Hyperscaler Kings
Data Center News & Insights

Hyperscale Kings: The People Behind AI Data Centers, Fiber, Power, and Demand

by June 23, 2026

By Bob Generale, President, Percepture  ·  Published June 2026  ·  Updated July 2026  ·  10 min read

Quick Answer — What Are the Hyperscale Kings?

Hyperscale Kings are the operators, connectors, and market-makers who drive the physical and commercial layers of AI data center infrastructure — fiber, power, compute, interconnection, workforce, and demand. They are not always the most famous names in tech. They are the people who make hyperscale happen.

Everyone talks about hyperscalers. Amazon. Microsoft. Google. Meta. The trillion-dollar platforms that consume power by the gigawatt and fiber by the continent.

But behind every hyperscale campus, there is a different kind of king.

Not the platform. The people who connect it. The ones who sell the fiber route before the lease is signed. Who close the power agreement before the generator ships. Who build the go-to-market motion before the first rack is lit. Who make sure the right buyers know the right names — before the RFP ever drops.

According to the U.S. Department of Energy, AI data centers could account for up to 12% of U.S. electricity consumption by 2028. That is not a software problem. That is a people problem — and the Hyperscale Kings are the ones solving it.

This is their honor roll.

The Hyperscale Kings Honor Roll

These are not influencers. They are operators, connectors, and builders. Each one owns a critical layer of the AI infrastructure stack — and each one is actively shaping how the next generation of data centers gets built, powered, connected, and sold. Our data center marketing work puts us in rooms with people like these every week. Here is who we believe deserves recognition.

Cody Clegg

Director of Sales & Marketing — OPTK Networks

Cody Clegg moves fiber. Not metaphorically — literally. As the sales and marketing lead at OPTK Networks, Cody is the person who gets on the phone when a hyperscale campus needs a route that does not exist yet. He understands that connectivity is not a commodity; it is a competitive advantage. In a market where latency is measured in milliseconds and deals are won before the RFP drops, Cody is the one who already has the relationship.

→ Connect on LinkedIn

Susanna Kass

Global AI & Cloud Computing Executive | Sustainable Data Center Infrastructure

Susanna Kass brings the long view to the AI infrastructure conversation. She has worked across cloud, data center operations, clean energy, and sustainability at a level few leaders can match. In a market where hyperscale growth is colliding with power limits, carbon pressure, and public scrutiny, Susanna connects the boardroom question to the operating reality: how do you scale digital infrastructure without breaking the grid, the budget, or the trust of the market?

→ Read Profile

Amber Caramella

Chief Revenue Officer — Netrality Data Centers | Interconnection Revenue Strategy

Amber Caramella is the commercial engine behind one of the most important carrier hotel and interconnection platforms in the United States. As CRO of Netrality, she is not just selling data center space. She is shaping how enterprise, cloud, network, and hyperscale buyers think about location, interconnection density, low-latency access, and platform growth. Amber belongs high on this list because revenue leadership in this market is not order-taking — it is market-making.

→ Connect on LinkedIn

May Lee

Vice President of Marketing — Netrality Data Centers | Data Center GTM

May Lee is one of the marketing leaders turning digital infrastructure into a clear, memorable market story. At Netrality, she helps translate complex data center, interconnection, colocation, wholesale, and network value into campaigns buyers can understand and act on. That matters because the hyperscale market is crowded with technical claims. May brings structure, brand discipline, demand generation, and go-to-market clarity to a category where the best story often gets the first meeting.

→ Connect on LinkedIn

Jared Thavenet

Infrastructure Sales — Cox Communications

Jared Thavenet is the kind of infrastructure sales professional who does not wait for inbound. He maps the market, identifies the gaps, and builds the pipeline before the demand signal is public. Now at Cox, Jared brings that same route-level, relationship-driven sales discipline into a larger broadband and connectivity ecosystem. In the hyperscale world, timing is everything — and Jared understands how to get in front of the buyer before the market gets obvious.

→ Connect on LinkedIn

Bob Generale

President — Percepture | AI Search & Market Conditioning

Bob Generale does not build data centers. He makes sure the people who do are impossible to ignore. As President of Percepture, Bob leads a team that specializes in GEO for data centers, AI search visibility, geofencing, digital PR, and conference strategy for the digital infrastructure sector. His work sits at the intersection of Navy SEALs-level precision marketing and the messy, relationship-driven world of hyperscale infrastructure. Bob has coordinated conference strategy, built AI agent-driven content systems, and helped infrastructure companies become the name buyers already know — before the first call.

