This blog is based on the analysis, Growth Opportunities for Telcos in Enterprise GenAI Solutions by Frost & Sullivan’s growth expert, Carina Gonçalves, from the Internet of Things (IoT) and Edge solutions team.
What if telecommunications service providers (telcos) could move beyond selling connectivity and network services, evolving into strategic enablers of enterprise digital transformation? That’s the disruptive promise of generative AI (GenAI). It can take telcos beyond network optimization, automation, connectivity management, and customer support, towards differentiated digital services (powered by proprietary large language models [LLMs], natural language processing [NLP], and innovative data management tools).
But transformation rarely comes easy. While some telcos have already piloted AI solutions, many continue to grapple with the intricacies of legacy systems, siloed data, and ethical considerations that limit overall progress. To add to this challenge, revenue generation from traditional telecom services is on the decline, leaving little room for providers to delay innovation. The upside? Advances in cloud computing, sensor technologies, and pre-trained AI models are slashing technical and cost barriers, giving telcos a new window of opportunity. Those who adapt amid the following eight imperatives can position themselves favorably for long-term success:
Frost & Sullivan explores the evolving ecosystem of telco-led GenAI solutions, shedding light on:
- Companies to action and industry-specific enterprise AI solutions
- 3 lucrative AI-first growth opportunities and AI strategies to focus on
- Technology implementation frameworks and best practices in commercial GenAI
Click here for actionable intelligence on enterprise GenAI solutions!
- Innovative Business Models
AI-as-a-Service: Embedding NLP, computer vision, and GenAI into new business to business (B2B) offerings through AI-as-a-Service pricing models. This will help providers supercharge conventional products and services for 5G, edge, and data, while creating recurring revenue pipelines that position them as trusted partners in future enterprise AI initiatives.
- Disruptive Technologies
In-house, Proprietary LLMs: Creating domain-specific telecom LLMs that facilitate AI-based network optimization, intelligent edge solutions, predictive analytics, and service workflow automation. By doing this, providers will be able to strengthen data control and reduce their reliance on global models.
- Rising Competitive Intensity
AI Centers of Excellence (COEs): Ramping up investments in self-service analytics, data monetization strategies, cloud-native data platforms, and best practice implementation, thereby integrating siloed data and driving AI readiness in enterprises. These foundations will also help telcos minimize time to market for B2B AI services and better differentiate themselves.
- Internal Challenges
Data Management: Building clean and standardized data architecture is essential to unlocking the full potential of AI and machine learning (ML). But only a handful of telcos have the right tools that tie together diverse enterprise data pools. This is intensifying the pressure to break silos from legacy systems and capitalize on innovative services for data migration, integration, engineering, and governance.
Which strategic partnerships and collaborations will help telcos effectively scale AI-as-a-Service offerings?
- Industry Convergence
Vertical and Horizontal AI Solutions: Creating turnkey AI solutions that integrate seamlessly into enterprise workflows. This will help telcos develop white-label services, low-code tools, chatbots, customized foundational models, security services, and pre-built connectors for organizations to scale AI across various business functions with less complexity.
New technologies are enabling AI-first enterprise products/services in tomorrow’s telecoms. These go beyond newtork optimization and customer support.
Access full analysis to unlock lucrative growth opportunities and AI strategies in this space!
- Transformative Megatrends
AI Risk and Compliance: Building domain-specific expertise in regional regulatory mandates, governance structures, and security frameworks to ensure responsible AI adoption. Moreover, by reducing bias and hallucinations, telcos can also help enterprises trust GenAI by offering audit trails, bias-mitigation controls, and comprehensive data life-cycle management services.
- Customer Value Chain Compression
Augmented Intelligence Services: Developing new, outcome-based services in partnership with leading ICT players in facial recognition, speech, sentiment, behavioral, and text analytics. By co-creating such bundled offerings, telcos can help enterprises enhance decision-making, personalize B2B product portfolios, and deliver richer customer experiences.
- Innovative Business Models
Personalization and Targeting: Leveraging GenAI to enhance customer targeting, tailored advertising, and content generation while enabling enterprises with AdTech tools, analytics-as-a-service, and insights marketplaces. By offering AI subscriptions, pre-trained model licenses, and smaller domain-specific LLMs, telcos can monetize data and generate supplemental revenue streams.
In conclusion, AI places telcos at an inflection point: moving from pure-play connectivity and network services to AI-powered technology companies. By investing in GenAI, edge infrastructure, and verticalized offerings, they can unlock new revenue streams and differentiate themselves in a landscape where traditional services alone can no longer sustain growth.
Do you have the technology strategies and growth processes to thrive through the transformation spurred by GenAI?
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