Techaisle Analyst Insights

Channel partners were specific when Techaisle asked what a vendor program should deliver. In our 2026 survey of 5,450 channel partner firms, 88% rate profitability as critical or very important, and 78% say the same about predictability. Strategic value ranks last at 69%. Asked where programs fall short, partners name simplicity first (71%) and predictability second (61%). Predictability is one of the attributes partners value most and one of the two where programs fail most often.

Many of the largest vendors have rebuilt their partner programs over the past 2 years. Some of those changes line up with what partners asked for, and a few work against it. Across the 2026 changes from AWS, Cisco, Microsoft, Google Cloud, Dell, HPE, Lenovo, Palo Alto Networks, and Broadcom, one pattern stands out: programs are getting simpler faster than they are getting predictable. Most of the work went into fewer tiers, merged incentives, and automated paperwork, while the changes that cost partners money came from timing.

Techaisle calls this gap the Incentive-Trust Deficit. Partners will accept thinner margins in exchange for rules that hold for a year. For a vendor, that makes predictability a cheaper lever than a richer rebate. For a partner, a vendor's record of program changes matters as much as its margin structure when deciding where to commit staff.

First, the verdict: the new XPS 14 is a laptop I recommend, and highly. I have a complicated history with the XPS name, though, and so does Dell.

I have been using the XPS brand laptops since 2012, when the first XPS 13 arrived as one of Intel's Ultrabooks, a $999 Windows answer to the MacBook Air. I was not always an easy sell on where Dell took the line next. When 2-in-1s were the fashion, I stood at an Intel offsite and argued for two hours, with Techaisle data behind me, that the category would struggle. I had tried the contraptions, including Dell's original XPS Ferris-Wheel, and none of them convinced me to give up a clamshell. Then a few years later Dell sent me an XPS 13 2-in-1; I put it through a road test, and it made a convert of me. That is the thing about this line. It has a habit of winning arguments I walked in ready to lose.

By 2020, I was calling the XPS 13 perfection personified. I opened the 9300, set it on my desk, and let it sit for three days before I could bring myself to use it. For years, this was the one Windows laptop I could hand to someone without a caveat.

Then Dell decided the name had to go. In 2025, XPS became Dell Premium, the top rung of a new consumer ladder of Dell, Dell Plus, and Dell Premium, while the Pro and Pro Max labels went off to the commercial and workstation machines. It all looked tidy on an org chart and meant nothing to the person actually shopping for a laptop. I sat through more than one briefing where I watched a room full of smart people explain a naming system that answered a question nobody had asked. The machines stayed good throughout.

They just lost the one word that told you so at a glance.

This year Dell admitted it made a mistake and brought XPS back. New design, new silicon, same three letters. I have spent the last few months with the new XPS 14, and I have enjoyed nearly all of it.

Michael Dell opened Dell Technologies World with a line that sounded like theater but was actually a strategy: just as electricity transformed the world when it left the power plant, AI will transform the world when it leaves the screen. With intelligence becoming infrastructure, the job now is to make it real, local, secure, and useful, whether that is on an oil rig, in an ambulance, or on the factory floor.

The most revealing moment came a day later, when Jeff Clarke admitted that his own engineers burned through a month's worth of allocated tokens in a few hours. This happened not because something broke, but because it worked perfectly. Put those two moments together, and you have the entire event's thesis. Michael Dell named the destination (intelligence everywhere it is needed), while Clarke named the bill that arrives when you get there. Ultimately, what Dell announced was not a refresh cycle; it was a bet on where intelligence physically lives, and who pays the meter to run it.

The number that should reset every infrastructure budget

From the keynote stage, Jeff Clarke cited figures that framed everything that followed: token prices have fallen roughly 80% year over year, yet consumption for reasoning has surged 320-fold. Furthermore, inference, not training, now accounts for nearly two-thirds of all AI compute. Whatever the underlying sources of this data, the direction is indisputable and directly mirrors what Techaisle has been tracking from the buyer side all year.

Reading those numbers together leads to an unavoidable conclusion: the unit cost of intelligence is collapsing, yet total spend is accelerating. This is the exact pattern Techaisle named Token Shock. We've seen this curve before with bandwidth, storage, and compute, where cheaper units unlock so much new consumption that the overall bill climbs anyway. What sets this era apart is the sheer speed, as no one has seen a cost curve bend this quickly.

The strategic consequence, and the line Clarke delivered that should be sitting in every CFO conversation, is that as agents take on more cognitive work, costs migrate from headcount to tokens. Historically, cognitive work scaled with human hours; if you wanted more analysis, you hired more analysts. Agentic AI has broken that ratio entirely. Techaisle data puts a number on how far it has already shifted: the Agent-to-Human Ratio has reached 144-to-1 in the midmarket and 59-to-1 in small businesses. With the agentic workforce already deployed at that density, it's alarming that most of the operating models meant to govern it still assume a payroll rather than a token budget.

Dell's actual announcement was an answer to "Where"

Across both keynotes, one question sat underneath every announcement: where should a given token run?

Dell Technologies World 2025 (DTW) recently provided a comprehensive look into Dell's strategy and vision, with a particular focus on the transformative power of Artificial Intelligence (AI) for businesses of all sizes. Keynotes from Michael Dell and Jeff Clarke, alongside detailed briefings on Client Solutions Group (CSG) and Infrastructure Solutions Group (ISG), painted a picture of a company positioning itself as the end-to-end partner for the AI journey. While much attention often focuses on hyperscalers and large enterprises, Dell offers significant opportunities and tailored strategies for the midmarket as well as the vital channel partners who serve them.

Here are my seven key takeaways:

1. The Dell AI Factory is an End-to-End AI Framework, Not Just Hardware

Dell introduced and expanded upon the concept of the Dell AI Factory, describing it as an unmatched set of capabilities in the industry designed to help businesses get started with Generative AI and scale it. It is presented as an open, modular infrastructure with a rich ecosystem, delivering powerful GPUs, scalable storage, high-throughput networking, curated tooling, and integrated cutting-edge models, supported by deployment services. This framework covers the entire computing architecture for modern AI workloads, from PCs to data centers and the edge. Dell has helped over 3,000 businesses build their factories and launched over 200 new features since its inception a year ago. The vision is for customers to bring their own company data to the AI Factory, driving unique business outcomes.

Why this is important for Midmarket and Channel Partners: This framework provides a structured approach to AI adoption. For midmarket, it demystifies the complex landscape of AI infrastructure by offering a seemingly integrated and supported stack. They don't need to piece together disparate components or become AI experts overnight. For channel partners, the AI Factory is a complete solution portfolio to take to customers. Dell is making it easier to consume and deploy through reference architectures and packaged software. This enables partners to concentrate on delivering value and outcomes, rather than merely selling individual pieces of hardware. The concept of bringing "your own company data" to drive outcomes resonates strongly with businesses of all sizes, emphasizing that AI value is tied to their unique operations and data, which partners are often intimately familiar with.