Sheldon Bennett on Why DMG Blockchain’s Decade of Digital Infrastructure Experience May Be Its Greatest AI Advantage

Artificial intelligence may be the hottest investment theme in global markets today, but according to Sheldon Bennett, CEO and Director of DMG Blockchain Solutions Inc. (TSXV: DMGI | OTCQB: DMGGF), the companies best positioned to participate may not necessarily be the ones investors expect.

During a recent conversation with InvestorNews host Tracy Hughes, Bennett discussed DMG’s newly announced Letter of Intent to develop a 50-megawatt AI data center at the Company’s Christina Lake property in British Columbia. The announcement was met with an enthusiastic response from investors, reflecting growing market interest in AI infrastructure and the enormous demand for computing capacity that continues to emerge worldwide.

For Bennett, however, the story is not about abandoning blockchain or digital assets. It is about leveraging infrastructure and expertise that DMG has spent years building.

“We’ve been telling the market that this is a direction we want to go into,” Bennett explained. “We’ve been telling the market that we believe our Christina Lake property is suited for this type of use case.”

That distinction matters.

Unlike many companies now attempting to enter the AI infrastructure space, DMG is not starting from scratch. For nearly a decade as a public company, and for even longer as an operator of large-scale digital infrastructure, DMG has been managing the very assets that AI developers increasingly require: power, cooling, security, networking, and operational expertise.

The similarities between modern Bitcoin mining operations and AI data centers are more substantial than many investors realize.

Both industries consume enormous amounts of electricity. Both require sophisticated cooling systems. Both depend on highly reliable network infrastructure. Both demand operational uptime and security.

As Bennett noted, DMG already possesses significant infrastructure that can be adapted for AI workloads.

“We happen to have 12 megawatts of cooling capacity sitting on the ground,” he said. “A lot of infrastructure doesn’t need to change.”

That existing infrastructure may allow DMG to move faster than many competing projects.

While AI data center developments are often measured in years, Bennett believes DMG could potentially deliver an initial phase before the end of 2026. Discussions are currently underway regarding the size and timing of that first deployment under the proposed agreement.

The speed of execution is only part of the story.

Equally important is the identity of DMG’s proposed co-location partner and the financial support behind the project.

One challenge facing many AI infrastructure developers is financing. The cost of building facilities capable of supporting large-scale AI workloads is substantial. In many cases, companies are forced to raise large amounts of capital before knowing whether customers will ultimately commit to the project.

DMG chose a different path.

Rather than building first and searching for customers later, Bennett explained that the Company focused on understanding what potential AI operators required, completing the necessary due diligence, and identifying a partner capable of supporting development.

“A lot of people say they’re ready for AI,” Bennett observed. “A lot of people say they’re going to do AI. But the cost of this is very expensive.”

That practical perspective runs throughout Bennett’s view of the sector.

The current excitement surrounding AI has created the impression that any site with power and internet connectivity can become a successful data center. Bennett believes the reality is far more complicated.

“People think that because they have power and internet, they have an AI deal,” he said.

One of the largest challenges is fiber connectivity.

The scale of data transmission required by modern AI applications is enormous, and in many regions the telecommunications infrastructure simply does not yet exist to support it. Upgrading those networks requires coordination with telecommunications providers, significant investment, and considerable time.

Infrastructure is only one consideration.

Trust is another.

Bennett points out that a fully built AI facility can contain billions of dollars’ worth of graphics processing units and associated computing hardware. Companies deploying that equipment need confidence in both the physical infrastructure and the people operating it.

That is where DMG’s history may prove valuable.

The Company has spent years securing digital assets, operating blockchain infrastructure, managing large-scale power systems, and defending networks against increasingly sophisticated cyber threats.

Among its credentials is SOC 2 compliance, an important security standard that demonstrates the Company’s commitment to information security and operational controls.

“These are the types of things that potential co-location partners look at,” Bennett explained.

The Christina Lake site itself offers additional advantages.

The property benefits from significant physical security, a large fenced footprint, ownership of its own electrical substation, and redundant power generation capability through natural gas generation. Those features provide flexibility and resilience that are increasingly important to long-term data center operators.

For Bennett, the AI opportunity is not an isolated project but potentially the beginning of a broader strategy.

DMG continues to evaluate additional locations in both Canada and the United States, and success at Christina Lake could provide a foundation for future expansion.

At the same time, the Company continues to advance its existing businesses.

Investors can expect updates related to DMG’s trust company operations, expanded digital asset services, developments involving its partnership with Malahat, and growing interest in the Company’s modular prefabricated data center solutions.

Interestingly, Bennett noted that the AI announcement has generated inbound interest not only for large-scale deployments but also for smaller AI projects requiring one or two megawatts of capacity. Those opportunities align closely with DMG’s modular data center offerings and represent another potential avenue for growth.

What emerges from the discussion is not a company reinventing itself, but one applying hard-earned expertise to a rapidly evolving market opportunity.

For years, DMG built infrastructure to support blockchain networks and digital assets. Today, many of those same capabilities—power management, cooling systems, cybersecurity, network operations, and data center expertise—are becoming increasingly valuable in the world of artificial intelligence.

The investment thesis is therefore not Bitcoin versus AI.

It is whether a company that has spent years operating at the intersection of digital infrastructure, power management, cybersecurity, and compute-intensive workloads can leverage those capabilities across multiple high-growth industries simultaneously.

If Bennett is correct, DMG’s blockchain experience may prove to be one of its most valuable competitive advantages in the emerging AI economy.

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