Equinix, Inc. earnings call
Q4 bookings surged 42% year-over-year to $474M
Equinix reported record Q4 2025 bookings, with a significant acceleration driven by AI workloads (60% of largest deals). Management raised its 2026 guidance well above its June 2025 Analyst Day expectations, citing strong demand across all regions and customer types, improved pricing discipline, and efficient capital deployment. The tone is very bullish, with the company positioning itself as a central player in the AI infrastructure build-out. Record annualized gross bookings of $1.6B in 2025, up 27% YoY, with Q4 bookings of $474M up 42% YoY.
Buzzberg read Q4 bookings surged 42% year-over-year to $474M Equinix reported record Q4 2025 bookings, with a significant acceleration driven by AI workloads (60% of largest deals). Management raised its 2026 guidance well above its June 2025 Analyst Day expectations, citing strong demand across all regions and customer types, improved pricing discipline, and efficient capital deployment. The tone is very bullish, with the company positioning itself as a central player in the AI infrastructure build-out. Record annualized gross bookings of $1.6B in 2025, up 27% YoY, with Q4 bookings of $474M up 42% YoY. Read full analysisCollapse analysis
Equinix reported record Q4 2025 bookings, with a significant acceleration driven by AI workloads (60% of largest deals). Management raised its 2026 guidance well above its June 2025 Analyst Day expectations, citing strong demand across all regions and customer types, improved pricing discipline, and efficient capital deployment. The tone is very bullish, with the company positioning itself as a central player in the AI infrastructure build-out. Record annualized gross bookings of $1.6B in 2025, up 27% YoY, with Q4 bookings of $474M up 42% YoY.
- AI-driven workloads represented ~60% of the largest deals in Q4, up from ~50%, with enterprise AI adoption broadening beyond cloud providers.
- 2026 revenue growth guided to 9-10% and AFFO per share growth to 8-10%, with adjusted EBITDA margin expected to expand to ~51%.
- Interconnection business surpassed 500,000 total connections, growing 9% YoY, highlighting its insurmountable scale advantage.
What matters now
The highest-signal changes from the call.
AI drives 60% of large deals, half from non-cloud firms
2026 AFFO growth seen 8-10%, up 300bps from prior plan
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Adjusted EBITDA margins expected at ~51% in 2026
Hampton Xscale lease signing expected in Q1, site fully leased later 2026
Interconnection milestone: half a million connections
Actuals
| Metric | Reported | Change |
|---|---|---|
| Revenue | $2.442B | Reported |
| EPS | $2.70 | Reported |
| Gross margin | 50.94% | Reported |
| Operating margin | 17.28% | Reported |
| AFFO Free cash flow | $0 | Reported |
| Free cash flow | $-0.292B | Reported |
Forward guidance
| Metric | Period | Range | Midpoint | Status |
|---|---|---|---|---|
| Capex | FY2026 | $3.7B–$4.2B | $3.95B | Guided |
| Free cash flowAFFO_PER_SHARE | FY2026 | $8.00–$9.00 | $8.50 | Raised |
| Operating marginADJUSTED_EBITDA_MARGIN | FY2026 | 51% | 51% | Raised |
| Revenue | FY2026 | $10.4B–$10.5B | $10.45B | Raised |
Management read
Upbeat
Management expressed strong confidence in momentum, highlighted record bookings and a positive 2026 outlook, and emphasized execution and market positioning.
Management AI read
Management highlighted that AI is a key growth driver, with approximately 60% of large deals driven by AI workloads, up from 50% earlier in 2025, and noted that nearly half of these AI deals were from non-cloud/IT companies, indicating expanding enterprise adoption. They emphasized their differentiated position for AI inference due to network diversity, cloud proximity, and interconnection, and se
Investment and capacity
Management is aggressively expanding capacity, delivering a record 23,250 retail cabinets and over 90 MW in Xscale in 2025, with 52 major projects underway across 35 markets. They added ~1 GW of powered land in 2025 and plan 2026 capex of $3.7-4.2 billion, with Xscale contributing to growth via JVs.
