Context and Chronology

Over the last year large technology firms have moved decisively into public and private credit markets to fund AI infrastructure, R&D and capital returns. Market tallies put tech corporate bond issuance near $300 billion for 2025 (Q4 alone ~$108.7 billion) with another ~$15.5 billion of new paper placed in early 2026. Alphabet is among the most active: executives have begun marketing a multi-part, multi-market bond program targeting roughly $20 billion in US-dollar and offshore tranches (including placements in Switzerland and the U.K.), and recently sold a long-dated tranche of about £1 billion (~$1.37 billion). One tranche under consideration could reach a century in maturity, a move that would test demand for ultra-long corporate duration from a top-rated tech credit.

Capital raised is being directed across three vectors: large-scale data‑center and accelerator buildouts, extended share‑repurchase programs, and a strategic pool to underwrite selective M&A. The financing mix has broadened beyond bank loans and vanilla bonds; syndicated loans, commercial‑mortgage‑backed securities and bespoke structured credit now sit alongside private placements as treasurers match liability profiles to long-lived AI assets.

Policy and market observers are registeredly cautious. Federal Reserve minutes noted high equity valuations and concentrated market value among a handful of tech firms but characterized aggregate corporate‑borrowing risks as “moderate,” reflecting that many hyperscalers entered the cycle with light leverage. At the same time, fixed‑income desks and lenders report sharper dispersion: roughly $18 billion of problem loans materialized in a compressed window for software credits, and traders are widening spreads on smaller, single‑product vendors that face heavier capex and margin pressure.

This split — benign aggregate risk vs. concentrated credit stress — creates a two‑speed market. Large, cash‑rich platforms benefit from cheaper access to long‑dated funding and diversified investor demand (life insurers, pension funds and infrastructure managers), while smaller software and services firms face higher effective costs of capital, weaker secondary prices and narrower refinancing options. That repricing raises the bar for M&A sellers and tilt negotiating leverage to high‑quality public acquirers.

For venture‑backed companies the implications are immediate: potential acquirers with enlarged balance sheets can pay premiums selectively, narrowing windows for competitive exits and compressing late‑stage valuations where strategic fit is thin. Talent markets also tighten as incumbents convert liquidity into hiring and retention packages, raising regional compensation baselines. Founders and GPs will increasingly demand durable unit economics, longer revenue histories, and clearer capex plans from portfolio companies to justify valuation upside.

Execution frictions in the real economy amplify financing risk. Estimates of AI‑related infrastructure commitments range from roughly $1.5 trillion to multi‑trillion programs, while local permitting, grid limits and community pushback have already put about $64 billion of U.S. data‑center projects at risk or delay — a reminder that funding availability does not eliminate delivery and timing risks for buildouts.

Taken together, the wave of issuance reshapes term sheets, underwriting practices and diligence: lenders and rating agencies are focusing on free cash flow, customer concentration, margin durability and supplier dependencies; underwriters are pricing a wider dispersion across tenors and geographies; and investors are weighing duration exposure against refinancing and execution risk. Expect more selective tuck‑ins and regional R&D plays rather than frequent transformational buyouts, and a higher bar for IPO readiness as venture exit pipelines compress.