Case study overview
STL partnered with a leading hyperscaler to develop a strategic framework that prioritises GenAI skill development based on the organisation’s specific implementation needs.
The topic of generative AI gained significant momentum in 2023 and remains front of mind for many CSP decision-makers, given its potential to create significant value across the telecommunications industry. However, CSPs encounter significant challenges when implementing and deploying Gen AI across internal operations as well as in customer-facing products and services, impacting their ability to extract value from their efforts.
AWS approached STL Partners to explore the challenges that CSPs face as they adopt Gen AI, particularly those pertaining to internal skills and capabilities.
Our client asked STL Partners to develop a piece of thought leadership that explores the challenges CSPs face in building the necessary capabilities – and how AWS can position itself as a strategic partner in addressing these challenges.
What was the approach?
Following a series of in-depth interviews with senior telco stakeholders and decision-makers focused on Gen AI deployment, STL developed a comprehensive framework that categorises the skills and capabilities required for success in Gen AI implementation. The framework highlights the different skills required across various organisational domains.
We then developed detailed assets based on insights from primary research, highlighting why and how telcos should upskill up for success and maximise the value of GenAI. These included a thought leadership report and a presentation deck to support our client socialise key research findings internally.
Key results from the project
- Interviewed 6 global operators, including both Tier-1 and Tier-2 CSPs
- Identified 12 key internal and external Gen AI use cases (e.g. digital assistants, personalised marketing, network planning), mapped by adoption maturity
- Defined the critical skills and capabilities required across 5 core functional domains -strategy, procurement, governance, legal and risk, data and AI, and end users – aligned to deployment phases from vision definition to scaled implementation
- Shared findings at AWS Re:Invent
