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Notes from The Telarus Partner Summit

One of the clearest takeaways from the Telarus Partner Summit in Dallas was that the Technology Advisor market looks healthy, but it is changing quickly.

Three themes stood out.

The TA Model Is Still Strong

Technology Advisors remain valuable because customers are dealing with more complexity, not less.

The conversation is no longer just about circuits, voice or individual cloud applications. Customers increasingly need help understanding how cybersecurity, cloud, communications, managed services and AI fit together.

That favors the advisor who understands the customer's business and can assemble the right combination of technologies and partners.

The role continues to move from broker toward business technology advisor.

AI Is the Opportunity, and the Challenge

AI was everywhere in Dallas.

Customers want it, but many still do not know what they should buy, how they should govern it, or how to connect it to the systems they already use.

That creates a major opportunity for Technology Advisors, and it is also where we believe Vx has something unusually interesting.

The Vx GoodWeek platform brings multiple AI models and more than 1,000 integrations into a single governed interface. The user can work across email, CRM, accounting, calendars, payments and other business systems without constantly jumping between applications.

That was the part of the story that consistently produced the strongest reaction in Dallas.

People were not particularly impressed because we could show them another AI chatbot. There are plenty of those.

They reacted to the idea that AI could become a business operating layer, one place to interact with information scattered throughout the company.

We came away believing that Vx GoodWeek may be one of the most interesting AI offerings entering the Technology Advisor market right now.

And perhaps more importantly, the response from the channel suggested we are not the only ones who think so.

Scale Matters More

The other unmistakable trend is consolidation.

Private equity, acquisitions, larger partner organizations and sub-agent models are putting pressure on firms to think about scale.

That does not mean every successful TA needs hundreds of employees.

It does mean the modern advisor increasingly needs access to capabilities they may not own internally: engineering, cybersecurity expertise, AI expertise, implementation resources, support and marketing.

That is driving larger partnerships, affiliations and roll-up opportunities.

The independent TA can still win. But increasingly, independence does not mean operating alone.

What May Be Coming Next

The most interesting conclusion from Dallas may be bigger than any individual product.

For the past few years, the market has been focused on the AI model itself, ChatGPT, Claude, Gemini and whichever model comes next.

But businesses do not really want another place to log in and talk to an AI.

They want a layer that sits across the business, connects the systems they already use, understands the data they are permitted to access, and helps them get work done.

Call it the AI Business Layer: ABL.

The model underneath it may change. The applications connected to it will change. The device we use to access it will certainly change.

But the concept is much more durable:

One intelligent, governed layer connecting people to the information and systems required to run the business.

That is what seemed to capture people's imagination in Dallas.

The Bottom Line

The Technology Advisor market looks strong. Customers need more help, the solutions are becoming more sophisticated, and the channel continues to evolve toward higher-value advisory work.

At the same time, the next major technology category may already be starting to appear.

Cloud changed where applications lived.

SaaS changed how businesses bought them.

AI is changing how people interact with them.

The AI Business Layer may be what connects all of it together.

If Dallas was any indication, the market is healthy, and the next big thing may already be peeking around the corner.

For years, the smartphone has been an extraordinarily powerful computer constrained by one obvious problem: the screen is too small to do much real work comfortably.

We read email on it. We approve things. We answer Teams messages. We check dashboards. We may even make a quick change to a document.

But when it is time to actually work, most of us still reach for a laptop.

Foldable glass may be about to change that.

Glass That Isn't Supposed to Bend

One of the technologies making the next generation of phones possible sounds almost contradictory: glass that folds.

Corning has developed commercially available ultra-thin glass specifically designed to bend and fold while retaining the optical qualities expected from a premium display. The company says its technology can flex, fold and potentially even roll, opening possibilities well beyond today's conventional flat screens.

The significance isn't merely that someone can make an interesting-looking phone.

It means manufacturers can put a substantially larger display into something that still fits in your pocket.

And that changes the equation.

Samsung Is Already There

Samsung is no longer treating folding phones as an experiment.

