gaps, and data challenges that will stand in the way of effective implementation.”

Companies that were pioneers in the telecommunications industry have devised effective strategies for utilizing AI by collaborating with partners. One example of this is e& (formerly known as Etisalat), which has partnered with Netcracker and DataRobot to bolster their three-step GenAI integration strategy.

Despite the efforts of early adopters, the majority of the market is still in the initial phases of implementing AI and is grappling with various commercial and technical challenges.

Hayden points out, “Most telcos still need to figure out who to partner with. Three key players are building strong telco value propositions. OSS/BSS vendors are rolling out GenAI capabilities built on their strong telco expertise, hyper scalers are relying on their AI expertise and market-leading models, and AI leaders like Anthropic are playing a more niche role as they try and define their commercial proposition.”

Telecommunications companies should already be well into the stages of planning, preparation, and implementation. Additionally, securing strong partners will open doors for new opportunities and enable operational transformation in the long term. According to ABI Research, hyper scalers are the most promising partners for long-term benefits. However, vendors that focus on Operations Support System (OSS)/ Business Support System (BSS) will also be contenders, particularly if they continue to enhance their GenAI platforms. In addition to commercial partnerships, coop-etition, where companies cooperate and compete simultaneously, will be a potent force in addressing data accessibility and availability challenges for specific applications.

“However, the result will not be achieved through coop-etition and partnerships alone. Instead, as with most telco opportunities, ABI Research expects standardization to be key (like those defined in 3GPP). This process will help overcome the cost and deployment challenges, which are all too familiar to telcos,” concludes Hayden.

ABI Research’s report, “Defining Telco Strategy for BSS/OSS Artificial Intelligence Transformation,” presented the above conclusions. This report is a part of the company’s AI and Machine Learning research service, which offers various research, data, and ABI Insights.

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