Generative AI: A Potential Gamechanger for Telcos Struggling in a Competitive Landscape

Jakarta, INTI - The telecommunications industry is facing a period of intense competition and ongoing pressure to cut costs. However, a new technology – generative AI (gen AI) – is emerging as a potential catalyst for reigniting growth. This article explores the potential impact of gen AI on telcos, the challenges they face in adopting it, and the key building blocks for success.

Gen AI represents a significant leap forward in artificial intelligence. Unlike traditional AI, it can analyze diverse data types, including text, code, and images, and even generate entirely new content. This capability opens doors for a wide range of applications across various telco functions, including:

• Customer Service: Enhancing agent productivity, enabling fully digital interactions, and offering improved customer experiences through AI chatbots capable of summarizing voice and written interactions.
• Marketing and Sales: Personalizing marketing messages and content, identifying new sales leads from customer calls, and conducting deeper customer insights analysis.
• Network Operations: Optimizing network configurations, extracting customer insights from social media data, and improving network planning and management through the analysis of unstructured data.
• IT: Accelerating software development and migrations, reducing technical debt, and streamlining the software lifecycle.
• Support Functions: Reducing back-office operational costs and boosting employee productivity through automated content generation and internal chatbots.

Early signs of success are already evident. Telcos are reporting significant improvements in areas like customer service agent productivity, conversion rates for marketing campaigns, and cost reductions. These initial wins demonstrate the transformative potential of gen AI for the industry.

Challenges and Considerations

Despite the promising outlook, telcos face hurdles in adopting gen AI at scale. Some of the key challenges include:

• Shifting from a Proof-of-Concept Mentality: Many telcos are stuck in a cycle of developing proofs-of-concept without effectively scaling these solutions across the organization.
• Building the Right Team: The speed of innovation with gen AI necessitates a skilled workforce with expertise in areas like gen AI prompt engineering and data engineering. Upskilling existing staff and attracting new talent will be crucial.
• Developing an Effective Operating Model: Centralized decision-making, reusable services, and control towers to oversee gen AI investments are necessary for efficient implementation.
• Data Considerations: Telcos need to collect and manage data more comprehensively, including unstructured data, while ensuring responsible use practices to address privacy and intellectual property concerns.
• Change Management: A successful gen AI implementation requires a culture of innovation and experimentation. Leaders must prioritize employee training and change management initiatives to ensure adoption and scale.

The Blueprint for Success

To unlock the full potential of gen AI, telcos need to build upon a foundation of core building blocks:

• Business-Led Roadmap: Aligning vision, value, and roadmap creation, assessing gen AI's risks and opportunities, and establishing clear guidelines for organizational use are critical first steps. Leaders need to decide whether to build, buy, or fine-tune gen AI solutions based on specific use cases.
• The Right Talent: A combination of upskilling existing staff and attracting new talent with gen AI expertise is necessary. Training programs and certification systems can equip employees with the necessary skills.
• Operating Model: Centralized decision-making, reusable services, and control towers to oversee gen AI investments are essential for efficient implementation.
• Technology Blueprint: A blueprint outlining reusable services, large language model selection strategies, and scaling plans is crucial. Additionally, establishing a dedicated gen AI innovation lab to keep pace with industry developments is recommended.
• Data Strategy: Collecting a wider range of data, including unstructured data, and establishing responsible use practices are essential considerations.
• Change Management: Prioritizing employee training, upskilling, and change management initiatives is crucial for fostering a culture of innovation and ensuring successful adoption.

The Road to an AI-Native Telco

By embracing gen AI and overcoming the associated challenges, telcos have the opportunity to redefine industry standards and achieve significant growth. This journey will involve fostering a culture of innovation, experimentation, and agility. Early adopters stand to gain a significant competitive advantage by leveraging gen AI's transformative capabilities to enhance customer experiences, optimize operations, and drive revenue growth.