Its newly released Galaxy Z Fold8 family takes the idea directly into mainstream premium smartphones. Samsung's Fold8 opens to a 7.6-inch display, while the Fold8 Ultra offers an 8-inch main screen. Samsung is explicitly positioning these devices for multitasking and business use, including reports, dashboards, video meetings and multiple applications running side by side.

An 8-inch screen isn't simply a bigger telephone screen. It starts approaching small-tablet workspace territory, except it folds and goes back into your pocket.

Samsung has also put considerable AI processing directly into the device. Its current Fold8 uses a processor incorporating CPU, GPU and NPU resources, with the NPU specifically supporting AI functions.

Hardware, screen real estate and AI are beginning to converge.

And Then Comes Apple

Apple has not officially released a foldable iPhone, so rumors need to remain rumors until Apple says otherwise.

But this is no longer an obscure supply-chain story.

Reuters reported earlier this year that Apple has been working toward its first foldable iPhone, with a possible 2026 introduction, although engineering and production challenges could still affect timing. Reuters has also reported that Apple views the foldable device as an important part of its premium iPhone strategy.

If Apple enters the market, the significance could extend well beyond another high-end iPhone.

Apple has a history of taking a technology category that already exists and helping make its use mainstream.

And mainstream foldables could arrive at almost exactly the same time that another technology is changing what we expect a computer to do.

AI.

This Is Where It Gets Interesting

Think about what business AI is becoming.

An AI business platform such as GoodWeek isn't simply another chatbot. It can sit across the information you already use, email, files, SharePoint, accounting systems, business applications and organizational knowledge, and let you interact with that information conversationally.

Now put that capability onto an 8-inch foldable display.

Suddenly your phone isn't asking you to navigate six tiny applications to accomplish something.

You can ask:

"Show me the customers who owe us the most money."

"Find the email where we agreed to that price."

"Compare this invoice with the proposal."

"Summarize what happened on this account before I walk into the meeting."

"Draft the response and show me the supporting documents."

That is fundamentally different from trying to run Excel on a 6-inch telephone screen.

The AI does much of the navigation, searching, assembling and computing. The larger foldable screen becomes the workspace where you interact with the result.

That combination may be far more important than either technology by itself.

The Phone Becomes a Business Device Again

For years we have discussed whether smartphones might eventually replace PCs.

They haven't.

The problem wasn't computing power. Modern phones have enormous computing capability.

The problem was the interface.

A tiny screen plus dozens of applications, menus and keyboards simply isn't a particularly good environment for serious work.

Foldable glass attacks the first problem.

AI attacks the second.

Instead of making you operate the software, AI increasingly operates across the software on your behalf.

And instead of trying to see the result through a conventional phone-sized window, you unfold the device into something approaching a tablet.

Pocket sized when you carry it.
Tablet sized when you open it.
AI powered when you work.

That is a much more compelling vision of mobile computing.

Your Next "Cellie" May Be Something Different

Samsung is already selling this future. Apple appears increasingly likely to join it.

The first generations will remain expensive. There will be questions about hinges, durability, battery life, screen creases and whether consumers really want to spend nearly $2,000 on a telephone. Samsung's Galaxy Z Fold8 currently starts at $1,899.99 in the United States.

Those are legitimate issues.

But technology tends to become interesting when several developments arrive at the same time.

Foldable glass is getting better.

Screens are getting larger.

Processors now include dedicated AI hardware.

Business AI is becoming capable of working across applications and company information.

And the software increasingly understands what we want instead of requiring us to understand where every piece of information lives.

Put those together and the foldable phone starts looking like something more important than a phone with a clever hinge.

It may be the form factor that finally makes serious AI-powered work from the device in your pocket genuinely practical.

Your next cellie may still make phone calls.

That could be one of the least interesting things it does.

If you have looked at a new business computer recently, you have probably encountered a new collection of acronyms. CPU. GPU. NPU. AI PC. Copilot+ PC. NVIDIA seems to be everywhere.

What do all these processors actually do, and does the average business user need them?

The easiest place to start is with the processor we have used for decades.

