Vertiv's Strategic Acquisition of Great Lakes: A Positioning Play in the High-Growth AI Infrastructure Market

The acquisition of Great Lakes Data Racks by Vertiv (VRTX) represents a calculated move to capitalize on the AI-driven data center revolution. Priced at $200 million—11.5x expected 2026 EBITDA—the deal reflects a disciplined valuation in a sector where AI infrastructure companies command multiples averaging 21.8x. Vertiv's strategic integration of Great Lakes' custom rack design capabilities with its existing power and cooling portfolio positions the combined entity to dominate in high-margin, pre-engineered AI infrastructure solutions.

Valuation Rationale: A Discounted Premium in a High-Growth Sector

While the 11.5x EBITDA multiple may appear modest compared to the 25.8x average for AI M&A in 2025, this reflects the inclusion of cost synergies and cross-selling opportunities. Great Lakes' specialized expertise in high-density rack systems aligns with the surging demand for AI infrastructure, which is projected to grow at a 12.7% CAGR through 2030. Vertiv's ability to offer end-to-end solutions—combining racks, power, and cooling—creates a defensible moat in a market where hyperscalers and enterprises increasingly demand integrated systems to manage AI workloads.

Strategic Fit: Closing the Infrastructure Gap for AI Workloads

Great Lakes' rack systems are critical for managing the thermal and spatial challenges of AI-driven data centers. By acquiring the company, Vertiv accelerates its transition from a hardware supplier to a solutions provider. The integration of Great Lakes' factory-optimized racks with Vertiv's power and cooling technologies reduces deployment timelines and operational costs for clients. This synergy is particularly valuable in edge computing and modular data center markets, where speed and efficiency are paramount.

The acquisition also diversifies Vertiv's revenue streams. Great Lakes' 95% capital and coastal protection project backlog—highlighted in its Q1 2025 EBITDA of $60.1 million—provides visibility into sustained cash flows. This contrasts with Vertiv's reliance on commodity IT infrastructure, offering a buffer against market volatility.

Long-Term Earnings Potential: Leveraging AI's Infrastructure Tailwinds

Vertiv's 2025 guidance projects EBITDA of $1.9B, a 20% increase from 2024, driven by operational leverage and AI-related demand. Great Lakes' post-acquisition growth is expected to accelerate this trajectory. With AI workloads consuming 50% of global data center capacity by 2027, the combined entity's focus on AI-ready infrastructure could unlock $500M+ in incremental revenue annually.

Key drivers include:
- Cross-selling: Vertiv's global sales force can now upsell integrated rack-power-cooling bundles to existing clients.
- Tariff Mitigation: Great Lakes' U.S. manufacturing base aligns with Vertiv's strategy to reduce supply chain risks, enhancing gross margins.
- Edge Computing: Modular, AI-optimized racks from Great Lakes will target the $1.2B edge infrastructure market, where Vertiv is currently underrepresented.

Investment Implications: A Buy for Long-Term Growth

The acquisition is a rare example of a strategic leveraged buyout in a sector where many acquirers overpay for AI hype. Vertiv's disciplined valuation, combined with its strong balance sheet ($2.3B liquidity, 0.8x net leverage), supports a bullish outlook. Investors should monitor two metrics:
1. EBITDA accretion post-merger: If the combined entity achieves $220M in 2026 EBITDA (vs. $1.9B for Vertiv alone), the 11.5x multiple becomes a compelling entry point.
2. Cross-selling penetration: A 10% increase in Vertiv's AI infrastructure revenue share could drive 250bps of margin expansion.

For risk-tolerant investors, the acquisition offers exposure to AI's infrastructure tailwinds at a discount to sector multiples. For conservative investors, Vertiv's diversified revenue base and Great Lakes' stable backlog provide downside protection. In either case, this deal is a textbook example of positioning for the next phase of the AI revolution.