How Bank of America's AI Demand Concerns Are Reframing Digital Realty's Investment Story
Bank of America moved Digital Realty Trust (DLR) from Buy to Neutral, citing slower traction in converting AI-related demand into signed leases and limited exposure to newer growth markets. That doesn't blow up the long-term data center thesis, but it does put timing and mix under the microscope.
For investors, the question shifts from "Is AI demand real?" to "How fast does it hit DLR's P&L-and in which markets?" Near-term, the spotlight is on execution.
What Changed - And What Didn't
- Changed: Confidence in the pace of AI-driven leasing. The downgrade implies enthusiasm isn't translating into contracts quickly enough.
- Changed: Concern about market mix. Limited exposure to newer high-growth geographies may be a headwind.
- Unchanged: The key catalyst. Q4 2025 results on 5 February 2026 should be all about leasing velocity and AI commentary.
- Unchanged: Core thesis: DLR's global platform remains relevant to AI and cloud workloads-execution timing is the debate.
The Core Narrative-Now With Caveats
Owning DLR still means believing demand for its global data center platform-especially AI and cloud-can support backlog and future earnings. The caveat: how quickly that demand becomes contracted MRR and cash flow in a competitive market.
If AI deal cycles elongate or shift to markets where DLR has less presence, near-term leasing could look softer even if the pipeline is large.
2028 Targets: Growth With Margin Pressure
DLR's narrative points to $7.9 billion revenue and $1.0 billion earnings by 2028. That implies about 11.5% annual revenue growth alongside a step down in earnings from $1.3 billion today.
Translation: the path relies on growth but tolerates margin compression. That can work-if leasing scales and developments deliver-but it narrows the margin for error on pricing, power availability, and start dates.
Feb 5: What to Listen For
- Leasing detail: Gross vs. net new, AI-specific wins, ticket sizes, and pre-leasing on development.
- Pricing & terms: New logo rates, renewal spreads, and structure (power-inclusive vs. pass-through).
- Market mix: Momentum in AI-favored metros vs. slower legacy markets; commentary on "newer growth" exposure.
- Backlog quality: Start dates, probability-weighting, and visibility into near-term commencements.
- Capacity & power: Time-to-power, interconnect density, and any constraints affecting delivery.
- Capital & JV activity: Development funding, balance sheet capacity, and asset recycling to sustain growth.
Scenario Map for 2026
- Traction: Clear AI lease wins, improving win rates in key markets, and better pre-leasing. Backlog converts cleanly, easing concerns.
- Stall: Decision delays and softer net leasing. Backlog grows but conversions push right, pressuring 2026 revenue and margins.
- Mixed: Healthy bookings but concentrated in fewer markets with longer ramps. Growth intact, timing risk elevated.
Valuation Dispersion-and Why It Matters
Community fair value estimates span roughly US$110 to US$241 per share. That spread reflects different assumptions about the speed of AI conversion, market mix, and margin trajectory to 2028.
If you assume faster AI leasing and earlier starts, the model supports higher multiples. If you assume slower conversions and heavier capital needs, multiples compress.
Portfolio Takeaways
- Underwrite a slower AI ramp until evidence shows otherwise; prioritize backlog timing over headline bookings.
- Stress test margin compression alongside revenue growth; 2028 earnings guide implies tighter unit economics.
- Watch market exposure: where capacity is, where AI demand is landing, and the speed to power-on.
- Track capital intensity and funding sources-development pace only works with clean balance sheet math.
- Use the Feb 5 update to recalibrate 2026-2028 lease start schedules, development yields, and renewal pricing.
Useful Resources
- Digital Realty Investor Relations - events, presentations, and filings.
- AI tools for finance - practical resources to benchmark workflows as AI spend scales.
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