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In Conversation with
FRANK SOMMERS
Vice President, Technology Leasing, First Financial Equipment Leasing
Frank Sommers, Vice President, Technology Leasing, at First Financial Equipment Leasing, brings 30 years of experience in the IT leasing industry, advising global enterprise organizations on how to modernize their infrastructure while preserving capital and accelerating technology adoption. A former collegiate soccer player at Cal Poly San Luis Obispo, Frank brings a strong sense of competitiveness and teamwork to every client relationship.
As AI adoption moves quickly across industries, large enterprises are facing significant financial hurdles, with full-scale AI data center investments ranging from $150 to $500 million. Frank joins us today to explain how organizations can overcome these barriers. He discusses how IT leasing acts as a “budget multiplier,” allowing companies to bypass the massive upfront costs of high-performance compute infrastructure and avoid the trap of rapidly depreciating technology.
Techronicler: AI adoption is moving quickly across industries. What challenges are large enterprises facing as they try to modernize their technology stack?
Frank Sommers:
Large enterprises face several significant challenges when modernizing for AI. First, the core infrastructure is expensive and highly concentrated, particularly GPUs which are essential for processing AI workloads. For a full-scale AI deployment, organizations may need to invest hundreds of thousands to millions per GPU cluster, resulting in total data center investments ranging from $150 to $500 million.
The financial hurdle is especially steep for mid-tier enterprises. Many lack the balance sheet strength to secure traditional credit for these large expenditures. As a result, they often turn to private equity or high-interest lenders, or in some cases are forced to pay cash up front. Even when organizations can afford these purchases, many IT leaders are frustrated in trying to keep pace with AI evolution as the technology can become obsolete before it’s fully deployed.
Techronicler: How does leasing help organizations adopt AI faster than traditional purchasing?
Frank Sommers:
Leasing offers two major advantages that can ease and accelerate AI adoption:
Minimizing upfront costs: Traditional purchasing requires a large cash outlay, which often forces organizations to scale back roll outs even when they need more capacity. Leasing eliminates this barrier by converting a massive one-time upfront expense into manageable monthly payments, freeing up budget for additional needs. For example, instead of spending $50 million upfront, a company could lease the same equipment for a predictable monthly expense, enabling more projects to move forward simultaneously.
Enhancing flexibility and reducing financial risk: When organizations purchase technology, it goes on their balance sheet and depreciates over a set period. If the business needs to change or upgrade the technology before full depreciation, it can result in significant book losses. Alternatively, leasing categorizes the equipment as an operating expense, keeping it off the balance sheet and allowing companies to get in and out of technology quickly without the burden of depreciation or potential financial loss.
Ability to bundle software, security and maintenance: Leasing allows organizations to address AI requirements that go beyond infrastructure – by bunding associated software, maintenance, and security costs into a single package.
Based on these advantages, leasing allows organizations to adopt AI faster by lowering financial barriers, maintaining flexibility, and mitigating risks associated with asset ownership.
Techronicler: What kinds of AI‑related technologies are organizations leasing right now?
Frank Sommers:
The largest category we’re seeing is high-performance compute infrastructure, particularly GPU-based servers designed to handle AI and machine learning workloads. Unlike traditional CPU-based servers, GPUs are optimized for the intense processing demands of AI model training and inference.
Beyond compute, organizations are leasing the full AI technology stack, including: Networking equipment to support high-speed data transfer; enterprise storage systems, often integrated directly into the server environment; data center infrastructure, including fully configured “rack and roll” solutions; security components such as firewalls; and AI-specific and enterprise software that runs on top of the hardware.
Techronicler: Many executives worry about the pace of technology obsolescence. How does leasing address that concern?
Frank Sommers:
Leasing gives organizations flexibility and helps them stay proactive in managing technology lifecycles. Instead of committing to five years of ownership, a three- or four-year lease encourages regular review of what’s in use. At the end of the term, companies can decide to extend the lease, buy out the equipment, or return it and upgrade to newer technology.
This approach prevents the “set it and forget it” mindset that often happens with technology ownership, where equipment ages silently until a critical failure or performance gap forces costly, reactive decisions. In the AI and data center space, this can easily triple costs. Leasing ensures companies remain agile, continuously optimizing their infrastructure and aligning with the latest technology advancements without over-investing or falling behind.
Techronicler: Security and compliance are top-of-mind with any technology deployment. How does a leasing approach support these areas?
Frank Sommers:
Leasing allows organizations to bundle all associated software, maintenance, and security costs into a single package. This includes embedded software, add-on applications, and ongoing maintenance contracts.
Hardware and infrastructure is treated with a residual value, typically 10–15% below its purchase cost, spread over the lease term.
All “soft costs” such as software licenses, maintenance and other services are included in the lease payments and automatically expire at the end of the term, since software licenses can’t be resold.
Clients only assume responsibility for the hardware at lease end, simplifying compliance and ensuring that security-related updates, patches and licenses remain current throughout the lease.
By bundling hardware and software this way, IT leaders can reduce administrative overhead, ensure compliance with licensing requirements, and keeps security measures up to date – side stepping the risk of aging, insecure and unsupported systems.
Techronicler: What advice would you give to enterprise leaders planning large-scale AI adoption in 2026 and beyond?
Frank Sommers:
AI technologies are evolving rapidly, and no one can predict what the landscape will look like in three years. Leasing infrastructure allows organizations to adapt, upgrade, or pivot as business needs change. Owning large amounts of rapidly depreciating technology can leave companies stuck with outdated assets that no longer align with their strategy.
Leaders must also account for the full lifecycle cost of AI infrastructure. Equipment refresh, secure data wiping, asset disposition, and compliance requirements all carry operational and financial burdens. When organizations own the equipment outright, those responsibilities and costs fall entirely on them, and they can be significant.
The most important priority for IT leaders right now is developing a strategy that enables AI adoption with the least possible upfront cost, and which offers maximum flexibility. AI initiatives can be capital intensive, and if organizations commit the bulk of their budget to a single large purchase, they risk not having the funding for other critical projects.
Instead of paying cash and quickly exhausting a $10 or $50 million IT budget, leaders should think of IT leasing as a budget multiplier. For example, rather than spending $10 million upfront, that same capital can be allocated toward predictable monthly lease payments. By doing so, organizations can realize greater total project value while preserving liquidity and maintaining momentum across the broader IT roadmap.
“Instead of paying cash and quickly exhausting a $10 or $50 million IT budget, leaders should think of IT leasing as a budget multiplier.”
That powerful advice from Frank Sommers fundamentally shifts how we should think about enterprise AI strategy. As we discussed, the operational and financial burdens of equipment refresh, secure data wiping, and asset disposition can be significant when organizations own their equipment outright. By treating AI as an operating expense, IT leaders can maintain the flexibility to adapt and upgrade as business needs change.
A huge thank you to Frank for sharing his deep expertise in IT lifecycle management and enterprise procurement. For IT leaders planning large-scale AI adoption in 2026 and beyond, prioritizing maximum flexibility and the lowest possible upfront costs is clearly the winning playbook.
Frank Sommers brings 30 years of experience in the IT leasing industry, working closely with global enterprise organizations to help them modernize infrastructure while preserving capital and accelerating technology adoption. Known for consistently exceeding sales targets, Frank has also developed and led numerous successful vendor financing programs in partnership with major resellers, creating flexible acquisition models that support complex IT environments. His deep expertise in IT lifecycle management, financing strategies, and enterprise procurement has made him a trusted advisor across the industry. A former collegiate soccer player at Cal Poly San Luis Obispo, Frank brings the same competitiveness and teamwork to every client relationship.