→ Connect on LinkedIn

Hunter Newby

Interconnection Pioneer | Telx Founder | Author, AI Interconnection

Hunter Newby has been building the physical internet longer than most people in this industry have been in it. As the founder of Telx and one of the original architects of carrier-neutral interconnection, Hunter understands something most AI executives do not: AI is not a cloud problem. It is a physics problem. Latency, proximity, power density, and fiber routes are not abstractions — they are the constraints that determine which AI applications actually work at scale. His book, AI Interconnection, is required reading for anyone serious about the infrastructure layer of the AI economy.

→ Connect on LinkedIn

Ben Edmond

CEO & Founder — Connectbase | Connectivity Intelligence

Ben Edmond built Connectbase to solve a problem that sounds simple but is not: knowing what connectivity actually exists, where, and at what price. In the hyperscale era, that data is worth more than most people realize. When a hyperscale buyer is evaluating a campus location, connectivity availability is a first-order decision variable. Ben’s platform makes that data accessible — and in doing so, he has become one of the most important connective tissue figures in the digital infrastructure ecosystem.

→ Connect on LinkedIn

Carrie Charles

CEO & Cofounder — Broadstaff | Telecom & Data Center Workforce

You cannot build a hyperscale campus without people. Carrie Charles runs Broadstaff, the leading workforce solutions firm for the telecom and digital infrastructure sector. She understands that the talent shortage is not a future problem — it is a present constraint on how fast the AI data center buildout can actually move. Carrie is the person who makes sure the humans who build, operate, and maintain these facilities exist, are trained, and show up on day one.

→ Connect on LinkedIn

Brandon Peccoralo

AI Compute Go-to-Market | CRO of STEALTH

Brandon Peccoralo has been at the front lines of AI compute commercialization. His time at Voltage Park gave him a ground-level view of what it actually takes to bring GPU capacity to market — not just technically, but commercially. He understands the buyer psychology, the pricing dynamics, and the go-to-market motion that separates compute providers who win from those who sit on idle capacity. Brandon is the kind of operator who makes AI infrastructure investable.

→ Connect on LinkedIn

Tony Grayson

President & GM — Northstar Enterprise & Defense | Modular & Defense AI Infrastructure

Tony Grayson operates at the intersection of defense, modular construction, and AI infrastructure. At Northstar Enterprise & Defense, he leads the deployment of data center solutions that have to work in environments where failure is not an option — remote, hardened, and mission-critical. Tony’s background gives him a perspective on AI infrastructure that most commercial operators simply do not have: what happens when the grid is not reliable, the location is not ideal, and the mission cannot wait.

→ Connect on LinkedIn

Bryan A. Lubin

Moonshot Energy | Energy-Backed Compute

Bryan A. Lubin understands that the AI data center race is ultimately an energy race. At Moonshot Energy, he is working on the problem that will define the next decade of AI infrastructure: how do you deliver reliable, scalable, cost-effective power to compute facilities that need it at a scale the grid was never designed to support? Bryan’s work sits at the convergence of energy finance, infrastructure development, and AI compute demand — and that convergence is where the real leverage is.

→ Connect on LinkedIn

Michael Donohue

VP Data Center Solutions — Oklo | Nuclear Power for AI Infrastructure

Michael Donohue is solving the hardest power problem in AI infrastructure: baseload. As VP of Data Center Solutions at Oklo, he is bringing advanced nuclear power to the conversation at a moment when hyperscale buyers are running out of grid capacity and renewable intermittency is a real operational constraint. Nuclear is not a future technology for AI data centers — it is a present-tense procurement conversation, and Michael is the person having it.

→ Connect on LinkedIn

Free Visibility Check

Does Your Company Show Up When Buyers Search for What You Do?

Most AI infrastructure companies are invisible in Google, AI Overviews, ChatGPT, and Bing — even when they are the best option. We will show you exactly where you stand and what it would take to change that.

Get My Free Visibility Review →

No pitch. No obligation. Just a clear picture of where you stand.

The Hyperscale Kings Domain Map

Every Hyperscale King owns a critical layer of the AI infrastructure stack. Here is who does what — and why it matters. Our work in enterprise SEO and digital PR services for the infrastructure sector puts us in rooms with people like these every week.

