A major shift is underway in IT, and customers are leading the charge. Across industries — retail, logistics, healthcare, and manufacturing — businesses are moving away from centralized data centers and embracing a model that brings technology closer to where value is created. The distributed enterprise isn’t just an emerging trend; it’s a complete rethinking of IT strategy.
In this blog series, I’ll explore why this shift matters, how it’s reshaping IT infrastructure, and what it means for organizations looking to stay ahead. The distributed model isn’t just about efficiency — it’s about unlocking new levels of agility, resilience, and innovation.
If the next slide has a cloud, this meeting is over!
In 1997, I found myself in the middle of a wide-area networking pitch to a key customer executive. My slides were packed with cloud diagrams, showing how devices would seamlessly connect. Five slides in, the executive stopped me cold.
“If the next slide has a cloud, this meeting is over.”
Without missing a beat, I smiled, shut my laptop, and said, “No problem. Let’s talk about what really matters. What are you trying to do?”
Long before cloud computing was even a thing, that moment taught me a lesson that has stuck with me for decades: customers bring their own priorities, their own perspectives, and their own challenges to the table. What’s important to me as a vendor might be completely irrelevant to them. Their time is limited. Their goals are non-negotiable. And the most valuable insights don’t come from talking — they come from listening. And what they’re saying today may surprise you.
Fast forward to 2025: IT’s biggest challenge isn’t what you think
At Hewlett Packard Enterprise (HPE), we have some of the most forward-thinking customers in the world. What we’re hearing is that the biggest IT challenge today isn’t simply choosing between cloud, AI, or edge computing. It’s something deeper.
Decades of IT decisions — investments in legacy architecture, vendor lock-in, and rigid operating models — have created an enormous weight that enterprises are struggling to escape. Many organizations find themselves not just burdened by technical debt, but by the outdated IT philosophies that shaped those decisions. Even modernization efforts, like shifting workloads to the cloud or navigating compliance challenges, have often resulted in fragmented, complex, and costly environments that are difficult to manage.
It’s a frustrating paradox. The technologies meant to drive innovation are now causing bottlenecks. Instead of shaping bold, forward-looking strategies, many IT leaders are spending their time maintaining toolchains and platforms built for a different era.
The solution isn’t another incremental upgrade or a slightly better cloud migration strategy. It requires something far more fundamental: a shift in mindset.
Breaking free: Clean-slate thinking
For years, IT has been shaped by a data center-first mindset. The enterprise computing model was built around large, centralized hubs that processed and stored everything, with branch locations, remote offices, and manufacturing sites acting as secondary nodes. That model worked well in an era when businesses were centralized, and network capacity was scarce.
But today, enterprises operate as dynamic, distributed ecosystems. Retail chains, healthcare providers, and logistics companies don’t function as a single monolithic entity — they are sprawling, interconnected networks, each with unique operational needs and real-time data demands. IT should reflect that reality.
Clean-slate thinking offers a different approach. Instead of trying to optimize an aging model, it asks: if we were starting from scratch today, how would we design IT for a distributed world? The answer isn’t about moving everything to the cloud or holding onto traditional infrastructure — it’s about rethinking IT as a flexible, location-aware, and real-time system that adapts to business needs rather than forcing businesses to adapt to IT limitations.
Cracks in the old model
Real-time applications are pushing IT to the edge — literally — and putting immense pressure on legacy IT infrastructure. AI-driven analytics, high-resolution cameras, and IoT sensors are generating massive amounts of data — data that must be processed instantly to be valuable.
Consider modern quality assurance systems in manufacturing. A single AI-powered inspection system can generate 100MB of data per second, all of which needs to be analyzed immediately. Sending that data over a network to a distant data center introduces 10 to 20 seconds of delay — an eternity when a pass/fail decision must be made in under a second.
Retailers face similar challenges. AI-driven theft detection systems rely on real-time video analysis. If video feeds must be sent to a centralized cloud or data center before an action can be taken, the system fails in its primary goal: preventing theft in the moment.
For industries dependent on instant decision-making, the old model simply doesn’t work. A centralized processing approach turns real-time data into historical data before it can be acted upon. And in these cases, delayed insights are as good as no insights at all.
Organizations that cling to a rigid, centralized model are putting themselves at a disadvantage. Those that embrace a distributed approach, where data is processed where it’s generated, will gain an operational edge.
Rethinking IT for 2025 and beyond
Enterprise IT wasn’t always built this way. In the early days of computing, a single central processing unit (CPU) ran everything. Early mainframes were massive, expensive machines housed in specialized rooms, accessible to only a handful of people. Adjusted for 2025 dollars, running a single-CPU mainframe in the 1950s would cost upwards of $200,000 per month — not including the space and personnel required to operate it.
The world moved on. Computing became distributed. Processing power expanded beyond a single CPU to networks of interconnected systems. But despite these advances, enterprise IT remained largely centralized, tied to the idea that data must flow to a core processing hub before it can be useful.
That mindset is outdated. Data is no longer just an asset to be stored and analyzed — it’s the lifeblood of a modern enterprise. And just like goods, services, and financial transactions, it needs to flow freely to be valuable.
Shifting from a data center-centric approach to a distributed enterprise model requires more than just new technology. It demands a new way of thinking. Today’s use cases require a model where:
Instead of a few massive data centers, IT infrastructure is spread across a network of private clouds, edge locations, and intelligent local processing nodes, using spot instances, GPU-sharing, and dynamic workload placement to maximize efficiency.
Instead of relying on centralized security models and rigid VPNs, organizations embrace Zero Trust principles, where access is identity-based and data is protected at every level.
Instead of monolithic applications that require extensive backend processing, businesses build microservices that run dynamically in containers and serverless environments.
And, instead of constantly pinging data back and forth to the cloud, AI and analytics run where data is generated, with distributed data fabrics and federated learning ensuring that insights are shared efficiently.
This is not just about efficiency. It’s about agility, resilience, and the ability to operate at the speed of business. Enterprises that distribute their compute, storage, and analytics capabilities will be positioned to make faster decisions, reduce costs, and unlock new opportunities for innovation.
What comes next?
The future of enterprise IT isn’t about holding on to outdated models—it’s about unlocking the full potential of real-time data where it’s actually needed. The distributed enterprise is the natural evolution of IT, and companies that embrace it will be at the forefront of the next wave of innovation.
Watch for my next posts where I’ll delve into data gravity — how it shapes IT strategy and why understanding the lifecycle of data is key to making the distributed enterprise a reality, as well as other aspects of this model.
See you then.