Enterprise AI is moving from pilots into production, and Dell Technologies is adjusting its partner story to match. Last month, at SC25, Dell introduced a set of
updates to the Dell AI Factory with NVIDIA that are less about showcasing new components and more about making AI infrastructure easier for partners to deploy, manage, and monetize across midmarket and enterprise customers.
The
updates span compute, storage, automation, and hybrid cloud integration, with a consistent theme: reduce engineering friction so MSPs and solution providers can turn AI infrastructure into repeatable services rather than one-off projects.
What changed in the Dell AI Factory
At the infrastructure level, Dell expanded support for new PowerEdge platforms built on NVIDIA Hopper and Blackwell GPUs, targeting training, inference, and emerging agentic workloads. On the data side, PowerScale and ObjectScale remain central to the AI Factory architecture, supporting large-scale unstructured data and high-throughput AI pipelines.
Automation is also playing a bigger role. The Dell Automation Platform is now embedded across AI Factory solutions, allowing partners to deploy validated, full-stack AI environments using prescriptive blueprints rather than custom builds.
Together, these updates are designed to make AI environments faster to stand up and easier to operate over time, especially in on-prem and hybrid scenarios where customers want tighter control over data, cost, and security.
Turning AI infrastructure into partner services
For channel partners, the practical impact is about time to revenue. Custom AI builds are expensive to deliver and hard to scale. Dell is positioning the AI Factory as a way to standardize that work.
“The Dell AI Factory with NVIDIA gives MSPs a faster, more repeatable path to monetize AI,” a Dell spokesperson said. “By building on Dell’s latest PowerEdge platforms, NVIDIA GPUs and validated software stacks, partners can stand up production-ready AI environments with far less engineering overhead.”
That approach is meant to support AI training, inference, and tuning services at both midmarket and enterprise scale, while keeping workloads on-prem where customers want predictable costs and stronger control over sensitive data.
Automation reduces delivery friction
As more AI workloads shift on-prem, Dell is leaning heavily on automation to help partners productize AI services rather than treat each deployment as a bespoke engagement.
“As more AI workloads move on-prem, we’re giving partners the automation and repeatability they need to productize those services,” the Dell spokesperson said. “AI solutions can now be deployed using the Dell Automation Platform, offering prescriptive deployment blueprints, lifecycle automation and integrated observability.”
For MSPs, that translates into faster onboarding, more consistent SLAs, and the ability to scale compute and storage independently as customer workloads grow, without increasing operational overhead.
Hybrid AI without operational sprawl
Storage and data movement remain critical AI bottlenecks, particularly in hybrid environments. Dell continues to position PowerScale as a core part of its hybrid AI strategy, including PowerScale for Azure.
“Dell PowerScale for Azure combines enterprise-grade file storage with seamless Azure integration,” the Dell spokesperson said. “It offers on-premises control with cloud-native agility, scales to multi-petabyte namespaces, supports multiple protocols, and is fully managed by Dell to simplify operations.”
For partners, that model supports managed AI services that span on-prem and cloud environments without fragmenting operations or security controls.
Microsoft co-engineering and partner repeatability
Microsoft integration is another area Dell is leaning into. Azure Local, Dell Private Cloud, PowerScale for Azure, and Dell’s AI PC ecosystem are positioned as co-engineered building blocks that partners can deploy consistently across customers.
“These integrations provide partners with turnkey solutions that simplify hybrid-cloud deployments,” the Dell spokesperson said. “They allow partners to deliver repeatable services across hybrid and AI-driven workloads, instead of assembling custom stacks each time.”
This reduces integration work and shifts partner focus toward lifecycle management, optimization, and higher-value services.
Clearer monetization paths for MSPs
Dell is also tightening its message around partner economics. As AI infrastructure becomes more standardized, recurring revenue opportunities move toward managed services, resilience, and ongoing optimization.
“We empower MSPs and cloud partners with solutions that reduce operational overhead and support recurring services,” the Dell spokesperson said, pointing to streamlined procurement, unified billing, and access to Dell professional services.
The takeaway is straightforward. Dell’s AI Factory updates are less about chasing AI trends and more about making AI infrastructure consumable as a service. By combining validated platforms, deeper automation, and hybrid flexibility, Dell is giving partners a clearer way to package AI offerings without carrying excessive delivery risk.
As AI budgets shift from experimentation to operations, that repeatability may be what separates partners who can scale AI services from those stuck delivering one-off deployments.