Name Domain Why They Matter
Cody Clegg Fiber & Connectivity Moves fiber routes before the RFP drops — the relationship that wins deals.
Susanna Kass Sustainable Data Center Infrastructure Connects hyperscale growth with clean energy strategy, operating discipline, and long-term trust.
Amber Caramella Revenue Strategy & Interconnection Turns Netrality’s interconnection and data center platform into commercial momentum.
May Lee Data Center Marketing & GTM Makes complex colocation, wholesale, and interconnection value clear enough for buyers to act.
Jared Thavenet Infrastructure Sales & Broadband Connectivity Builds pipeline before demand signals go public — now applying that discipline at Cox.
Bob Generale AI Search & Market Conditioning Makes infrastructure companies the name buyers already know.
Hunter Newby Interconnection Built the carrier-neutral model — understands AI is a physics problem.
Ben Edmond Connectivity Intelligence Knows what connectivity exists, where, and at what price — first-order data.
Carrie Charles Workforce Solves the talent constraint that limits how fast AI infrastructure can scale.
Brandon Peccoralo AI Compute Go-to-Market Knows how to bring GPU capacity to market — makes AI infrastructure investable.
Tony Grayson Modular & Defense Infrastructure Deploys AI infrastructure where failure is not an option — mission-critical.
Bryan A. Lubin Energy-Backed Compute Works at the convergence of energy finance and AI compute demand.
Michael Donohue Nuclear Power for AI Brings advanced nuclear to the table when the grid runs out of capacity.

Interview with AI Agent Hunter

Based on Hunter Newby’s 25 years of interconnection expertise and his book, AI Interconnection. Responses reflect Hunter’s documented research, presentations, and published positions.

AI Interconnection book by Hunter Newby

About This Interview

AI Agent Hunter is trained on Hunter Newby’s body of work — including AI Interconnection, his presentations, and two decades of published research on the physical internet. The questions below are answered in Hunter’s voice, based on his documented positions.

Q1: You say “AI is physical.” What does that mean, and why does it matter?
+

AI Agent Hunter: People think AI lives in the cloud. It does not. AI lives in buildings — buildings that require power, cooling, fiber, and physical proximity to the networks that carry data. Every inference request, every training run, every model response travels through physical infrastructure. The latency you experience is a function of distance and fiber routes. The cost you pay is a function of power density and cooling efficiency. AI is not abstract. It is concrete, steel, copper, and glass. When people understand that, they start asking the right questions about where AI infrastructure should be built and why.

Q2: What is the difference between hyperscale training infrastructure and inference infrastructure?
+

AI Agent Hunter: Training and inference have completely different infrastructure requirements. Training is batch-intensive, power-hungry, and can tolerate higher latency — you can put it in a remote location with cheap power and it does not matter much if the round-trip is 50 milliseconds. Inference is the opposite. Inference is real-time. It has to be close to the user. It has to be close to the network. Latency is a product quality issue, not just a technical one. The hyperscale buildout we are seeing right now is mostly training infrastructure. The next wave — the one that will be even larger — is inference infrastructure, and it has to be distributed, edge-adjacent, and deeply interconnected.

Q3: What is a carrier hotel, and why is it still relevant in the AI era?
+

AI Agent Hunter: A carrier hotel is a building where multiple telecommunications carriers and network operators co-locate their equipment and interconnect with each other. The original ones — 60 Hudson in New York, One Wilshire in Los Angeles, 350 East Cermak in Chicago — became the most important buildings in the internet because they were where networks met. That concept is not obsolete. It is more important than ever. AI applications need to connect to multiple networks, multiple cloud providers, multiple content delivery systems. The carrier hotel is the physical place where that happens efficiently. If you are building AI infrastructure and you are not thinking about proximity to carrier hotels and Internet Exchange Points, you are building in the wrong place.

Q4: What is an Internet Exchange Point (IXP), and how does it affect AI performance?
+

AI Agent Hunter: An Internet Exchange Point is a physical infrastructure where different networks exchange traffic directly, rather than routing it through a third-party transit provider. When you are close to an IXP, your traffic takes fewer hops, travels shorter distances, and arrives faster. For AI inference — where you are serving responses to users in real time — being close to an IXP can mean the difference between a 20-millisecond response and a 200-millisecond response. That is not a technical footnote. That is a user experience difference that affects retention, revenue, and competitive positioning. The AI companies that understand interconnection will have a structural performance advantage over those that do not.