Companiesreturns since call
Customers
Salesforce is deploying a large, multi-region private networking layer on Equinix Fabric, indicating deepening enterprise AI infrastructure spend and a significant win for Equinix's interconnection business.
Evidence
“Salesforce chose Equinix to create a private multi-cloud networking layer for the engine inside their data and AI foundation.”
Hudson River Trading's selection of Equinix for high-density, low-latency AI workloads validates Equinix's ability to capture demand from financial services firms upgrading their HPC infrastructure.
Evidence
“Leading quantitative trading firm Hudson River Trading selected Equinix because our global footprint and our advanced cooling solutions enable them to achieve the latency and the density requirements they need to power their next-gen AI”
Honeywell's global expansion with Equinix highlights the demand from industrial enterprises for internal AI application integration and multi-market digital infrastructure, a key growth area for Equinix.
Evidence
“Fortune 500 multinational Honeywell Corporation expanded its relationship with Equinix because of the secure, flexible solutions and global fabric connectivity we provide, including for key metros such as Shanghai, Tokyo, and London.”
Partners
NVIDIA's high-end hardware is being deployed in Equinix data centers, reinforcing Equinix's position as a preferred location for high-performance AI infrastructure and the associated demand it generates.
Evidence
“We are working with Alnavic as they deploy the NVIDIA DGX SuperPod with NVIDIA Grace Blackwell systems to expand their addressable market through distributed AI.”
Equinix's role in connecting enterprise customers to hyperscaler clouds like AWS is a core part of its value proposition, cementing its position as an essential intermediary in the multi-cloud ecosystem.
Evidence
“By deploying Equinix Fabric Cloud Router across 14 countries and 21 metros, we are enabling private network connectivity between Salesforce's presence in AWS, Azure, and other cloud service providers.”
Supply chain
AI-driven deals are 33% more power-dense (avg ~10kVA/cabinet) than non-AI deals, and 11 liquid-cooled deployments were made in Q4, including 5 in NYC for FSI customers. — This confirms the acceleration of high-density, liquid-cooled deployments in retail colocation, which is a strong demand signal for providers of advanced cooling and high-power infrastructure.
Evidence
“We saw a 33% increase in density compared to the non-AI deals, so an average of about 10 kVA per cap for these transactions.”
Q4 saw a significant drop in MRR churn to 2.2% (from 2.4% avg for the year), attributed to new AI-driven predictive tools and earlier identification of at-risk renewals. — The successful use of AI tools to reduce churn highlights a new operational edge and validates the value of AI-driven customer success in the data center industry.
Evidence
“Global Q4 MR return was 2.2%, lower than planned. And for the full year, our average quarterly MRR churn was 2.4%.”
Equinix expects to raise debt in 2026 at lower costs in locations like Canada, Singapore, and Europe, continuing a strategy that has optimized net interest expense. — This capital efficiency provides Equinix with a cost-of-capital advantage relative to new entrants and heavily levered competitors, allowing for more aggressive, yet still accretive, expansion.
Keith TaylorSupply-chain alpha · 3returns since call
AI-driven deals are 33% more power-dense (avg ~10kVA/cabinet) than non-AI deals, and 11 liquid-cooled deployments were made in Q4, including 5 in NYC for FSI customers.
Q4 saw a significant drop in MRR churn to 2.2% (from 2.4% avg for the year), attributed to new AI-driven predictive tools and earlier identification of at-risk renewals.
Equinix expects to raise debt in 2026 at lower costs in locations like Canada, Singapore, and Europe, continuing a strategy that has optimized net interest expense.
Methodology & coverage
Management-only analysis. All 9 validated company mentions are shown. Reported actuals and forward guidance are kept separate. Public evidence is limited to eight short attributed quotes. AI-generated analysis can be incomplete or wrong; verify important claims against the original source.