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Summary
The AI build-out has reached historically extreme investment intensity and unprecedented concentration, but it has not yet developed the financing characteristics that made the dot-com build-out fragile. Where the dot-com carriers were largely pre-revenue or unprofitable, funding a fiber build-out almost entirely with debt, the Hyper 5 are profitable companies funding the build-out almost entirely from their own cash flow, at least so far.
Join S&P Global Market Intelligence for this 30-minute webinar on the AI-driven capex cycle and its next phase. We'll set out the signals to watch as the build-out develops including:
- Whether capex exceeds operating cash flow
- Whether the financing mix continues to shift toward debt
- Whether the cash/capex ratio falls through its 2000 starting level
- Whether AI demand materializes on a normal timeline.
We'll also showcase a live GenAI research agent. Using a Snowflake-hosted LLM interface, it combines S&P Global's Fundamental Powerhouse data with context from SEC filings, machine-readable earnings call transcripts, and our own quantitative research into a single AI-powered research workflow that updates the analysis live.
What we will cover:
- How today's investment intensity and concentration compare with previous cycle peaks
- The scale of the AI build-out driven by the Hyper 5 (Amazon, Alphabet, Microsoft, Meta and Oracle)
- How this cycle differs from the dot-com era: profitable, cash-funded hyperscalers versus pre-revenue, debt-funded telecom carriers
- The signals to watch, including capex exceeding operating cash flow and a shift toward debt funding
- Whether enterprise adoption of generative AI is materializing quickly enough to justify the current level of investment
- A demo of the GenAI research agent that updates this analysis live
Speakers
S&P Global Market Intelligence
Daniel Sandberg
Global Head of Quantitative Research & Solutions
Daniel J. Sandberg, PhD, CFA is a thought-leader at the intersection of data science, finance, and mathematics. After 9 years studying the physical sciences, Dan decided to apply his quantitative skill set to the field of equity research. In his current role, Dan leads original research projects, validates new alternative data sets, and builds better technology for Investment Management professionals.
S&P Global Market Intelligence
Liam Hynes
Head of New Product Development – Public Markets
Liam Hynes serves as the Global Head of New Product Development. In this role, he leads strategic product innovation, driving the development of cutting-edge research & solutions across the firm’s extensive data and analytics platforms. His work spans the entire solution life cycle from proof-of-concept development, business assessment, beta client engagement, blueprint creation, product development, go-to-market strategies and commercialisation. Under Liam’s leadership, the team has delivered impactful research such as Questioning the Answers, blueprint solutions such as QTA & Ripple Effect and product launches with CCDE.
Before assuming his current role, Liam served as Head of ESG & Quant Specialists, EMEA, advising S&P clients on quantitative modelling, climate risk assessments, and alternative data integration. Prior to S&P Global, he was Founding Partner & Portfolio Manager at Monreith Capital LLP, managing a Global Financials Hedge Fund. He also held senior investment roles at Liontrust Asset Management and Occam Assest Management, focusing on emerging markets and commodities.
Liam is currently pursuing a PhD in AI & Finance from Kemmy Business School, where his research covers natural language processing, network theory, and AI-driven executive sentiment & behavioural analysis. He has also earned a BSc (Hons) in Mathematics from the University of Limerick and holds a Machine Learning certification from Stanford University.
Questions?
Please contact us if you need more information or have trouble accessing the webinar.