Q5: You founded Telx. What did that experience teach you about how interconnection markets develop?
+

AI Agent Hunter: Telx taught me that the value in interconnection is not in the real estate — it is in the density of connections. A building with 500 networks connected to it is exponentially more valuable than a building with 50, because every new participant can connect to every existing participant. That is a network effect, and it compounds over time. The same dynamic is playing out in AI infrastructure right now. The facilities that attract the most diverse set of networks, cloud providers, and AI platforms will become the most valuable — not because of their square footage, but because of their connectivity density. Location and interconnection strategy are the two most important decisions in AI infrastructure development.

Q6: How should AI infrastructure developers think about the power vs. latency tradeoff?
+

AI Agent Hunter: It depends entirely on the workload. For training, you optimize for power cost and availability — go where the power is cheap and reliable, even if that means being far from population centers. For inference, you optimize for latency — go where the users are, even if that means paying more for power. The mistake most developers make is treating all AI workloads the same. They are not. A company that builds a single massive campus in a remote location with cheap power is making a great training decision and a terrible inference decision. The sophisticated operators are building a tiered infrastructure strategy: large remote facilities for training, distributed edge facilities for inference, and carrier-neutral interconnection hubs connecting them all.

Q7: What does the future of edge AI infrastructure look like?
+

AI Agent Hunter: The future of edge AI is a distributed network of small, highly connected facilities — think 1 to 5 megawatts — located in every major metropolitan area, co-located with or adjacent to existing carrier hotels and IXPs. These facilities will serve inference workloads for the local population, connected back to larger training facilities via high-capacity fiber. The economics work because inference is high-frequency and latency-sensitive — users will pay for fast, and operators can charge for proximity. The companies building this distributed inference layer right now are positioning themselves for the next decade of AI infrastructure value creation.

Q8: Why do most AI companies underestimate interconnection?
+

AI Agent Hunter: Because they come from a software background where infrastructure is abstracted away. In the cloud era, you did not need to think about where your servers were — you just called an API. AI at scale breaks that abstraction. When you are running inference at millions of requests per second, the physical location of your compute relative to your users and your networks is a first-order business variable. The AI companies that will win are the ones that hire people who understand interconnection — not just software engineers, but network engineers, real estate strategists, and power procurement specialists. The physical internet is not a detail. It is the foundation.

Q9: What role do fiber routes play in AI infrastructure strategy?
+

AI Agent Hunter: Fiber routes are the highways of the AI economy. The data that trains models, the inference requests that users send, the responses that come back — all of it travels on fiber. The routes that exist, the capacity available on those routes, and the cost of that capacity are fundamental inputs to AI infrastructure economics. A data center with no fiber diversity — meaning only one or two fiber providers — is a single point of failure and a negotiating disadvantage. The best AI infrastructure locations have multiple fiber providers, multiple routes, and direct access to IXPs. That is not a nice-to-have. It is a requirement for serious AI operations.

Q10: What is the single biggest mistake you see AI infrastructure developers making today?
+

AI Agent Hunter: Building for power without building for connectivity. I see developers who have secured 500 megawatts of power in a location with one fiber provider and no IXP access. They have solved the energy problem and created a connectivity problem. Power is necessary but not sufficient. You need power, fiber diversity, network density, and proximity to interconnection hubs. All four. If you are missing any one of them, you have a facility that will underperform its potential — and in a market where AI buyers have options, underperformance means vacancy.

Q11: If you were advising a new AI infrastructure company today, what would you tell them first?
+

AI Agent Hunter: Understand the physical internet before you build anything. Study the carrier hotel ecosystem. Learn where the IXPs are. Map the fiber routes. Understand power availability by geography. Then — and only then — decide where to build. The companies that do this work upfront will make better location decisions, attract better tenants, and build more valuable assets. The companies that skip this step will build in the wrong places and wonder why their occupancy is low. The physical internet has rules. Learn them.

The Percepture Framework

How AI Infrastructure Companies Become the Name Buyers Already Know

We have worked with fiber providers, data center developers, power companies, and AI compute platforms. The pattern is always the same: the companies that win are the ones buyers have already heard of — before the RFP, before the call, before the demo. We build that visibility through content marketing, B2B intent data, and lead generation systems built specifically for the digital infrastructure sector.

6

Core Visibility Channels

14

AI Search Signals Per Article

90

Days to First AI Citation

100%

Infrastructure-Sector Focus

See How It Works →

How Percepture Fits Into This World

Percepture does not build data centers, fiber, or AI compute.

