Generative AI: Why and how telcos should skill up for success?

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Generative AI is expected to create significant value across the telecommunications industry. To capitalise on the opportunity, telcos must build new skills across their organisations. Getting this right is critical given the scale of implementation challenges and the significance of impact on how employees work.


Format: PDF filePages: 20 pagesAuthor: Will DaviesPublication Date: February 2024

Table of Contents

  • Executive Summary
    • What are the next steps for telcos?
  • The generative AI journey has many challenges, but the destination is worth it
    • Generative AI poses unique risks and challenges for telcos that require focused attention and expertise to solve
  • A cross-domain effort is required to address challenges at different deployment phases
    • Vision definition
    • Model development and acquisition
    • Initial implementation
    • Model fine tuning
    • Scaled implementation, optimisation and utilisation
  • Conclusion: telcos must address skill and capability gaps to ensure success
    • Further reading

Table of Figures

  • Figure 1: Recommendations for building generative AI capabilities within telcos
  • Figure 2: Our research programme consisted of in-depth interviews with six telco operators globally
  • Figure 3: The costs of generative AI necessitate careful use case prioritisation
  • Figure 4: Skills requirements across different functional domains at each phase of generative AI deployment


Technologies and industry terms referenced include: AI, AWS, Cybersecurity, Deutsche Telekom, end users, Gen AI, Generative AI, Governance, Hyperscalers, legal, Llama 2, LLMs, Machine Learning, ML, open source, People and Skills, procurement, public relations, senior leadership, SK Telecom, SMEs, transformation