Case study overview
STL supported a global telecoms and technology service provider to validate the value proposition for its AI-enabled WAN, and workload management and orchestration platform solution, to develop a business case for launch.
Enterprises are increasingly exploring how to deploy AI across diverse operational environments but often lack cohesive infrastructure and management strategies. As a result, organisations face challenges predicting infrastructure demand, monitoring distributed edge AI workloads, and meeting evolving data sovereignty and regulatory requirements.
A global fixed and technology service provider identified two emerging AI service opportunities – an AI-enabled WAN, and an AI workload management and orchestration platform solution – that seek to address enterprise AI demand and deployment bottlenecks.
Our client engaged STL Partners to help define and validate the value proposition and assess its commercial potential. The project aimed to gather direct feedback from potential enterprise customers on key pain points, infrastructure preferences and willingness to pay, while also analysing the competitive landscape and market opportunity.
What was the approach?
To address the problem statement, STL Partners was asked to conduct a structured validation process to assess the market fit of the client’s solutions, spanning three key stages: proposition ideation, validation and refinement, and business case modelling.
This included voice of the customer interviews with senior enterprise decision-makers, market analysis and stakeholder workshops, bringing together an assessment of the market attractiveness and client’s right to win across both solution areas. Building on these insights, STL developed a five-year business case to evaluate revenue potential.
The outcome was a set of strategic recommendations to refine its AI value proposition aligned to priority target customer segments and solution feature set and define a practical go-to-market and investment strategy.
Key results from the project
- Evaluated 11 enterprise AI opportunities (e.g. private inferencing, training, fine-tuning by industry and edge location) on market attractiveness and client’s right to win to tailor solution to market demand
- Identified 3 high-value use cases across 3 target industries with strong demand for edge AI infrastructure for the client to address
- Interviewed 6 large UK enterprises in a voice of the market research to validate market fit and customer value
- Assessed 11 competitors against a comprehensive capability evaluation framework with 25 criteria’s spanning infrastructure and edge and AI workload orchestration capabilities
- Modelled a 5-year revenue forecast to support business case evaluation, extrapolating to 6 additional markets to reflect client’s reach