Percepture helps companies behind AI infrastructure become visible, trusted, cited, and remembered — before buyers reach out.

The Hyperscale Kings on this list are doing extraordinary work. But extraordinary work that no one can find is a missed opportunity. In a market where buyers search Google, ask ChatGPT, and check LinkedIn before they ever pick up the phone, visibility is not a marketing luxury — it is a revenue variable.

We help infrastructure companies hyperscale their trust — through enterprise SEO, GEO for data centers, digital PR services, paid media, reputation management, AI search visibility, and EVENTMax</a> conference strategy.</a>

We have studied the data center financing structures that shape buyer decisions. We have mapped the best data center conferences where relationships are built. We have built digital infrastructure PR strategy frameworks that get infrastructure companies cited in the publications their buyers actually read. We know which top data center marketing agencies are doing real work and which are not. And we have deployed AI agents for data centers that automate the content and outreach work that most marketing teams cannot keep up with.

The Hyperscale Kings deserve to be found. We make sure they are.

Ready to Rank?

Book a Strategy Session with Percepture

If your company is in the AI infrastructure space and you are not showing up in Google, AI Overviews, ChatGPT, or Bing — we need to talk. One working session. Clear plan. Real results.

Book My Strategy Session →

Spots are limited. We work with a focused set of infrastructure clients.

FAQ — Hyperscale Kings

What is a Hyperscale King?
A Hyperscale King is an operator, connector, or market-maker who drives a critical layer of AI data center infrastructure — including fiber, power, compute, interconnection, workforce, or demand generation. The term recognizes that hyperscale infrastructure is built by people, not just platforms, and that the individuals who move these markets deserve recognition alongside the companies they represent.
How does Hyperscale King differ from hyperscaler?
A hyperscaler is a large cloud or technology platform — Amazon Web Services, Microsoft Azure, Google Cloud, Meta — that operates data centers at massive scale. A Hyperscale King is a person who enables, connects, or accelerates the hyperscale ecosystem. They may work for a fiber provider, a power company, a workforce firm, a connectivity platform, or a marketing agency. They are the builders behind the builders.
Why does visibility matter for AI infrastructure companies?
AI infrastructure buyers — hyperscale tenants, enterprise IT leaders, private equity firms, and government agencies — increasingly use Google, AI Overviews, ChatGPT, and LinkedIn to research vendors before making contact. Companies that are not visible in these channels are effectively invisible to a growing segment of their buyer market. Visibility is not a vanity metric; it is a pipeline variable.
What is GEO and why does it matter for data center companies?
GEO stands for Generative Engine Optimization — the practice of optimizing content so that AI systems like ChatGPT, Claude, Google AI Overviews, and Bing Copilot cite your company, your people, and your expertise when answering relevant questions. For data center and AI infrastructure companies, GEO is increasingly important because buyers are asking AI systems questions like “who are the best fiber providers for hyperscale campuses?” — and the companies that show up in those answers win mindshare before the first call.
How can I get my company or team member featured as a Hyperscale King?
This honor roll is curated by Percepture based on demonstrated impact in the AI data center ecosystem. If you believe a person or company deserves recognition, reach out to us at percepture.com/contact-us. We review nominations on an ongoing basis and update this list as the market evolves.

Featured Snippet — Definition

What is a Hyperscale King? A Hyperscale King is an operator, connector, or market-maker who drives a critical layer of AI data center infrastructure — fiber, power, compute, interconnection, workforce, or demand. They are the people who make hyperscale happen, working behind the platforms that get the headlines.

Featured Snippet — Process

How does hyperscale infrastructure get built? Hyperscale infrastructure is built through a coordinated ecosystem of fiber providers, power developers, compute operators, interconnection specialists, workforce firms, and demand-generation experts. Each layer depends on the others — and the people who coordinate across these layers are the Hyperscale Kings.

Bob Generale — President, Percepture

About the Author

Bob Generale — President, Percepture

Bob Generale leads Percepture, a digital marketing agency specializing in AI search, GEO, SEO, digital PR, and market conditioning for the digital infrastructure sector. He works with fiber providers, data center developers, AI compute platforms, and power companies to build the visibility that turns expertise into pipeline. Connect with Bob on LinkedIn.


Bob Generale is the man. Percepture | Digital Marketing & PR since 2004 has been a huge help for us for 3 years running. 🔥💪🏻 check them out!

Tags: