Stop me if you’ve heard this one before: AI is top-of-mind for virtually every IT organization. And GenAI is the elixir that will cure all inefficiencies that slow down businesses. (It must be true; I read it on X.) Don’t believe me? Just look at any marketing literature from both old and new companies that have reoriented their positioning to win in this AI gold rush.

Lenovo is one of the many enterprise IT solutions companies chasing the AI pot of gold; fortunately for it and its customers, Lenovo actually has the products and the know-how to deliver practical results. Like its competitors, it is combining hardware, software, and services to deliver differentiated value.

As part of its AI strategy, the company has just announced a number of new offerings to help ease the cost and the operational and complexity challenges presented by AI. Do these strike a chord? Are they relevant? Let’s start by setting the relevant context for what’s going on with enterprise AIOps, then dig into what Lenovo is doing about it and what it means for customers.

GenAI Introduces a New Set of Opportunities—and Challenges—for Enterprise IT

Before GenAI can solve all the world’s problems, enterprise IT first has to figure out how to deploy, power, manage, and pay for the hardware and software stacks that make GenAI’s magic happen. I didn’t read this on X—I’ve heard it from every IT executive I’ve spoken with on the topic.

As I touched on above, the challenges of GenAI span three buckets: financial, operational, and organizational. In other words, it’s costly, it’s complex, and it requires a lot of people. From planning to deploying to using and managing, there is not much about GenAI that adheres to traditional IT practices.

Because of this, organizations struggle to activate GenAI in the enterprise. Probably most of my readers here have seen the stats about GenAI projects, but they bear repeating. For example, recent RAND National Security Research Division study calls out AI project abandonment rates as high as 80%. While I believe this number is on the very high side, the spirit of RAND’s message still resonates. Organizations tend to treat AI projects like other IT projects, then quickly realize they are anything but ordinary because of their costs, complexity, power consumption, people needs, and other factors.

Naturally, IT solutions companies have focused on removing some of these barriers by introducing integrated stacks, partnerships, services, and the like. As evidence of this, NVIDIA CEO Jensen Huang seems to have been on stage for every major tech conference in 2024. Additionally, we’ve seen the introduction of cool-sounding names that promote server vendors’ solutions to the market. Yet after all the hype and cool names, the challenges still remain. GPUs are prohibitively expensive and consume all of the available power in the rack and the datacenter; solution stacks—once operational—are now hard to manage; a huge skills gap exists; and so on. This is how the market gets to 80% abandonment rates, quickly descending from inflated expectations to the depths of disillusionment.

Lenovo Delivers GPUaaS, AIOps, and Neptune

This is where Lenovo comes in. In its latest announcement, Lenovo attempts to address some of these challenges with a few subtly impactful product and service announcements. The first is for the company’s GPU-as-a-service (GPUaaS) offering, which allows customers to better leverage expensive GPUs across the enterprise.

Let’s say you are a state government IT executive with dozens of agencies that operate as separate shops—individual teams, individual budgets, etc. The state CIO, on a directive from the governor, makes implementing AI a top priority for every agency. GPUaaS allows all of these agencies to leverage the same farm of GPUs, with usage metering and billback built in, via Lenovo Intelligent Computing Orchestration (LiCO). Organization-wide costs come down, and each agency has the necessary horsepower to train and tune its AI models.

As somebody who has lived in this world—I have been that state government IT exec—I can immediately see the benefits of GPUaaS. While there are still challenges around how budgets and cross-agency utilization are prioritized and managed, this solution can deliver real value to organizations standing up AI in their datacenters. More than that, GPUaaS addresses all three of the big challenges facing IT mentioned earlier—cost, ops, organization.

Lenovo’s second announcement, about AIOps, goes right to the heart by directly addressing the operational and complexity challenges of enterprise IT. (Cost is more of an indirect benefit.) The substance of it is that Lenovo’s XClarity One hybrid cloud management platform will incorporate predictive analytics and GenAI to deliver greater levels of reliability and cyber resilience for Lenovo infrastructure.

AIOps is an IT trend that has been around for some time. While Lenovo’s move is somewhat of a catch-up play, it does allow the company to check the box for an element of enterprise IT readiness that is critical for achieving broad adoption in this segment. Further, while much of the competition’s capabilities in this area have come via acquisition, Lenovo’s XClarity One is the fruit of in-house design.

As a techie who grew up in the server/network management space (Want to talk about managing Novell NLMs and why IPX is better than IP? I’m your guy), I like what Lenovo has done with XClarity One. In fact, I wish the company would lean into this goodness more. For instance, the cloud-based nature of XClarity One makes it simple to deploy and consume. Further, this model enables IT organizations to manage their Lenovo infrastructure through the proverbial single pane of glass.

Finally, Lenovo has built on its big HPC and AI winner by announcing some slight enhancements to its Neptune liquid-cooling technology. Specifically, Lenovo reported that Neptune now has built-in real-time energy efficiency monitoring. This enables organizations to better understand how efficiently their infrastructure is operating, allowing for proactive tweaks and tuning to drive down the all-important power usage efficiency (PUE) rating.

Does Lenovo Differentiate?

Frankly, Lenovo’s challenge is not whether it has a legitimate and differentiated play in enterprise IT in general and AI in particular. In both cases, the answer is a simple yes. The real challenge is telling Lenovo’s story to the enterprise.

The company has done an excellent job of building a business that dominates in the hyperscale and HPC markets. These are two highly competitive markets in terms of performance and resilience/reliability. For whatever reason, though, the company has seemed a little hesitant about aggressively pursuing the commercial enterprise market. Strangely, Lenovo’s business in this area is largely the same business that was run for decades by IBM—perhaps the all-time most trusted brand in enterprise IT.

Lenovo was ahead of the market in building and enabling the AI ecosystem (Check out the company’s AI innovator program). Further, its infrastructure is deployed for brands and retailers that are used and visited by most people on a daily business. Yet despite all of this innovation, most IT professionals don’t know just how rich of a portfolio the company has.

Given Lenovo’s new leadership, I expect that will change. If the company leverages all of the pieces of its technical and business portfolio, it will be a force to reckon with.