The CPU Still Runs the Computer

The CPU, or Central Processing Unit, remains the primary processor in your PC. Windows, Outlook, Excel, QuickBooks, your web browser and most traditional business applications rely primarily on the CPU.

Modern CPUs are extremely powerful. For ordinary office work, the CPU remains the most important processor in the machine.

But as computers have been asked to perform increasingly specialized work, manufacturers have added processors optimized for particular types of calculations.

That is where the GPU and NPU come in.

The GPU: Built for Massive Parallel Processing

The GPU, or Graphics Processing Unit, originally became important because computers needed a specialized processor to draw complex graphics quickly.

Rather than processing a relatively small number of complicated instructions like a CPU, a GPU can perform enormous numbers of similar calculations simultaneously.

That turned out to be useful for much more than graphics.

Artificial intelligence involves exactly this type of mathematics. Training and running large AI models requires huge numbers of calculations that can be performed in parallel. That is one reason NVIDIA, the dominant supplier of high-performance GPUs, has become so closely associated with the AI revolution.

The enormous NVIDIA systems being installed in AI data centers are GPUs, although they bear little resemblance in power, size or cost to the graphics chip in a normal office computer.

You can also buy laptops with dedicated NVIDIA GPUs. They are valuable for applications such as:

There is a tradeoff. A powerful dedicated GPU requires considerably more electricity, generates more heat and usually requires more cooling. That means a larger, heavier laptop with shorter battery life.

For most business users, that is unnecessary.

The NPU: The New AI Specialist

The NPU, or Neural Processing Unit, is newer to mainstream PCs.

It is designed specifically to perform AI calculations efficiently.

Think of the difference this way:

A powerful GPU is built to say, "Give me a huge computational problem and I will process it extremely quickly."

An NPU is designed to say, "Give me these AI tasks and I will keep handling them efficiently without consuming much power."

That makes an NPU particularly useful in a laptop.

For example, an NPU can assist with things such as:

Many of these processes can run continuously. Having a specialized low-power processor handle them means the CPU remains available for your traditional applications while preserving battery life.

Do You Need an NPU?

Today, for normal office computing, the answer is no.

A good computer without an NPU will still run Outlook, Word, Excel, Teams, QuickBooks, SharePoint and normal web applications perfectly well.

Most of the AI that businesses currently use also operates in the cloud.

When you use ChatGPT, Claude, Microsoft 365 Copilot or most enterprise AI platforms, the enormous AI model is generally running in a data center. Your laptop does not need an NVIDIA GPU or a powerful NPU to ask the model a question.

The NPU becomes important when more of that intelligence moves onto the local computer.

That transition is already beginning.

Microsoft's Copilot+ PC specification, for example, established a new class of Windows computers with powerful NPUs capable of supporting local AI features. Intel, AMD and Qualcomm are now building increasingly capable AI processors directly into mainstream PCs.

So Why Doesn't Every Laptop Have an NVIDIA GPU?

Because it would be the wrong tool for most users.

Consider a thin business laptop.

The goal is usually:

Light weight.
Long battery life.
Low heat.
Quiet operation.
Strong everyday performance.

Installing a large dedicated NVIDIA GPU works against several of those goals.

Instead, a modern business laptop might contain a CPU, an integrated GPU and an NPU together. Each processor handles the work for which it is best suited.

That is increasingly the architecture of the modern PC.

The Bigger Change

For years, buying a business computer was mostly a discussion about processor speed, memory and storage.

AI is changing that conversation.

We are moving toward computers that contain several different processing engines:

CPU: Runs the computer.

GPU: Handles graphics and large-scale parallel computation.

NPU: Handles specialized AI tasks efficiently.

And behind all three sits another layer: enormous cloud-based GPUs running the largest AI models in data centers.

The important point is that these technologies are not really competing with one another. They perform different jobs.

For the average business user today, a powerful NPU is a useful feature rather than an absolute requirement. A dedicated NVIDIA GPU is generally unnecessary.

But if you are purchasing computers that you expect to keep for four or five years, the NPU is becoming increasingly worth having.

The PC is evolving from a machine with one primary processor into a collection of specialized processors working together.

AI is one of the major reasons why.